Financial toxicity profiles and influencing factors among ovarian cancer Patients: a latent profile analysis

Financial toxicity profiles and influencing factors among ovarian cancer Patients: a latent profile analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Financial toxicity profiles and influencing factors among ovarian cancer Patients: a latent profile analysis Fengye Sun, Qian Wang, Yaru Zhang, Yingtao Meng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8660541/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 4 You are reading this latest preprint version Abstract Background Financial toxicity is a ubiquitous challenge for the ovarian cancer patient population. Targeting high-risk groups for financial toxicity with precise interventions can alleviate this burden and enhance patients' quality of life. Therefore, this study aimed to analyze the current status and latent profiles of financial toxicity among ovarian cancer patients and explore the factors influencing different profiles of financial toxicity. Methods A cross-sectional study design was employed. Using convenience sampling, 342 ovarian cancer patients hospitalized in a provincial cancer hospital in Shandong Province from July to November 2025 were enrolled. Data were collected using self-designed questionnaires for general and clinical information, Comprehensive Scores for Financial toxicity based on Patient‑Reported Outcome Measures (COST‑PROM), Simplified version of the 10‑item Connor‑Davidson Resilience Scale (CD‑RISC‑ 10), the Medical Coping Modes Questionnaire (MCMQ), and Social Support Rating Scale (SSRS). Latent profile analysis (LPA) was conducted to identify subgroups based on financial toxicity levels. Multinomial logistic regression was used to analyze the factors influencing financial toxicity across different profiles. Results Among the 342 ovarian cancer patients, the median financial toxicity score was 17.10±(7.88). Latent profile analysis identified three distinct financial toxicity profiles: mild (27.2%), moderate (50.9%), and severe (21.9%). Multinomial logistic regression revealed that the severity of financial toxicity was significantly associated with employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, out-of-pocket medication expenses, confrontation, resignation. Conclusion Significant variability in financial toxicity exists among the three groups of ovarian cancer patients, with over 70% experiencing moderate to severe levels. Healthcare professionals can develop precise nursing interventions based on the profile characteristics and influencing factors of financial toxicity to alleviate patients' financial burden, optimize treatment outcomes, and enhance their quality of life. Ovarian Cancer Financial Toxicity Latent Profile Analysis China Figures Figure 1 Background Ovarian cancer is one of the most common malignancies of the female reproductive system, posing a serious threat to women's health [ 1 ] . In 2022 alone, an estimated 324,400 new cases were diagnosed worldwide, resulting in approximately 206,800 deaths [ 2 ] . China contributed substantially to this burden, with about 61,100 new cases and 32,600 deaths annually, representing a significant proportion of global ovarian cancer mortality [ 3 ] . Of particular concern is the rising global burden over the past decade, with the incidence of ovarian cancer having increased at an average annual rate of 3.2% and mortality by 1.8%, maintaining the highest case-fatality rate among gynecological malignancies [ 4 – 6 ] . Recent advancements in anti-cancer therapeutics have led to the continuous evolution of treatment modalities for ovarian cancer, encompassing surgery, chemotherapy, targeted therapy, and other multimodal approaches, which have significantly improved patient survival [ 7 ] . However, these innovative treatments are associated with high costs, imposing a substantial economic burden on patients [ 8 ] . A global study synthesizing data from 204 countries revealed that the socioeconomic burden of ovarian cancer accounts for approximately 0.1% of the global Gross Domestic Product (GDP) [ 9 ] . Consistent with this global perspective, research [ 10 ] from China indicates that households with cancer patients are more likely to experience excessive healthcare expenditure, with 77% of cancer patients perceiving the financial burden as catastrophic. The concept of "financial toxicity" was first introduced by Bullock [ 11 ] in 2013 and later elaborated by Zafar [ 12 ] to describe the financial hardship and resultant physical and psychological distress experienced by cancer patients due to medical costs. With advances in cancer treatment, financial toxicity has become increasingly prevalent among cancer survivors [ 13 ] . It is estimated that 35% to 58% of gynecological cancer survivors experience financial toxicity [ 14 – 17 ] . Notably, ovarian cancer has been identified as the most costly to treat among gynecological cancers, and its survivors are consequently at the highest risk for severe financial toxicity [ 18 ] . The adverse effects of financial toxicity extend beyond financial distress to encompass a multidimensional burden that detrimentally impacts treatment adherence, psychological well-being, and overall quality of life. For patients with ovarian cancer, the high costs associated with novel therapeutic agents, such as PARP inhibitors and anti-angiogenic drugs, can lead to catastrophic health expenditures [ 19 ] . This severe financial toxicity directly compromises treatment adherence, resulting in the delay, skipping, or outright abandonment of recommended therapies, which may ultimately contribute to suboptimal clinical outcomes and reduced survival rates [ 20 ] . Concurrently, persistent concerns over medical debt and financial insecurity significantly exacerbate levels of depression, anxiety, and diminished health-related quality of life [ 21 , 22 ] . Furthermore, this burden often extends to family members, depleting household savings, altering career paths, and exacerbating socioeconomic disparities in access to cancer care and treatment outcomes [ 23 ] . Recognizing these profound and interconnected harms underscores the critical necessity of investigating the factors that influence financial toxicity in patients. Previous studies have identified a range of factors associated with financial toxicity in cancer patients. These encompass socio-demographic characteristics, such as age [ 24 ] , marital status [ 25 ] , educational attainment [ 15 ] , employment status, monthly per capita income [ 26 ] , and type of health insurance [ 27 ] . Disease-related factors, including cancer stage, treatment modalities [ 15 ] , out-of-pocket expenses [ 28 ] , and the presence of comorbidities [ 29 ] , also play a significant role. Furthermore, research indicates that patients' coping strategies in response to their illness can influence their experience of financial toxicity [ 30 ] . Psychosocial factors, particularly perceived social support [ 31 ] and psychological resilience, have been recognized as protective factors against financial toxicity in this population [ 32 ] . Latent profile analysis (LPA) [ 33 ] , a specific type of latent class model, identifies distinct subgroups within a population based on individuals' response patterns across observed indicator variables. This person-centered approach is more effective than traditional variable-centered analyses in uncovering the heterogeneity of financial toxicity manifestations, thereby facilitating the development of more targeted interventions. While prior studies have explored factors influencing financial toxicity in ovarian cancer patients, they have predominantly employed variable-centered methodologies, which may overlook the intrinsic heterogeneity within the patient population. Therefore, this study aims to identify latent categories of financial toxicity among ovarian cancer patients using LPA and to examine the factors associated with membership in each distinct category. The findings are expected to provide an empirical basis for developing personalized intervention strategies to alleviate financial toxicity and ultimately improve the quality of life in this patient group. Methods Study design A cross-sectional descriptive study was conducted from July to November 2025. Using the convenience sampling method, patients with ovarian cancer who were receiving treatment at a tertiary grade A cancer specialty hospital in Shandong Province, Chinese mainland, were selected as the research subjects. Participants The inclusion criteria were:(1) Diagnosed with ovarian cancer; (2) Age ≥ 18 years; (3) Be cognitively aware of their diagnosis and treatment costs; (4) No mental illness or cognitive impairment; (5) Providing written informed consent voluntarily. Those who have communication difficulties or those whose conditions are too severe to cooperate will be excluded. Sample size According to the sample size calculation method of the multi-factor analysis approach, the sample size should be 5 to 10 times the number of research variables [ 34 ] . The research variables include 9 general data variables, 11 clinical-related data variables, 3 dimensions of the financial toxicity comprehensive assessment scale, 3 dimensions of disease coping styles scale, 1 dimension of the simplified psychological resilience scale, and 3 dimensions of the social support assessment scale, totaling 30 variables. Considering a 10% inefficiency rate, the sample size was expanded to 334 cases. A total of 350 questionnaires were distributed, among which 342 received valid responses, resulting in an effective recovery rate of 97.71%. Measures General Demographic Data Questionnaire Based on a review of relevant literature, the research team independently developed a questionnaire for collecting general demographic data, which included the patient's age, marital status, educational level, per-capita monthly income, employment status, type of medical insurance, number of dependent children, number of dependent elders, employment status of adult children. Clinical Data Questionnaire Combining the available clinical data, the clinical data questionnaire includes: time since diagnosis, disease stage, comorbid chronic conditions, metastasis status, history of surgery, history of chemotherapy, history of radiotherapy, history of targeted therapy, total hospitalization costs, out-of-pocket medication expenses, household disposable savings. Comprehensive Scores for FT based on Patient‑Reported Outcome Measures (COST‑PROM) This scale was developed by De Sousa et al. [ 35 ] from the University of Chicago in 2014. It consists of 11 items and uses a Likert 5-point scale, with 0-4, where 0 represents "not at all" and 4 represents "very much". Items 2, 3, 4, 5, 8, 9, and 10 are reverse-scored. The lower the score, the more severe the financial toxicity . The scale has demonstrated good reliability and validity in cancer populations, including breast cancer patients [ 36 ] , supporting its sound psychometric properties. In this study, the Cronbach's α was 0.800. Simplified version of the 10‑item Connor‑Davidson Resilience Scale (CD‑RISC‑ 10) The simplified version of the Psychological Resilience Scale was derived by Campbell-shills [ 37 ] from the 25-item CD-RISC. The full scale consists of 10 items and is scored on a 5-point Likert scale, where "never like this" is scored as 1, "rarely like this" as 2, "sometimes like this" as 3, "often like this" as 4, and "always like this" as 5. The total score is the sum of the scores of each item, and the higher the total score, the better the psychological resilience. In this study, the Cronbach's α coefficient was 0.790. Medical Coping Modes Questionnaire (MCMQ) This questionnaire was developed by Feifel et al. [ 38 ] . It is mainly used in cancer and chronic disease patients in China, covering three dimensions: confrontation, avoidance, and resignation, with a total of 20 items. The confrontation dimension includes 8 items, namely items 1, 2, 5, 10, 12, 15, 16, and 19; the avoidance dimension includes 7 items, namely items 3, 7, 8, 9, 11, 14, and 17; and the resignation dimension includes 5 items, namely items 4, 6, 13, 18, and 20. It uses a Likert 4-point rating scale ranging from 0 to 4. Among them, items 1, 4, 9, 10, 12, 13, 18 and 19 are those using the reverse scoring method.The score for each coping event is calculated from low to high as 1, 2, 3, and 4, with a total score ranging from 20 to 80. The higher the score of each dimension, the more likely the patient is to adopt this coping method. This questionnaire has good reliability and validity and has been verified [ 39 ] . In this study, the Cronbach's α for the three dimensions were 0.785, 0.718, and 0.786 respectively. Social Support Rating Scale (SSRS) This scale was compiled and revised by Xiao [ 40 ] and is used to assess the overall level of an individual's social support. It consists of 3 dimensions: subjective support, objective support, and the utilization of social support, with a total of 10 items. Items 1-4, 8-10 use the Likert 4-point rating method. Item 5 is scored from "no support" to "complete support" with 1-4 points respectively. Items 6-7 are scored based on the number of sources, with 0 points for "no any source". The higher the total score, the better the social support level. In this study, the Cronbach's α of this scale is 0.751. Data collection Firstly, the researchers obtained the research permission from the nursing department and received the informed consent from the head nurse of the ovarian tumor ward. They distributed the questionnaires to eligible ovarian cancer patients through the form of Questionnaire Star and paper questionnaires. Before the formal survey, the researchers received training on ovarian cancer knowledge, familiarized themselves with the common treatment methods and nursing measures for patients, and familiarized themselves with the patient history in the ward in advance to answer patients' questions during the process. During the survey, the researchers explained the purpose, methods, benefits and potential risks of the study to the participants in clear and understandable language, informed the participants of their right to withdraw from the study at any time, obtained the informed consent from the patients and signed the consent form, and then officially began the survey. The researchers conducted a pre-survey in July 2025, and further improved the questionnaire based on the results of the pre-survey to form the final version of the questionnaire. The questionnaire was filled out by the patients themselves, and when necessary (for example, due to cultural limitations), the researchers would provide assistance. After filling out the questionnaire, it was collected on the spot and carefully reviewed. Missing items were supplemented in a timely manner and invalid questionnaires were eliminated. Data analysis The data were statistically analyzed using SPSS 22.0 and Mplus 8 software. A difference was considered statistically significant when P < 0.05. Continuous variables that followed a normal distribution were described using the mean ± standard deviation ( x ( _ ) ± SD ), while non-normally distributed data were described using the median and interquartile range M ( P 25, P 75). Categorical variables were compared using the chi-square test or Fisher’s exact test when more than 20% of cells had an expected count less than 5 [ 41 ] . Continuous variables were compared using analysis of variance (ANOVA). To identify key factors associated with subgroup classification, a multinomial logistic regression model was constructed, incorporating sociodemographic, disease-related, economic variables and disease coping style variable as independent predictors. Variable selection for the Multinomial model was based on significant findings from prior univariate analyses (i.e., chi-square test and ANOVA). Ethics considerations This study has been successfully approved by the Ethics Committee of Shandong First Medical University Affiliated Tumor Hospital (Approval Number: 202508030). All research procedures strictly followed the ethical guidelines of the Helsinki Declaration, ensuring the informed consent, voluntariness, absence of harm, and privacy protection rights of the participants. Results Common method bias To assess the potential for common method bias (CMB) arising from the self-reported nature of our data, Harman's single-factor test was conducted. The results of the exploratory factor analysis revealed the presence of 14 distinct factors with eigenvalues greater than 1. The first factor accounted for 27.22% of the variance, which is below the critical threshold of 40% [ 42 ] , indicating that common method bias is not a serious concern in this study Demographic and clinical characteristics of the participants The mean age of the participants was 57.65 years (SD = 10.62). A total of 63.5% of patients had been diagnosed for less than one year, and 96.5% were married. Nearly one-third of the patients had attained a bachelor’s degree or higher. Regarding monthly income, 58.8% reported a per-capita income between 3,000 and 4,999 RMB, and 53.5% were retired. In terms of medical insurance, 65.5% were covered by employee basic medical insurance. With respect to family responsibilities, 61.4% of patients were supporting more than one child, while 69.0% were caring for one or fewer elderly individuals. Additionally, 86.3% had children who were already employed. Clinically, 49.4% of patients were at disease stage II or lower. 19.0% of the patients have Comorbid chronic conditions; 10.8% of patients presented with tumor metastasis. Regarding treatment, 74.6% had undergone surgery for ovarian cancer, 77.5% had received chemotherapy, 4.1% had undergone radiotherapy, and 29.5% had received targeted therapy. Financially, 65.2% of patients had total hospitalization costs ≤100,000 RMB, 88.9% reported out-of-pocket medication expenses ≤50,000 RMB, and 80.4% had household disposable savings ≤100,000 RMB. The detailed baseline characteristics of the participants, including age, disease status, and clinical features, are presented in Table 1. Table 1 Patient characteristics and COST values (N= 342) Characteristic N (%) COST F/X 2 Value P Age (Years) 57.65±10.62 17.10±7.88 0.866 * 0.732 Marital status 1.070 ** 0.302 Married 330(96.5%) 17.08±7.79 Unmarried 12(3.5%) 17.75±10.50 Education level 4.026 ** 0.003 Primary school and below 86(25.1) 14.59±7.74 Middle school 84(24.6) 17.08±7.91 High school / junior college 54(15.8) 19.74±9.40 bachelor’s degree or higher 118(34.5%) 17.73±6.70 Per-capita monthly income 15.290 ** ＜0.001 ＜1000 51(14.9%) 12.37±6.57 1000-2999 42(12.3%) 15.91±7.36 3000-4999 201(58.8%) 17.29±7.52 ≥5000 48(14.0%) 22.34±7.97 Employment Status 11.439 ** ＜0.001 Employed 27(7.9%) 20.26±7.40 retired 183(53.5%) 18.38±7.48 farming 132(38.6%) 14.68±7.93 Type of medical insurance Urban and Rural Resident Basic Medical Insurance 118(34.5) 11.60±7.08 0.669 ** 0.414 Employee Basic Medical Insurance 224(65.5) 20.00±6.66 Number of dependent children 0.132 ** 0.756 ≤1 132(38.6) 18.046±7.897 ＞1 220(61.4%) 16.505±7.835 Number of dependent elders 7.000 ** 0.009 ≤1 236(69.0%) 17.67±8.35 ＞1 106(31.0%) 15.83±6.60 Employment status of adult children ＜0.001 ** 0.984 Not employed 47(13.7) 17.40±7.70 Employed 295(86.3) 17.05±7.92 Time since diagnosis （ year ） 9.184 ** ＜0.001 ≤1 217(63.5) 18.32±8.07 1-5 87(25.4) 14.14±6.64 ≥5 38(11.1) 16.90±7.77 Disease stage 2.532 ** 0.081 ≤Ⅱ 169(49.4%) 18.07±8.15 Ⅲ 109(31.9%) 16.19±8.04 Ⅵ 64(18.7%) 16.09±6.60 Table 1 (continued) Characteristic N (%) COST F/X 2 Value P Comorbid chronic conditions 9.586 ** 0.002 0 277(81.0%) 17.42±8.16 1 65(19.0%) 15.74±6.45 Metastasis status 3.768 ** 0.053 0 305(89.2%) 17.66±7.86 1 37(10.8%) 12.51±6.50 History of surgery 0.047 ** 0.828 0 87(25.4%) 18.92±7.89 1 255(74.6%) 16.48±7.80 History of chemotherapy 0.434 ** 0.511 0 77(22.5%) 18.33±8.22 1 265(77.5%) 16.74±7.76 History of radiotherapy 0.048 ** 0.826 0 328(95.9%) 17.30±7.83 1 14(4.1%) 12.36±7.83 History of targeted therapy 0.223 ** 0.627 0 241(70.5%) 17.94±7.81 1 101(29.5%) 15.10±7.74 Total hospitalization costs 1.342 ** 0.248 ≤10 223(65.2%) 18.56±7.55 ＞ 10 119(34.8%) 14.37±7.80 Out-of-pocket medication expenses 0.096 ** 0.757 ≤5 304(88.9%) 17.85±7.61 ＞ 5 38(11.1%) 11.13±7.60 Household disposable savings 1.594 ** 0.208 ≤10 275(80.4%) 15.70±7.54 ＞ 10 67(19.6%) 22.87±6.57 * ANOVA and ** chi-square test Identification of financial toxicity subgroups Using the 11 items of the COST-PROM scale as manifest variables, five latent profile analysis models were successively established. Their fit indices are presented in Table 2. As the number of profiles in the models increased, entropy values all exceeded 0.8, while the values for AIC, BIC, and aBIC showed a declining trend. Given that the LMRT [ 43 ] value for Model 3 was 0.007, whereas for Model 4 it was 0.213 (>0.05), Model 3 was deemed to be significantly superior to Model 2 and was considered the most clinically meaningful. Therefore, Model 3 was identified as the optimal and most ideal model. Detailed model fit indices are provided in Table 2. The characteristics of each latent profile were defined as follows: C1: Severe Financial Toxicity Profile (27.2%); C2: Moderate Financial Toxicity Profile (50.9%); C3: Mild Financial Toxicity Profile (21.9%). Detailed information is illustrated in Figure 1. Table 2 Fit metrics of each model Models Log(L) AIC BIC ABIC Entropy LMRT BLRT Probability of category 1 -6098.229 12240.457 12324.823 12255.034 2 -5758.522 11585.045 11715.429 11607.573 0.866 0 0 0.415/0.585 3 -5681.943 11455.885 11632.286 11486.364 0.821 0.0074 0.0079 0.272/0.509/0.219 4 -5584.270 11284.540 11506.959 11322.970 0.925 0.2128 0.2186 0.345/0.363/0.143/0.149 5 -5437.090 11014.180 11282.617 11060.561 1.000 0 0 0.272/0.175/0.409/0.012/0.132 Differences in financial toxicity among the three latent profiles Table 3 presents the individual differences among these three latent profiles. Variables such as per-capita monthly income, employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, metastasis status, history of chemotherapy, radiotherapy, and targeted therapy, total hospitalization costs, out-of-pocket medication expenses, household disposable savings, psychological resilience, confrontation and resignation subscale scores, subjective support, and the utilization of social support showed significant differences across the three subgroups. Related factors associated with cancer patients’ financial toxicity The three subgroups of financial toxicity trajectories in ovarian cancer patients were defined as the dependent variable. Independent variables included factors that were statistically significant in prior univariate analyses: per-capita monthly income, employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, metastasis status, history of chemotherapy, radiotherapy, and targeted therapy, total hospitalization costs, out-of-pocket medication expenses, household disposable savings, psychological resilience, confrontation and resignation subscale scores, subjective support, and the utilization of social support. A multinomial logistic regression model was employed for the analysis. All independent variables underwent collinearity diagnostics, with tolerance values greater than 0.1 and variance inflation factors (VIF) below 10 [ 44 ] , confirming the absence of multicollinearity. Compared with Profile 3, patients in Profiles 1 and 2 had a larger number of dependent elderly individuals and a higher likelihood of having chronic comorbidities. Meanwhile, relative to Profile 3, patients in Profile 1 were associated with higher out-of-pocket medication expenses, a higher probability of having a time since diagnosis of 1–5 years, and a greater tendency to adopt a resignation coping style when facing the disease. In contrast, patients who were retired and those covered by employee medical insurance were more likely to belong to Profile 1. Compared with Profile 3, patients who employed a confrontation coping style and those diagnosed at stage III or earlier were less likely to be classified into Profile 2 but more likely to belong to Profile 3. Details are presented in Table 4. Table 3 Demographic, disease-related characteristics, psychological resilience, coping styles, and social support by latent profiles (N= 342) C1 (n=93) C2(n=174) C3(n=75) F/X 2 P Age (Years) 57.31±10.38 57.73±10.71 57.90±10.83 0.787 a 0.854 Marital status 0.090 c 0.956 Married 92(98.9) 168(96.6) 72(96.0) Unmarried 3(1.1) 6(3.4) 3(4.0) Education level 11.048 b 0.087 Primary school and below 31(33.3) 44(25.3) 11(14.7) Middle school 22(23.7) 43(24.7) 19(25.3) High school / junior college 13(14.0) 23(13.2) 18(24.0) bachelor’s degree or higher 27(29.0) 64(36.8) 27(36.0) Per-capita monthly income 34.844 b ＜0.001 ＜1000 25(26.9) 22(12.6) 3(4.0) 1000-2999 12(12.9) 21(12.1) 9(12.0) 3000-4999 51(54.8) 110(63.2) 41(54.7) ≥5000 5(5.4) 21(12.1) 22(29.3) Employment Status 21.461 b ＜0.001 Employed 3(3.2) 14(8.0) 10(13.3) retired 37(39.8) 102(58.6) 44(58.7) farming 53(57.0) 58(33.3) 21(28.0) Type of medical insurance 124.723 c ＜0.001 Urban and Rural Resident Basic Medical Insurance 74(81.3) 31(17.8) 11(14.7) Employee Basic Medical Insurance 17(18.7) 143(82.2) 64(85.7) Number of dependent children 2.524 b 0.283 ≤1 31(33.3) 67(38.5) 34(45.3) ＞1 62(66.7) 107(61.5) 41(54.7) Number of dependent elders 14.486 b 0.001 ≤1 62(66.7) 109(62.6) 65(86.7) ＞1 31(33.3) 65(37.4) 10(13.3) Employment status of adult children 1.310 b 0.52 Not employed 16(17.2) 22(12.64) 9(12.0) Employed 77(82.8) 152(87.36) 66(88.0) Time since diagnosis(year) 21.106 b ＜0.001 ≤1 49(52.7) 107(61.5) 61(81.3) 1-5 36(38.7) 44(25.3) 7(9.3) ≥5 8(8.6) 23(13.2) 7(9.3) Disease stage 15.099 b 0.005 ≤Ⅱ 41(44.1) 78(44.8) 50(66.7) Ⅲ 34(36.6) 55(31.6) 20(26.7) Ⅵ 18(19.4) 41(23.6) 5(6.7) Table 3 (continued) C1 (n=93) C2(n=174) C3(n=75) F/X 2 P Comorbid chronic conditions 22.493 b ＜0.001 0 76(81.7) 127(73.0) 74(98.7) 1 17(18.3) 47(27.0) 1(1.33) History of other surgeries 3.220 b 0.200 0 83(89.2) 145(83.3) 68(90.7) 1 10(10.8) 29(16.7) 7(9.3) Metastasis status 0 73(78.5) 159(91.4) 73(97.3) 17.045 b ＜0.001 1 20(21.5) 15(8.6) 2(2.7) History of surgery 4.994 b 0.082 0 17(18.3) 45(25.9) 25(33.3) 1 76(81.7) 129(74.1) 50(66.7) History of chemotherapy 6.446 b 0.040 0 18(19.4) 34(19.5) 25(33.3) 1 75(80.6) 140(80.5) 50(66.7) History of radiotherapy 6.930 b 0.031 0 85(91.4) 169(97.1) 74(98.7) 1 8(8.6) 5(2.9) 1(1.3) History of targeted therapy 8.688 b 0.013 0 55(59.1) 127(73.0) 59(78.7) 1 38(40.9) 47(27.0) 16(21.3) Total hospitalization costs 25.961 b ＜0.001 ≤100,000 41(44.1) 124(71.3) 58(77.3) ＞100,000 52(55.9) 50(28.7) 17(22.7) Out-of-pocket medication expenses( yuan) 27.939 b ＜0.001 ≤50,000 69(74.2) 164(94.3) 71(94.7) ＞50,000 24(25.8) 10(5.7) 4(5.3) Household disposable savings( yuan) 31.127 b ＜0.001 ≤100,000 89(95.7) 140(80.5) 46(61.3) ＞100,000 4(4.3) 34(19.5) 29(38.7) psychological resilience 22.043±7.791 27.39±7.65 32.63±5.81 5.707 a ＜0.001 confrontation 14.398±2.542 17.71±5.11 22.85±4.04 11.984 a ＜0.001 resignation 16.473±2.636 12.40±4.16 8.63±3.01 20.151 a ＜0.001 avoidance 20.376±3.260 20.01±3.40 19.81±3.19 1.249 a 0.248 Social support 13.451±15.953 34.71±6.25 34.00±0.00 1.608 a 0.122 subjective support, 18.989±4.187 20.61±3.01 22.67±3.71 9.704 a ＜0.001 objective support 3.054±3.595 7.85±2.38 8.00±0.00 1.020 a 0.402 The utilization of social support 5.688±1.260 7.09±1.90 8.85±2.06 21.440 a ＜0.001 Note: a One-way analysis of variance. b Pearson chi-squared test. c Fisher’s exact test. Table 4 Multinomial logistic regression analysis of latent profiles in Ovarian cancer patients (N= 342) B SE OR P 95%CI C1 vs C3 Employment Status (reference: farming) retired -2.840 1.275 0.058 0.026 0.005-0.710 Type of medical insurance(reference: Urban and Rural Resident Basic Medical Insurance) Employee Basic Medical Insurance -3.384 0.692 0.034 ＜0.001 0.009-0.132 Number of dependent elders(reference: ≤ 1) ＞1 1.645 0.668 5.180 0.014 1.399-19.177 Time since diagnosis(reference: ＞ 5year) 1-5year 2.772 1.026 15.993 0.007 2.140-119.536 Comorbid chronic conditions(reference: No) Yes 3.279 1.255 26.544 0.009 2.267-310.826 Out-of-pocket medication expenses(reference: ≤ 5) ＞5 2.874 1.127 17.708 0.011 1.944-161.340 resignation 0.377 0.127 1.457 0.003 1.136-1.870 C2 vs C3 Number of dependent elders(reference: ≤ 1) ＞1 1.528 0.497 4.609 0.002 1.741-12.202 Disease stage(reference: Ⅵ) ≤Ⅱ -1.493 0.615 0.225 0.015 0.067-0.750 Ⅲ -1.338 0.664 0.262 0.044 0.071-0.965 Comorbid chronic conditions(reference: No) Yes 3.569 1.144 35.479 0.002 3.766-334.210 confrontation -0.161 0.054 0.851 0.003 0.766-0.946 Note: C1: Severe Financial Toxicity Profile; C2: Moderate Financial Toxicity Profile ; C3: Mild Financial Toxicity Profile. Discussion To our knowledge, this study is the first to apply latent profile analysis to identify distinct profiles of financial toxicity and their associated factors among ovarian cancer patients. The analysis revealed three distinct financial toxicity profiles: C1 (severe financial toxicity), C2 (moderate financial toxicity), and C3 (mild financial toxicity). Factors found to be associated with profile membership included employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, out‑of‑pocket medication expenses, and the confrontation and resignation coping styles. These findings offer a novel perspective by recognizing the heterogeneity within the ovarian cancer population rather than treating them as a homogeneous group. They provide an evidence‑based foundation for developing tailored interventions aimed at mitigating financial toxicity based on the identified influencing factors. Furthermore, this study contributes to a deeper understanding of financial toxicity among ovarian cancer patients within the unique socioeconomic context of China. This study revealed that the average financial toxicity score among ovarian cancer patients was approximately 17.10 ± 7.88. Notably, 78.1% of patients self-reported moderate to severe financial toxicity, with 27.2% experiencing severe financial toxicity. These findings are consistent with broader research on cancer-related financial toxicity [ 45 ] , which indicates that nearly one-quarter of patients report a severe financial burden. They also align with the results reported by Vasquez-Trespalacios et al. [ 26 ] regarding financial toxicity in advanced ovarian cancer patients. The study by Bouberhan et al. [ 46 ] showed that 31% of ovarian cancer patients experienced severe financial toxicity, a proportion slightly higher than that found in our study. This discrepancy may be attributed to their use of a higher cutoff score (23 points) to identify high financial toxicity, which effectively lowers the threshold for defining severe financial toxicity. In contrast, Smith et al. [ 27 ] reported that 44% of gynecologic cancer patients had financial toxicity. This difference is likely because ovarian cancer patients constituted only 21% of their sample, which included patients with various gynecologic malignancies. Thus, our findings provide valuable data on the prevalence and severity of financial toxicity specifically among ovarian cancer patients in China. More importantly, by employing Latent profile analysis rather than relying on simple COST-PROM score thresholds, our study offers a more nuanced, person-centered understanding of the heterogeneity in financial burden within this population. This study identified caring for more than one elderly dependent as a significant predictor of heightened financial toxicity in ovarian cancer patients, with a higher prevalence in moderate/severe financial toxicity groups. This association can be largely attributed to the traditional norm of filial piety in Chinese society, which reinforces families’ primary responsibility for elders’ financial and care needs [ 47 ] . When combined with the sustained, high costs of ovarian cancer treatment, multi-elder care creates a compounded financial burden that rapidly depletes household resources, reduces economic resilience, and intensifies perceived financial stress. This finding aligns with evidence linking increased family caregiving burdens to worse financial toxicity outcomes in cancer populations, particularly where formal support systems are limited [ 48 ] . This study identified the presence of chronic comorbidities as a significant predictor of heightened financial toxicity in ovarian cancer patients, with a higher prevalence in moderate/severe financial toxicity groups. This association can be explained through multiple intertwined pathways. First, comorbidities directly exacerbate the economic burden by introducing sustained, overlapping costs for concurrent cancer treatment and chronic disease management (e.g., medications, monitoring) [ 49 , 50 ] . Second, they increase treatment complexity, potentially influencing oncology care plans (e.g., adjusted chemotherapy, prolonged hospitalization), thereby elevating total direct medical expenditures [ 51 , 52 ] . This finding aligns with established evidence recognizing comorbidities as a key risk factor for catastrophic health expenditures in cancer populations and is consistent with observations that ovarian cancer patients with severe financial toxicity often face more complex health and social needs [ 53 ] . Consequently, integrated care models that address both cancer and chronic conditions, coupled with proactive financial navigation, are essential to mitigate this multifaceted burden. Our study identifies retirement status as a significant protective factor against severe financial toxicity in ovarian cancer patients, with retirees demonstrating a higher propensity for mild financial toxicity profiles—a finding consistent with the observations of Zhang et al. [ 54 ] . The underlying mechanisms can be attributed to retirees' stable pension or savings-derived fixed income, which, being independent of work capacity, remains uninterrupted by treatment-related sick leave or disability, thereby providing a fundamental "financial ballast" for long-term care, coupled with their predominant urban residence that ensures proximate access to tertiary hospitals with specialized oncology units, significantly reducing the indirect costs and time burdens associated with long-distance travel, accommodation, and family caregiving for standardized treatment [ 55 ] . This stands in stark contrast to patients engaged in farming, who typically reside in rural areas, rely on physically demanding labor with inherent income unpredictability and vulnerability, and face immediate severe impairment of their core earning capacity upon diagnosis; moreover, the substantial hidden financial toxicity arising from non-medical expenses such as travel, lodging, and family lost wages during necessary trips to urban medical centers further exacerbates their financial burden [ 56 ] . This study reveals that ovarian cancer patients enrolled in urban employee basic medical insurance experience significantly lower financial toxicity compared to those covered by urban and rural resident basic medical insurance, a finding consistent with research by Yusuf, et al. [ 57 ] This disparity is rooted in the inherent structural inequities within China's multi-tiered health insurance system. The urban employee insurance typically offers higher reimbursement rates and higher annual payment caps, more effectively covering hospitalization and treatments within the national reimbursement drug list, thereby directly buffering patients' out-of-pocket expenses. In contrast, the urban and rural resident insurance, adhering to the principle of "broad coverage with basic benefits," features lower reimbursement rates and caps, resulting in patients bearing a substantially larger share of medical costs. Despite the near-universal coverage of basic insurance in China, design elements such as formulary restrictions, deductibles, and co-payment rates maintain high levels of personal cash expenditure [ 58 ] . This burden is disproportionately amplified for the resident insurance population, whose coverage is inherently weaker. Furthermore, the low penetration of supplementary protections like commercial health insurance fails to adequately bridge the coverage gaps in the basic schemes, further exacerbating the financial vulnerability of patients reliant on resident insurance [ 59 ] . Consequently, the disparity in financial toxicity is not merely a reflection of individual financial capacity but a direct manifestation of the unequal "depth of coverage" conferred by different insurance institutions during a personal health crisis. Our study identified that patients diagnosed with ovarian cancer within 1 to 5 years were significantly more likely to experience severe, rather than mild financial toxicity, a finding that underscores the protracted economic vulnerability inherent to this disease’s chronic and recurrent trajectory. As highlighted in a JAMA review [ 60 ] , the standard of care following initial intensive therapy often entails years of maintenance treatment, leading to the relentless accrual of out-of-pocket expenses. This is compounded by the progressive erosion of financial reserves: while savings or short-term support may buffer the initial crisis, prolonged income loss due to treatment-induced disability exhausts these resources over the 1- to 5-year window, critically undermining a household’s economic resilience. Furthermore, the high risk of disease recurrence during this period generates a dual psychological and financial strain, where fear of relapse is inextricably linked with anticipatory anxiety over the catastrophic costs of subsequent-line therapies [ 61 ] . This nexus of sustained treatment costs, depleted financial buffers, and recurrence-related distress encapsulates the core dimensions of financial toxicity that converge to disproportionately burden patients in this pivotal survivorship phase. Our study found that compared to patients with stage IV disease, those diagnosed at stage II or III were more likely to belong to the mild financial toxicity profile rather than the moderate profile. This observation aligns with evidence suggesting that advanced disease stages are generally associated with heavier financial burden [ 26 ] . The increased likelihood of moderate or severe financial toxicity in stage IV patients may be explained by several clinical and psychological factors. Stage IV disease often indicates distant metastasis, which typically requires more aggressive and prolonged treatment regimens, including extensive cytoreductive surgery—frequently involving multi-organ resection—and the integration of costly targeted therapies or prolonged maintenance treatment with novel agents [ 62 ] . These complex interventions are associated with longer hospital stays, higher rates of complications, and significantly elevated direct medical costs. Beyond these direct costs, an advanced-stage diagnosis itself constitutes a profound psychological stressor [ 63 ] . The awareness of a high risk of recurrence creates anticipatory financial anxiety, as patients confront the prospect of successive, potentially more expensive lines of therapy (e.g., second- or third-line chemotherapy or secondary surgery). This "fear of future financial crisis" is a core, subjective dimension of financial toxicity, compounding the objective economic strain from treatment. Out-of-pocket expenditure on externally procured medications represents a pivotal and distinct factor exacerbating financial toxicity, a finding consistent with the work of Xu et al. [ 64 ] . This effect operates through a well-defined mechanism. According to the World Health Organization, a household experiences catastrophic health expenditure when its out-of-pocket health spending exceeds 40% of its capacity to pay (disposable income after basic subsistence) or 10% of its total consumption, a threshold that forces families to curtail essential consumption, sell assets, or incur debt. Externally procured drugs—typically those excluded from the national reimbursement drug list or requiring out-of-hospital, self-paid purchases—constitute a direct, non-reimbursable cash cost for patients. Crucially, these expenses are frequently not counted toward the deductible or the annual out-of-pocket ceiling of basic medical insurance schemes. Consequently, a higher proportion of total out-of-pocket spending attributed to such drugs reflects a lower effective coverage rate from the insurance system, subjects patients to a more immediate and severe financial shock, and substantially elevates the risk of triggering catastrophic expenditure. Furthermore, this acute, unbuffered financial pressure directly induces severe cost-related nonadherence, manifesting as dose reduction, treatment interruption, or forgone necessary follow-up care to alleviate economic burden. This behavior not only compromises immediate treatment efficacy and survival but also potentiates greater long-term healthcare costs due to disease progression, thereby cementing a vicious cycle of “financial hardship → suboptimal treatment → worsened prognosis → intensified financial burden.” [ 65 ] Therefore, spending on externally procured medications is not merely an indicator of financial toxicity but a central driver of its self-perpetuating cycle. In this study, patients in the severe financial toxicity group demonstrated significantly higher scores on the resignation subscale compared to the mild financial toxicity group, a finding consistent with prior research [ 66 ] . This association may be mechanistically explained by a characteristic dual pattern of behavioral avoidance. Individuals adopting a resignation coping style typically exhibit pessimism and a lack of confidence in treatment efficacy and physical recovery, which often leads to a reluctance to engage in shared medical decision-making and proactive financial planning. Concurrently, they tend to refuse essential social support, reducing profound communication with family, friends, and the healthcare team due to feelings of shame or an unwillingness to be perceived as a burden. This two-fold behavioral avoidance results in a dual deprivation of critical resources. The rupture of their social support network fosters isolation, thereby further undermining their psychological resilience in confronting stress. Consequently, it is imperative for healthcare providers to vigilantly monitor the coping strategies of ovarian cancer patients during clinical care, with focused attention on those prone to resignation and associated social avoidance. Timely psychological intervention, provision of structured training to enhance coping competencies when necessary, and encouraging engagement with peers who demonstrate proactive coping are recommended to steer patients toward more adaptive strategies for accepting alterations in their physical function. Our study revealed that patients who actively confront their illness are more likely to fall into the mild rather than the moderate financial toxicity group, a finding consistent with the work of Chen et al. [ 67 ] . This association can be attributed to the multifaceted benefits of a proactive coping style. Such patients demonstrate a greater capacity to acknowledge and adapt to disease-induced alterations in bodily appearance and function. They actively mobilize support networks—including family, friends, healthcare providers, and peer groups—to secure informal financial, informational, and emotional resources [ 68 ] . This robust support system aids in sustaining a positive psychological state, alleviating anxiety, and mitigating overall distress. Concurrently, through active disease self-management—such as acquiring medical knowledge, comparing treatment options, and engaging in financial navigation (e.g., applying for subsidies or liaising with insurance agencies)—they can optimize treatment-related expenditures and reduce unnecessary out-of-pocket costs. Furthermore, their enhanced adaptability correlates with better treatment adherence, which helps maintain or improve physical health. This favorable biopsychosocial status may subsequently reduce the risk of additional healthcare costs stemming from psychological complications or poor clinical management. Consequently, bolstering social support for vulnerable populations—through mechanisms such as living allowances, subsidized healthcare, or charitable donations—is imperative. Mobilizing multi-layered societal resources to provide tangible, informational, and emotional aid can help patients tangibly experience societal care, thereby mitigating the systemic drivers of financial toxicity. Conclusions In this study, financial toxicity among ovarian cancer patients was categorized into three levels: mild, moderate, and severe. The research emphasizes that intervention strategies should be patient-centered and individually tailored based on the distinct characteristics of each category, including demographic profiles, disease-related information, and economic burdens. Specifically, patients who are unemployed, covered by urban resident basic medical insurance, supporting more than one elderly family member, diagnosed within 1–5 years, at stage IV of the disease, with comorbidities, having out-of-pocket medication expenses exceeding 50,000RMB, or adopting a resigned coping style toward their illness should be prioritized for interventions aimed at alleviating financial toxicity. These findings are significant for implementing targeted measures to improve financial well-being in this patient population. limitations This study has several limitations. First, the cross-sectional design only reflects the current status of financial toxicity among ovarian cancer patients. Financial toxicity is a dynamic process that persists throughout the entire treatment journey. Our research team is currently planning a longitudinal study on the financial toxicity of ovarian cancer patients to assess its changes over time and the dynamic evolution of influencing factors, aiming to provide a scientific basis for developing effective interventions and policies. Second, the study was conducted at a single tertiary cancer hospital in Shandong Province, and although it included a small number of patients from other provinces, its generalizability remains limited. Future research should adopt a multi-center, stratified random sampling approach to include ovarian cancer patients from various regions across the country. Third, while this study presented detailed statistical data and charts to illustrate the characteristics of patients in different latent profiles of financial toxicity, further investigation into the influencing factors of these latent profiles is needed. Future studies should incorporate qualitative methods such as in-depth interviews or focus group discussions to gain a more comprehensive understanding of the factors influencing different latent profiles of financial toxicity, thereby providing a scientific basis for developing targeted interventions. Abbreviations aBIC Adjusted Bayesian Information Criteria AIC Akaike Information Criterion BIC Bayesian Information Criteria BLRT Bootstrap Likelihood Ratio Test LMRT Lo–Mendell–Rubin Test Log(L) Log-likelihood value OR Odds Ratio Declarations Acknowledgments We would like to express our gratitude to all the participants in the department of ovarian tumor ward, who voluntarily participated and provided sincere responses. Author contributions Sun F was responsible for the writing of the original draft and data analysis. Wang Q was responsible for the conceptual design, data analysis, obtaining funds, and strictly revised the manuscript. Zhang Y was responsible for the conceptual design, method design, and editing of the manuscript. Meng Y was responsible for the project management, supervision, and obtaining funds. Funding This study was funded by the Chronic Disease Management Research Project of National Health Commission Capacity Building and Continuing Education Center (GWJJMB202510022147), Collaborative Academic Innovation Project of Shandong Cancer Hospital(No.FC010) and Research and Practice on the Innovation of Moral Education Model for Medical Students during Their Internship Period under the Context of the Comprehensive Ideological and Political Education(XM2024123). Data availability The data that support the results of this study are available on request from the corresponding author, researcher Yingtao Meng, upon reasonable request. Ethics approval and consent to participate This study has been successfully approved by the Ethics Committee of Shandong First Medical University Affiliated Tumor Hospital (Approval Number: 202508030). All research procedures strictly followed the ethical guidelines of the Helsinki Declaration, ensuring the informed consent, voluntariness, absence of harm, and privacy protection rights of the participants. Consent for publication Not applicable. Competing interests The authors declare no competing interests. Author details Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440, Jizuan Road, Jinan, Shandong, China. References Gaona-Luviano, P., Medina-Gaona, L. A., & Magaña-Pérez, K. (2020). Epidemiology of ovarian cancer. Chinese clinical oncology , 9 (4), 47. Bray, F., Laversanne, M., Sung, H., Ferlay, J., Siegel, R. L., Soerjomataram, I., et al. (2024). 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Jing J, Feng R, Zhang X, Li M, Gao J (2020) Financial toxicity and its associated patient and cancer factors among women with breast cancer: a single-center analysis of low-middle income region in China. Breast Cancer Res Treat 181(2):435–443 Xu, B., So, W. K. W., Choi, K. C., Huang, Y., Liu, M., Qiu, L., et al. (2024). Disparities in cancer-related financial toxicity across economically diverse provinces in China: A multi-center cross-sectional study. Asia-Pacific journal of oncology nursing , 12 , 100636. Smith, J., Yu, J., Gordon, L. G., & Chilkuri, M. (2023). Financial Toxicity and Out-of-Pocket Costs for Patients with Head and Neck Cancer. Current oncology (Toronto, Ont.) , 30 (5), 4922–4935. Smith, G. L., Banegas, M. P., Acquati, C., Chang, S., Chino, F., Conti, R. M., et al. (2022). Navigating financial toxicity in patients with cancer: A multidisciplinary management approach. CA: a cancer journal for clinicians , 72(5), 437–453. Chen, C., Cao, J., Wang, L., Zhang, R., Li, H., & Peng, J. (2020). Body image and its associated factors among Chinese head and neck cancer patients undergoing surgical treatment: a cross-sectional survey. Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer , 28(3), 1233–1239. Luo, Q., Chen, X., Liu, L., Peng, J., & Tang, F. (2025). Financial toxicity-related factors in patients with nasopharyngeal carfcinoma: a cross-sectional study. Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer , 33 (3), 201. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8660541","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":598924319,"identity":"8b610dc4-a809-4bdd-ac5f-2c35da46e40e","order_by":0,"name":"Fengye Sun","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Fengye","middleName":"","lastName":"Sun","suffix":""},{"id":598924320,"identity":"4cc21677-7821-4168-89f9-ff9018230cb7","order_by":1,"name":"Qian Wang","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Qian","middleName":"","lastName":"Wang","suffix":""},{"id":598924321,"identity":"5636ca8d-4bc2-4540-b6bb-c56eff2e1f19","order_by":2,"name":"Yaru Zhang","email":"","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences","correspondingAuthor":false,"prefix":"","firstName":"Yaru","middleName":"","lastName":"Zhang","suffix":""},{"id":598924322,"identity":"89563e5c-88e9-4e4a-953f-1b330f9c3b37","order_by":3,"name":"Yingtao Meng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/UlEQVRIie3QMWrDMBSAYZsHml7wGpWSGxRUBC6lprmKREGTD5BRxqWZsqfQc5SOMh66iHgNZKhDx2awN2+tMnao4rEQfYMQ4v0IKYqC4P/KMIG4aMXCbRI9phBqRpdQs9aqS7o2o5Kas4Youn+sM6aFf/hquaq/JgNIXSNnUjfIIhN3ff53ktqNukNBZFHidSvfdngDGujzqyfZ5ilHgbKE4y12h7faEJj4ko/DMZnKJ8DUrRtkRpxItsg/UTCOQJRLzIjE5mn8osRsCu6ThX1Auq5K/1veLe8O2TfOm6rYD4v7eZKUVdd7Eodc4O+DWHvnHeiHUyNBEATn7QcOcFXnVPBhogAAAABJRU5ErkJggg==","orcid":"","institution":"Shandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Yingtao","middleName":"","lastName":"Meng","suffix":""}],"badges":[],"createdAt":"2026-01-21 13:51:12","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8660541/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8660541/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104180649,"identity":"35367ada-a214-429c-9339-d0196d561286","added_by":"auto","created_at":"2026-03-08 17:23:00","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":59868,"visible":true,"origin":"","legend":"\u003cp\u003ePotential profile characteristics of FT in Ovarian cancer patients.\u003c/p\u003e\n\u003cp\u003eC1: Severe Financial Toxicity Profile (27.2%); C2: Moderate Financial Toxicity Profile (50.9%); C3: Mild Financial Toxicity Profile (21.9%).\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8660541/v1/33fae1989428a53e6986faee.png"},{"id":104404009,"identity":"b0a54591-8c19-48ed-9b3b-5278c4cd0190","added_by":"auto","created_at":"2026-03-11 12:19:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2273826,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8660541/v1/2aec9073-802d-4e47-b239-13f8d4189580.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Financial toxicity profiles and influencing factors among ovarian cancer Patients: a latent profile analysis","fulltext":[{"header":"Background","content":"\u003cp\u003eOvarian cancer is one of the most common malignancies of the female reproductive system, posing a serious threat to women's health\u003csup\u003e[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/sup\u003e. In 2022 alone, an estimated 324,400 new cases were diagnosed worldwide, resulting in approximately 206,800 deaths \u003csup\u003e[\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]\u003c/sup\u003e. China contributed substantially to this burden, with about 61,100 new cases and 32,600 deaths annually, representing a significant proportion of global ovarian cancer mortality \u003csup\u003e[\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e. Of particular concern is the rising global burden over the past decade, with the incidence of ovarian cancer having increased at an average annual rate of 3.2% and mortality by 1.8%, maintaining the highest case-fatality rate among gynecological malignancies \u003csup\u003e[\u003cspan additionalcitationids=\"CR5\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRecent advancements in anti-cancer therapeutics have led to the continuous evolution of treatment modalities for ovarian cancer, encompassing surgery, chemotherapy, targeted therapy, and other multimodal approaches, which have significantly improved patient survival\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]\u003c/sup\u003e. However, these innovative treatments are associated with high costs, imposing a substantial economic burden on patients\u003csup\u003e[\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. A global study synthesizing data from 204 countries revealed that the socioeconomic burden of ovarian cancer accounts for approximately 0.1% of the global Gross Domestic Product (GDP)\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]\u003c/sup\u003e. Consistent with this global perspective, research\u003csup\u003e[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e from China indicates that households with cancer patients are more likely to experience excessive healthcare expenditure, with 77% of cancer patients perceiving the financial burden as catastrophic.\u003c/p\u003e \u003cp\u003eThe concept of \"financial toxicity\" was first introduced by Bullock\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]\u003c/sup\u003e in 2013 and later elaborated by Zafar\u003csup\u003e[\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e to describe the financial hardship and resultant physical and psychological distress experienced by cancer patients due to medical costs. With advances in cancer treatment, financial toxicity has become increasingly prevalent among cancer survivors\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]\u003c/sup\u003e. It is estimated that 35% to 58% of gynecological cancer survivors experience financial toxicity\u003csup\u003e[\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]\u003c/sup\u003e. Notably, ovarian cancer has been identified as the most costly to treat among gynecological cancers, and its survivors are consequently at the highest risk for severe financial toxicity\u003csup\u003e[\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThe adverse effects of financial toxicity extend beyond financial distress to encompass a multidimensional burden that detrimentally impacts treatment adherence, psychological well-being, and overall quality of life. For patients with ovarian cancer, the high costs associated with novel therapeutic agents, such as PARP inhibitors and anti-angiogenic drugs, can lead to catastrophic health expenditures\u003csup\u003e[\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]\u003c/sup\u003e. This severe financial toxicity directly compromises treatment adherence, resulting in the delay, skipping, or outright abandonment of recommended therapies, which may ultimately contribute to suboptimal clinical outcomes and reduced survival rates\u003csup\u003e[\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]\u003c/sup\u003e. Concurrently, persistent concerns over medical debt and financial insecurity significantly exacerbate levels of depression, anxiety, and diminished health-related quality of life\u003csup\u003e[\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e]\u003c/sup\u003e. Furthermore, this burden often extends to family members, depleting household savings, altering career paths, and exacerbating socioeconomic disparities in access to cancer care and treatment outcomes\u003csup\u003e[\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]\u003c/sup\u003e. Recognizing these profound and interconnected harms underscores the critical necessity of investigating the factors that influence financial toxicity in patients.\u003c/p\u003e \u003cp\u003ePrevious studies have identified a range of factors associated with financial toxicity in cancer patients. These encompass socio-demographic characteristics, such as age\u003csup\u003e[\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e]\u003c/sup\u003e, marital status\u003csup\u003e[\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]\u003c/sup\u003e, educational attainment\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, employment status, monthly per capita income\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e, and type of health insurance\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e. Disease-related factors, including cancer stage, treatment modalities\u003csup\u003e[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e]\u003c/sup\u003e, out-of-pocket expenses\u003csup\u003e[\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]\u003c/sup\u003e, and the presence of comorbidities\u003csup\u003e[\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e]\u003c/sup\u003e, also play a significant role. Furthermore, research indicates that patients' coping strategies in response to their illness can influence their experience of financial toxicity\u003csup\u003e[\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e]\u003c/sup\u003e. Psychosocial factors, particularly perceived social support\u003csup\u003e[\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e]\u003c/sup\u003e and psychological resilience, have been recognized as protective factors against financial toxicity in this population\u003csup\u003e[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eLatent profile analysis (LPA)\u003csup\u003e[\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]\u003c/sup\u003e, a specific type of latent class model, identifies distinct subgroups within a population based on individuals' response patterns across observed indicator variables. This person-centered approach is more effective than traditional variable-centered analyses in uncovering the heterogeneity of financial toxicity manifestations, thereby facilitating the development of more targeted interventions. While prior studies have explored factors influencing financial toxicity in ovarian cancer patients, they have predominantly employed variable-centered methodologies, which may overlook the intrinsic heterogeneity within the patient population. Therefore, this study aims to identify latent categories of financial toxicity among ovarian cancer patients using LPA and to examine the factors associated with membership in each distinct category. The findings are expected to provide an empirical basis for developing personalized intervention strategies to alleviate financial toxicity and ultimately improve the quality of life in this patient group.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA cross-sectional descriptive study was conducted from\u0026nbsp;July to November\u0026nbsp;2025. Using the convenience sampling method, patients with ovarian cancer who were receiving treatment at a tertiary grade A cancer specialty hospital in Shandong Province, Chinese mainland, were selected as the research subjects.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eParticipants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe inclusion criteria were:(1) Diagnosed with ovarian cancer; (2) Age \u0026ge; 18 years; (3) Be cognitively aware of their diagnosis and treatment costs; (4) No mental illness or cognitive impairment; (5) Providing written informed consent voluntarily. Those who have communication difficulties or those whose conditions are too severe to cooperate will be excluded.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAccording to the sample size calculation method of the multi-factor analysis approach, the sample size should be 5 to 10 times the number of research variables\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e34\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e. The research variables include 9 general data variables, 11 clinical-related data variables, 3 dimensions of the\u0026nbsp;\u003cstrong\u003efinancial toxicity\u003c/strong\u003e comprehensive assessment scale, 3 dimensions of disease coping styles scale, 1 dimension of the simplified psychological resilience scale, and 3 dimensions of the social support assessment scale, totaling 30 variables. Considering a 10% inefficiency rate, the sample size was expanded to 334 cases. A total of 350 questionnaires were distributed, among which 342 received valid responses, resulting in an effective recovery rate of 97.71%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral Demographic Data Questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBased on a review of relevant literature, the research team independently developed a questionnaire for collecting general demographic data, which included the patient\u0026apos;s age, marital status, educational level, per-capita monthly income, employment status, type of medical insurance, number of dependent children, number of dependent elders, employment status of adult children.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eClinical Data Questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCombining the available clinical data, the clinical data questionnaire includes: time since diagnosis, disease stage, comorbid chronic conditions, metastasis status, history of surgery, history of chemotherapy, history of radiotherapy, history of targeted therapy, total hospitalization costs, out-of-pocket medication expenses, household disposable savings.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eComprehensive Scores for FT based on Patient‑Reported Outcome Measures (COST‑PROM)\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis scale was developed by De Sousa et al.\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e35\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003efrom the University of Chicago in 2014. It consists of 11 items and uses a Likert 5-point scale, with 0-4, where 0 represents \u0026quot;not at all\u0026quot; and 4 represents \u0026quot;very much\u0026quot;. Items 2, 3, 4, 5, 8, 9, and 10 are reverse-scored. The lower the score, the more severe the\u0026nbsp;\u003cstrong\u003efinancial toxicity\u003c/strong\u003e. The scale has demonstrated good reliability and validity in cancer populations, including breast cancer patients\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e36\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e, supporting its sound psychometric properties. In this study, the Cronbach\u0026apos;s \u0026alpha; was 0.800.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSimplified version of the 10‑item Connor‑Davidson Resilience Scale (CD‑RISC‑ 10)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe simplified version of the Psychological Resilience Scale was derived by Campbell-shills\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e37\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e from the 25-item CD-RISC. The full scale consists of 10 items and is scored on a 5-point Likert scale, where \u0026quot;never like this\u0026quot; is scored as 1, \u0026quot;rarely like this\u0026quot; as 2, \u0026quot;sometimes like this\u0026quot; as 3, \u0026quot;often like this\u0026quot; as 4, and \u0026quot;always like this\u0026quot; as 5. The total score is the sum of the scores of each item, and the higher the total score, the better the psychological resilience. In this study, the Cronbach\u0026apos;s \u0026alpha; coefficient was 0.790.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMedical Coping Modes Questionnaire (MCMQ)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis questionnaire was developed by Feifel et al.\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e38\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e. It is mainly used in cancer and chronic disease patients in China, covering three dimensions: confrontation, avoidance, and resignation, with a total of 20 items. The confrontation dimension includes 8 items, namely items 1, 2, 5, 10, 12, 15, 16, and 19; the avoidance dimension includes 7 items, namely items 3, 7, 8, 9, 11, 14, and 17; and the resignation dimension includes 5 items, namely items 4, 6, 13, 18, and 20. It uses a Likert 4-point rating scale ranging from 0 to 4. Among them, items 1, 4, 9, 10, 12, 13, 18 and 19 are those using the reverse scoring method.The score for each coping event is calculated from low to high as 1, 2, 3, and 4, with a total score ranging from 20 to 80. The higher the score of each dimension, the more likely the patient is to adopt this coping method. This questionnaire has good reliability and validity and has been verified\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e39\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e. In this study, the Cronbach\u0026apos;s \u0026alpha; for the three dimensions were 0.785, 0.718, and 0.786 respectively.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSocial Support Rating Scale (SSRS)\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis scale was compiled and revised by Xiao\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e40\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003eand is used to assess the overall level of an individual\u0026apos;s social support. It consists of 3 dimensions: subjective support, objective support, and the utilization of social support, with a total of 10 items. Items 1-4, 8-10 use the Likert 4-point rating method. Item 5 is scored from \u0026quot;no support\u0026quot; to \u0026quot;complete support\u0026quot; with 1-4 points respectively. Items 6-7 are scored based on the number of sources, with 0 points for \u0026quot;no any source\u0026quot;. The higher the total score, the better the social support level. In this study, the Cronbach\u0026apos;s \u0026alpha; of this scale is 0.751.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData collection\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFirstly, the researchers obtained the research permission from the nursing department and received the informed consent from the head nurse of the ovarian tumor ward. They distributed the questionnaires to eligible ovarian cancer patients through the form of Questionnaire Star and paper questionnaires. Before the formal survey, the researchers received training on ovarian cancer knowledge, familiarized themselves with the common treatment methods and nursing measures for patients, and familiarized themselves with the patient history in the ward in advance to answer patients\u0026apos; questions during the process. During the survey, the researchers explained the purpose, methods, benefits and potential risks of the study to the participants in clear and understandable language, informed the participants of their right to withdraw from the study at any time, obtained the informed consent from the patients and signed the consent form, and then officially began the survey.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe researchers conducted a pre-survey in July 2025, and further improved the questionnaire based on the results of the pre-survey to form the final version of the questionnaire. The questionnaire was filled out by the patients themselves, and when necessary (for example, due to cultural limitations), the researchers would provide assistance. After filling out the questionnaire, it was collected on the spot and carefully reviewed. Missing items were supplemented in a timely manner and invalid questionnaires were eliminated.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data were statistically analyzed using SPSS 22.0 and Mplus 8 software. A difference was considered statistically significant when \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05. Continuous variables that followed a normal distribution were described using the mean \u0026plusmn; standard deviation (\u003cruby\u003ex\u003crp\u003e(\u003c/rp\u003e\n \u003crt\u003e_\u003c/rt\u003e\n \u003crp\u003e)\u003c/rp\u003e\n \u003c/ruby\u003e\u0026plusmn;\u003cem\u003eSD\u003c/em\u003e), while non-normally distributed data were described using the median and interquartile range \u003cem\u003eM\u003c/em\u003e (\u003cem\u003eP\u003c/em\u003e25, \u003cem\u003eP\u003c/em\u003e75). Categorical variables were compared using the chi-square test or Fisher\u0026rsquo;s exact test when more than 20% of cells had an expected count less than 5\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e41\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e. Continuous variables were compared using analysis of variance (ANOVA). To identify key factors associated with subgroup classification, a multinomial\u0026nbsp;logistic regression model was constructed, incorporating sociodemographic, disease-related, economic variables and disease coping style variable as independent predictors. Variable selection for the\u0026nbsp;Multinomial\u0026nbsp;model was based on significant findings from prior univariate analyses (i.e., chi-square test and ANOVA).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics considerations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been successfully approved by the Ethics Committee of Shandong First Medical University Affiliated Tumor Hospital (Approval Number: 202508030). All research procedures strictly followed the ethical guidelines of the Helsinki Declaration, ensuring the informed consent, voluntariness, absence of harm, and privacy protection rights of the participants.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eCommon method bias\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo assess the potential for common method bias (CMB) arising from the self-reported nature of our data, Harman\u0026apos;s single-factor test was conducted. The results of the exploratory factor analysis revealed the presence of 14 distinct factors with eigenvalues greater than 1. The first factor accounted for 27.22% of the variance, which is below the critical threshold of 40%\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e42\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e, indicating that common method bias is not a serious concern in this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDemographic and clinical characteristics of the participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe mean age of the participants was 57.65 years (SD = 10.62). A total of 63.5% of patients had been diagnosed for less than one year, and 96.5% were married. Nearly one-third of the patients had attained a bachelor\u0026rsquo;s degree or higher. Regarding monthly income, 58.8% reported a per-capita income between 3,000 and 4,999 RMB, and 53.5% were retired. In terms of medical insurance, 65.5% were covered by employee basic medical insurance. With respect to family responsibilities, 61.4% of patients were supporting more than one child, while 69.0% were caring for one or fewer elderly individuals. Additionally, 86.3% had children who were already employed. Clinically, 49.4% of patients were at disease stage II or lower. 19.0% of the patients have Comorbid chronic conditions; 10.8% of patients presented with tumor metastasis. Regarding treatment, 74.6% had undergone surgery for ovarian cancer, 77.5% had received chemotherapy, 4.1% had undergone radiotherapy, and 29.5% had received targeted therapy. Financially, 65.2% of patients had total hospitalization costs \u0026le;100,000 RMB, 88.9% reported out-of-pocket medication expenses \u0026le;50,000 RMB, and 80.4% had household disposable savings \u0026le;100,000 RMB. The detailed baseline characteristics of the participants, including age, disease status, and clinical features, are presented in Table 1. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e Patient characteristics and COST values (N= 342)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"554\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eF/X\u003csup\u003e2\u003c/sup\u003e Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (Years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e57.65\u0026plusmn;10.62\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.10\u0026plusmn;7.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.866\u003csup\u003e*\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.732\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.070\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eMarried\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e330(96.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.08\u0026plusmn;7.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e12(3.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.75\u0026plusmn;10.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e4.026\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003ePrimary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e86(25.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14.59\u0026plusmn;7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e84(24.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.08\u0026plusmn;7.91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eHigh school / junior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e54(15.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e19.74\u0026plusmn;9.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003ebachelor\u0026rsquo;s degree or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e118(34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.73\u0026plusmn;6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePer-capita monthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e15.290\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e＜1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e51(14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e12.37\u0026plusmn;6.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1000-2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e42(12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e15.91\u0026plusmn;7.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e3000-4999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e201(58.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.29\u0026plusmn;7.52\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026ge;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e48(14.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e22.34\u0026plusmn;7.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e11.439\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e27(7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e20.26\u0026plusmn;7.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eretired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e183(53.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.38\u0026plusmn;7.48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003efarming\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e132(38.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14.68\u0026plusmn;7.93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of medical insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eUrban and Rural Resident Basic Medical Insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e118(34.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e11.60\u0026plusmn;7.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.669\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.414\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployee Basic Medical Insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e224(65.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e20.00\u0026plusmn;6.66\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dependent children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.132\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.756\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e132(38.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.046\u0026plusmn;7.897\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e220(61.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.505\u0026plusmn;7.835\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dependent \u0026nbsp;elders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e7.000\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e236(69.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.67\u0026plusmn;8.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e106(31.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e15.83\u0026plusmn;6.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status of adult children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e＜0.001\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.984\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNot employed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e47(13.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.40\u0026plusmn;7.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployed\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e295(86.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.05\u0026plusmn;7.92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime since diagnosis\u003c/strong\u003e\u003cstrong\u003e（\u003c/strong\u003e\u003cstrong\u003eyear\u003c/strong\u003e\u003cstrong\u003e）\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e9.184\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e217(63.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.32\u0026plusmn;8.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e87(25.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14.14\u0026plusmn;6.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026ge;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e38(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.90\u0026plusmn;7.77\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e2.532\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.081\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026le;Ⅱ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e169(49.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.07\u0026plusmn;8.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e109(31.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.19\u0026plusmn;8.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eⅥ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e64(18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.09\u0026plusmn;6.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e (continued)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"554\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003eN (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003eF/X\u003csup\u003e2\u003c/sup\u003e Value\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbid chronic conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e9.586\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e277(81.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.42\u0026plusmn;8.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e65(19.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e15.74\u0026plusmn;6.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetastasis status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e3.768\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.053\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e305(89.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.66\u0026plusmn;7.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e37(10.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e12.51\u0026plusmn;6.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.047\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.828\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e87(25.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.92\u0026plusmn;7.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e255(74.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.48\u0026plusmn;7.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of chemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.434\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e77(22.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.33\u0026plusmn;8.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e265(77.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e16.74\u0026plusmn;7.76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of radiotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.048\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e328(95.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.30\u0026plusmn;7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e14(4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e12.36\u0026plusmn;7.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of targeted therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.223\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.627\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e241(70.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.94\u0026plusmn;7.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e101(29.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e15.10\u0026plusmn;7.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal hospitalization costs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.342\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e223(65.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e18.56\u0026plusmn;7.55\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＞\u003c/strong\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e119(34.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14.37\u0026plusmn;7.80\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOut-of-pocket medication expenses\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e0.096\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.757\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e304(88.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e17.85\u0026plusmn;7.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＞\u003c/strong\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e38(11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e11.13\u0026plusmn;7.60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold disposable savings\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e1.594\u003csup\u003e**\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e0.208\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026le;10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e275(80.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e15.70\u0026plusmn;7.54\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e＞\u003c/strong\u003e\u003cstrong\u003e10\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 101px;\"\u003e\n \u003cp\u003e67(19.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e22.87\u0026plusmn;6.57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 93px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 59px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003csup\u003e*\u003c/sup\u003e ANOVA and \u003csup\u003e**\u003c/sup\u003echi-square test\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eIdentification of financial toxicity subgroups\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eUsing the 11 items of the COST-PROM scale as manifest variables, five latent profile analysis models were successively established. Their fit indices are presented in Table 2. As the number of profiles in the models increased, entropy values all exceeded 0.8, while the values for AIC, BIC, and aBIC showed a declining trend. Given that the LMRT\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e43\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e value for Model 3 was 0.007, whereas for Model 4 it was 0.213 (\u0026gt;0.05), Model 3 was deemed to be significantly superior to Model 2 and was considered the most clinically meaningful. Therefore, Model 3 was identified as the optimal and most ideal model. Detailed model fit indices are provided in Table 2.\u003c/p\u003e\n\u003cp\u003eThe characteristics of each latent profile were defined as follows: C1: Severe Financial Toxicity Profile (27.2%); C2: Moderate Financial Toxicity Profile (50.9%); C3: Mild Financial Toxicity Profile (21.9%). Detailed information is illustrated in Figure 1.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e Fit metrics of each model \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"646\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003eModels\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eLog(L)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003eAIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003eBIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eABIC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eEntropy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003eLMRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eBLRT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003eProbability of category\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-6098.229\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e12240.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e12324.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e12255.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-5758.522\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11585.045\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e11715.429\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e11607.573\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.866\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.415/0.585\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-5681.943\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11455.885\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e11632.286\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e11486.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.821\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.0074\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.0079\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.272/0.509/0.219\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-5584.270\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11284.540\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e11506.959\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e11322.970\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.925\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0.2128\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.2186\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.345/0.363/0.143/0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 46px;\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e-5437.090\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 71px;\"\u003e\n \u003cp\u003e11014.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 65px;\"\u003e\n \u003cp\u003e11282.617\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e11060.561\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 48px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 165px;\"\u003e\n \u003cp\u003e0.272/0.175/0.409/0.012/0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eDifferences in financial toxicity among the three latent profiles\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTable 3 presents the individual differences among these three latent profiles. Variables such as per-capita monthly income, employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, metastasis status, history of chemotherapy, radiotherapy, and targeted therapy, total hospitalization costs, out-of-pocket medication expenses, household disposable savings, psychological resilience, confrontation and resignation subscale scores, subjective support, and the utilization of social support showed significant differences across the three subgroups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eRelated factors associated with cancer patients\u0026rsquo; financial toxicity\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe three subgroups of financial toxicity trajectories in ovarian cancer patients were defined as the dependent variable. Independent variables included factors that were statistically significant in prior univariate analyses: per-capita monthly income, employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, metastasis status, history of chemotherapy, radiotherapy, and targeted therapy, total hospitalization costs, out-of-pocket medication expenses, household disposable savings, psychological resilience, confrontation and resignation subscale scores, subjective support, and the utilization of social support.\u003c/p\u003e\n\u003cp\u003eA\u0026nbsp;multinomial\u0026nbsp;logistic regression model was employed for the analysis. All independent variables underwent collinearity diagnostics, with tolerance values greater than 0.1 and variance inflation factors (VIF) below 10\u003cstrong\u003e\u003csup\u003e[\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e44\u003c/sup\u003e\u003c/strong\u003e\u003cstrong\u003e\u003csup\u003e]\u003c/sup\u003e\u003c/strong\u003e, confirming the absence of multicollinearity.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eCompared with Profile 3, patients in Profiles 1 and 2 had a larger number of dependent elderly individuals and a higher likelihood of having chronic comorbidities. Meanwhile, relative to Profile 3, patients in Profile 1 were associated with higher out-of-pocket medication expenses, a higher probability of having a time since diagnosis of 1\u0026ndash;5 years, and a greater tendency to adopt a resignation coping style when facing the disease. In contrast, patients who were retired and those covered by employee medical insurance were more likely to belong to Profile 1. Compared with Profile 3, patients who employed a confrontation coping style and those diagnosed at stage III or earlier were less likely to be classified into Profile 2 but more likely to belong to Profile 3. Details are presented in Table 4.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u003c/strong\u003e Demographic, disease-related characteristics, psychological resilience, coping styles, and social support by latent profiles (N= 342)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"576\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003eC1 (n=93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003eC2(n=174)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003eC3(n=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eF/X\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (Years)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e57.31\u0026plusmn;10.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e57.73\u0026plusmn;10.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e57.90\u0026plusmn;10.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.787\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.854\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.090\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.956\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e92(98.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e168(96.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e72(96.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e3(1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e6(3.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e11.048\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.087\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003ePrimary school and below\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e31(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e44(25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e11(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eMiddle school\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e22(23.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e43(24.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e19(25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eHigh school / junior college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e13(14.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e23(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e18(24.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003ebachelor\u0026rsquo;s degree or higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e27(29.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e64(36.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e27(36.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePer-capita monthly income\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e34.844\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e＜1000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e25(26.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e22(12.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e3(4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e1000-2999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e12(12.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e3000-4999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e51(54.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e110(63.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e41(54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026ge;5000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e5(5.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e21(12.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e22(29.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment Status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e21.461\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e3(3.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e14(8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eretired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e37(39.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e102(58.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e44(58.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003efarming\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e53(57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e58(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e21(28.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of medical insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e124.723\u003csup\u003ec\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eUrban and Rural Resident Basic Medical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e74(81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e31(17.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e11(14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eEmployee Basic Medical Insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e17(18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e143(82.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e64(85.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dependent children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e2.524\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.283\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e31(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e67(38.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e34(45.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e62(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e107(61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e41(54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dependent \u0026nbsp; \u0026nbsp; elders\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e14.486\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e62(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e109(62.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e65(86.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e31(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e65(37.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e10(13.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status of adult children\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.310\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.52\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e16(17.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e22(12.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e9(12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e77(82.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e152(87.36)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e66(88.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime since diagnosis(year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e21.106\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026le;1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e49(52.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e107(61.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e61(81.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e1-5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e36(38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e44(25.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026ge;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e8(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e23(13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e7(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e15.099\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003e\u0026le;Ⅱ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e41(44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e78(44.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e50(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e34(36.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e55(31.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e20(26.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 234px;\"\u003e\n \u003cp\u003eⅥ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 75px;\"\u003e\n \u003cp\u003e18(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 79px;\"\u003e\n \u003cp\u003e41(23.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 76px;\"\u003e\n \u003cp\u003e5(6.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e(continued)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"568\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003eC1 (n=93)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003eC2(n=174)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003eC3(n=75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003eF/X\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbid chronic conditions\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e22.493\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e76(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e127(73.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e74(98.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e17(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e47(27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1(1.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of other surgeries\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e3.220\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.200\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e83(89.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e145(83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e68(90.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e29(16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e7(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eMetastasis status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e73(78.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e159(91.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e73(97.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e17.045\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e20(21.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e15(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e2(2.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of surgery\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e4.994\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.082\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e17(18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e45(25.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e25(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e76(81.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e129(74.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e50(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of chemotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e6.446\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.040\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e18(19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e34(19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e25(33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e75(80.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e140(80.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e50(66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of radiotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e6.930\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.031\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e85(91.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e169(97.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e74(98.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e8(8.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e5(2.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e1(1.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHistory of targeted therapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e8.688\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.013\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e55(59.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e127(73.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e59(78.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e38(40.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e47(27.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e16(21.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal hospitalization costs\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e25.961\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026le;100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e41(44.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e124(71.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e58(77.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e＞100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e52(55.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e50(28.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e17(22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOut-of-pocket medication expenses( yuan)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e27.939\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026le;50,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e69(74.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e164(94.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e71(94.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e＞50,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e24(25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e10(5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e4(5.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHousehold disposable savings( yuan)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e31.127\u003csup\u003eb\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u0026le;100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e89(95.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e140(80.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e46(61.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e＞100,000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4(4.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e34(19.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e29(38.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003epsychological resilience\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e22.043\u0026plusmn;7.791\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e27.39\u0026plusmn;7.65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e32.63\u0026plusmn;5.81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e5.707\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003econfrontation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e14.398\u0026plusmn;2.542\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e17.71\u0026plusmn;5.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e22.85\u0026plusmn;4.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e11.984\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eresignation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e16.473\u0026plusmn;2.636\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e12.40\u0026plusmn;4.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e8.63\u0026plusmn;3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e20.151\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eavoidance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e20.376\u0026plusmn;3.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e20.01\u0026plusmn;3.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e19.81\u0026plusmn;3.19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1.249\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSocial support\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e13.451\u0026plusmn;15.953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e34.71\u0026plusmn;6.25\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e34.00\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1.608\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003esubjective support,\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e18.989\u0026plusmn;4.187\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e20.61\u0026plusmn;3.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e22.67\u0026plusmn;3.71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e9.704\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003eobjective support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3.054\u0026plusmn;3.595\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e7.85\u0026plusmn;2.38\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e8.00\u0026plusmn;0.00\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e1.020\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e0.402\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 226px;\"\u003e\n \u003cp\u003eThe utilization of social support\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.688\u0026plusmn;1.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 81px;\"\u003e\n \u003cp\u003e7.09\u0026plusmn;1.90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 67px;\"\u003e\n \u003cp\u003e8.85\u0026plusmn;2.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 53px;\"\u003e\n \u003cp\u003e21.440\u003csup\u003ea\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 54px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: \u003csup\u003ea\u003c/sup\u003eOne-way analysis of variance. \u003csup\u003eb\u003c/sup\u003ePearson chi-squared test. \u003csup\u003ec\u003c/sup\u003eFisher\u0026rsquo;s exact test.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTable 4 Multinomial logistic regression analysis of latent profiles in Ovarian cancer patients (N= 342)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"637\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003eB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003eOR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"13\" valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC1 vs C3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment Status (reference: farming)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eretired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-2.840\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.275\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.058\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.005-0.710\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eType of medical insurance(reference: Urban and Rural Resident Basic Medical Insurance)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eEmployee Basic Medical Insurance \u0026nbsp; \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-3.384\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.692\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.034\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.009-0.132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dependent elders(reference:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026le;\u003c/strong\u003e\u003cstrong\u003e1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.645\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.668\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e5.180\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.014\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.399-19.177\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime since diagnosis(reference:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e＞\u003c/strong\u003e\u003cstrong\u003e5year)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e1-5year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e2.772\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.026\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e15.993\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.007\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.140-119.536\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbid chronic conditions(reference: No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e3.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e26.544\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.009\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.267-310.826\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOut-of-pocket medication expenses(reference:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026le;\u003c/strong\u003e\u003cstrong\u003e5)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e＞5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e2.874\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e17.708\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.944-161.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eresignation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.127\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.457\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.136-1.870\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"8\" valign=\"top\" style=\"width: 41px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eC2 vs C3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of dependent elders(reference:\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026le;\u003c/strong\u003e\u003cstrong\u003e1)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e＞1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e1.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.497\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e4.609\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1.741-12.202\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDisease stage(reference: Ⅵ) \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u0026le;Ⅱ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-1.493\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.615\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.225\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.067-0.750\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eⅢ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-1.338\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.664\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.262\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.071-0.965\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbid chronic conditions(reference: No)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e3.569\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e1.144\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e35.479\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3.766-334.210\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 280px;\"\u003e\n \u003cp\u003e\u003cstrong\u003econfrontation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 56px;\"\u003e\n \u003cp\u003e-0.161\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.054\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 55px;\"\u003e\n \u003cp\u003e0.851\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e0.766-0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eNote: C1: Severe Financial Toxicity Profile; C2: Moderate Financial Toxicity Profile ; C3: Mild Financial Toxicity Profile.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eTo our knowledge, this study is the first to apply latent profile analysis to identify distinct profiles of financial toxicity and their associated factors among ovarian cancer patients. The analysis revealed three distinct financial toxicity profiles: C1 (severe financial toxicity), C2 (moderate financial toxicity), and C3 (mild financial toxicity). Factors found to be associated with profile membership included employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, out‑of‑pocket medication expenses, and the confrontation and resignation coping styles. These findings offer a novel perspective by recognizing the heterogeneity within the ovarian cancer population rather than treating them as a homogeneous group. They provide an evidence‑based foundation for developing tailored interventions aimed at mitigating financial toxicity based on the identified influencing factors. Furthermore, this study contributes to a deeper understanding of financial toxicity among ovarian cancer patients within the unique socioeconomic context of China.\u003c/p\u003e \u003cp\u003eThis study revealed that the average financial toxicity score among ovarian cancer patients was approximately 17.10\u0026thinsp;\u0026plusmn;\u0026thinsp;7.88. Notably, 78.1% of patients self-reported moderate to severe financial toxicity, with 27.2% experiencing severe financial toxicity. These findings are consistent with broader research on cancer-related financial toxicity\u003csup\u003e[\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e]\u003c/sup\u003e, which indicates that nearly one-quarter of patients report a severe financial burden. They also align with the results reported by Vasquez-Trespalacios et al.\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e regarding financial toxicity in advanced ovarian cancer patients. The study by Bouberhan et al.\u003csup\u003e[\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]\u003c/sup\u003e showed that 31% of ovarian cancer patients experienced severe financial toxicity, a proportion slightly higher than that found in our study. This discrepancy may be attributed to their use of a higher cutoff score (23 points) to identify high financial toxicity, which effectively lowers the threshold for defining severe financial toxicity. In contrast, Smith et al.\u003csup\u003e[\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]\u003c/sup\u003e reported that 44% of gynecologic cancer patients had financial toxicity. This difference is likely because ovarian cancer patients constituted only 21% of their sample, which included patients with various gynecologic malignancies. Thus, our findings provide valuable data on the prevalence and severity of financial toxicity specifically among ovarian cancer patients in China. More importantly, by employing Latent profile analysis rather than relying on simple COST-PROM score thresholds, our study offers a more nuanced, person-centered understanding of the heterogeneity in financial burden within this population.\u003c/p\u003e \u003cp\u003eThis study identified caring for more than one elderly dependent as a significant predictor of heightened financial toxicity in ovarian cancer patients, with a higher prevalence in moderate/severe financial toxicity groups. This association can be largely attributed to the traditional norm of filial piety in Chinese society, which reinforces families\u0026rsquo; primary responsibility for elders\u0026rsquo; financial and care needs\u003csup\u003e[\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e]\u003c/sup\u003e. When combined with the sustained, high costs of ovarian cancer treatment, multi-elder care creates a compounded financial burden that rapidly depletes household resources, reduces economic resilience, and intensifies perceived financial stress. This finding aligns with evidence linking increased family caregiving burdens to worse financial toxicity outcomes in cancer populations, particularly where formal support systems are limited\u003csup\u003e[\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study identified the presence of chronic comorbidities as a significant predictor of heightened financial toxicity in ovarian cancer patients, with a higher prevalence in moderate/severe financial toxicity groups. This association can be explained through multiple intertwined pathways. First, comorbidities directly exacerbate the economic burden by introducing sustained, overlapping costs for concurrent cancer treatment and chronic disease management (e.g., medications, monitoring)\u003csup\u003e[\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e, \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]\u003c/sup\u003e. Second, they increase treatment complexity, potentially influencing oncology care plans (e.g., adjusted chemotherapy, prolonged hospitalization), thereby elevating total direct medical expenditures\u003csup\u003e[\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e]\u003c/sup\u003e. This finding aligns with established evidence recognizing comorbidities as a key risk factor for catastrophic health expenditures in cancer populations and is consistent with observations that ovarian cancer patients with severe financial toxicity often face more complex health and social needs\u003csup\u003e[\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e]\u003c/sup\u003e. Consequently, integrated care models that address both cancer and chronic conditions, coupled with proactive financial navigation, are essential to mitigate this multifaceted burden.\u003c/p\u003e \u003cp\u003eOur study identifies retirement status as a significant protective factor against severe financial toxicity in ovarian cancer patients, with retirees demonstrating a higher propensity for mild financial toxicity profiles\u0026mdash;a finding consistent with the observations of Zhang et al.\u003csup\u003e[\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]\u003c/sup\u003e. The underlying mechanisms can be attributed to retirees' stable pension or savings-derived fixed income, which, being independent of work capacity, remains uninterrupted by treatment-related sick leave or disability, thereby providing a fundamental \"financial ballast\" for long-term care, coupled with their predominant urban residence that ensures proximate access to tertiary hospitals with specialized oncology units, significantly reducing the indirect costs and time burdens associated with long-distance travel, accommodation, and family caregiving for standardized treatment\u003csup\u003e[\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]\u003c/sup\u003e. This stands in stark contrast to patients engaged in farming, who typically reside in rural areas, rely on physically demanding labor with inherent income unpredictability and vulnerability, and face immediate severe impairment of their core earning capacity upon diagnosis; moreover, the substantial hidden financial toxicity arising from non-medical expenses such as travel, lodging, and family lost wages during necessary trips to urban medical centers further exacerbates their financial burden\u003csup\u003e[\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e]\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study reveals that ovarian cancer patients enrolled in urban employee basic medical insurance experience significantly lower financial toxicity compared to those covered by urban and rural resident basic medical insurance, a finding consistent with research by Yusuf, et al.\u003csup\u003e[\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]\u003c/sup\u003e This disparity is rooted in the inherent structural inequities within China's multi-tiered health insurance system. The urban employee insurance typically offers higher reimbursement rates and higher annual payment caps, more effectively covering hospitalization and treatments within the national reimbursement drug list, thereby directly buffering patients' out-of-pocket expenses. In contrast, the urban and rural resident insurance, adhering to the principle of \"broad coverage with basic benefits,\" features lower reimbursement rates and caps, resulting in patients bearing a substantially larger share of medical costs. Despite the near-universal coverage of basic insurance in China, design elements such as formulary restrictions, deductibles, and co-payment rates maintain high levels of personal cash expenditure\u003csup\u003e[\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]\u003c/sup\u003e. This burden is disproportionately amplified for the resident insurance population, whose coverage is inherently weaker. Furthermore, the low penetration of supplementary protections like commercial health insurance fails to adequately bridge the coverage gaps in the basic schemes, further exacerbating the financial vulnerability of patients reliant on resident insurance\u003csup\u003e[\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e]\u003c/sup\u003e. Consequently, the disparity in financial toxicity is not merely a reflection of individual financial capacity but a direct manifestation of the unequal \"depth of coverage\" conferred by different insurance institutions during a personal health crisis.\u003c/p\u003e \u003cp\u003eOur study identified that patients diagnosed with ovarian cancer within 1 to 5 years were significantly more likely to experience severe, rather than mild financial toxicity, a finding that underscores the protracted economic vulnerability inherent to this disease\u0026rsquo;s chronic and recurrent trajectory. As highlighted in a JAMA review\u003csup\u003e[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e]\u003c/sup\u003e, the standard of care following initial intensive therapy often entails years of maintenance treatment, leading to the relentless accrual of out-of-pocket expenses. This is compounded by the progressive erosion of financial reserves: while savings or short-term support may buffer the initial crisis, prolonged income loss due to treatment-induced disability exhausts these resources over the 1- to 5-year window, critically undermining a household\u0026rsquo;s economic resilience. Furthermore, the high risk of disease recurrence during this period generates a dual psychological and financial strain, where fear of relapse is inextricably linked with anticipatory anxiety over the catastrophic costs of subsequent-line therapies\u003csup\u003e[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e]\u003c/sup\u003e. This nexus of sustained treatment costs, depleted financial buffers, and recurrence-related distress encapsulates the core dimensions of financial toxicity that converge to disproportionately burden patients in this pivotal survivorship phase.\u003c/p\u003e \u003cp\u003eOur study found that compared to patients with stage IV disease, those diagnosed at stage II or III were more likely to belong to the mild financial toxicity profile rather than the moderate profile. This observation aligns with evidence suggesting that advanced disease stages are generally associated with heavier financial burden\u003csup\u003e[\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e]\u003c/sup\u003e. The increased likelihood of moderate or severe financial toxicity in stage IV patients may be explained by several clinical and psychological factors. Stage IV disease often indicates distant metastasis, which typically requires more aggressive and prolonged treatment regimens, including extensive cytoreductive surgery\u0026mdash;frequently involving multi-organ resection\u0026mdash;and the integration of costly targeted therapies or prolonged maintenance treatment with novel agents\u003csup\u003e[\u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e62\u003c/span\u003e]\u003c/sup\u003e. These complex interventions are associated with longer hospital stays, higher rates of complications, and significantly elevated direct medical costs. Beyond these direct costs, an advanced-stage diagnosis itself constitutes a profound psychological stressor\u003csup\u003e[\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e]\u003c/sup\u003e. The awareness of a high risk of recurrence creates anticipatory financial anxiety, as patients confront the prospect of successive, potentially more expensive lines of therapy (e.g., second- or third-line chemotherapy or secondary surgery). This \"fear of future financial crisis\" is a core, subjective dimension of financial toxicity, compounding the objective economic strain from treatment.\u003c/p\u003e \u003cp\u003eOut-of-pocket expenditure on externally procured medications represents a pivotal and distinct factor exacerbating financial toxicity, a finding consistent with the work of Xu et al.\u003csup\u003e[\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e]\u003c/sup\u003e. This effect operates through a well-defined mechanism. According to the World Health Organization, a household experiences catastrophic health expenditure when its out-of-pocket health spending exceeds 40% of its capacity to pay (disposable income after basic subsistence) or 10% of its total consumption, a threshold that forces families to curtail essential consumption, sell assets, or incur debt. Externally procured drugs\u0026mdash;typically those excluded from the national reimbursement drug list or requiring out-of-hospital, self-paid purchases\u0026mdash;constitute a direct, non-reimbursable cash cost for patients. Crucially, these expenses are frequently not counted toward the deductible or the annual out-of-pocket ceiling of basic medical insurance schemes. Consequently, a higher proportion of total out-of-pocket spending attributed to such drugs reflects a lower effective coverage rate from the insurance system, subjects patients to a more immediate and severe financial shock, and substantially elevates the risk of triggering catastrophic expenditure. Furthermore, this acute, unbuffered financial pressure directly induces severe cost-related nonadherence, manifesting as dose reduction, treatment interruption, or forgone necessary follow-up care to alleviate economic burden. This behavior not only compromises immediate treatment efficacy and survival but also potentiates greater long-term healthcare costs due to disease progression, thereby cementing a vicious cycle of \u0026ldquo;financial hardship \u0026rarr; suboptimal treatment \u0026rarr; worsened prognosis \u0026rarr; intensified financial burden.\u0026rdquo;\u003csup\u003e[\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e]\u003c/sup\u003e Therefore, spending on externally procured medications is not merely an indicator of financial toxicity but a central driver of its self-perpetuating cycle.\u003c/p\u003e \u003cp\u003eIn this study, patients in the severe financial toxicity group demonstrated significantly higher scores on the resignation subscale compared to the mild financial toxicity group, a finding consistent with prior research\u003csup\u003e[\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e]\u003c/sup\u003e. This association may be mechanistically explained by a characteristic dual pattern of behavioral avoidance. Individuals adopting a resignation coping style typically exhibit pessimism and a lack of confidence in treatment efficacy and physical recovery, which often leads to a reluctance to engage in shared medical decision-making and proactive financial planning. Concurrently, they tend to refuse essential social support, reducing profound communication with family, friends, and the healthcare team due to feelings of shame or an unwillingness to be perceived as a burden. This two-fold behavioral avoidance results in a dual deprivation of critical resources. The rupture of their social support network fosters isolation, thereby further undermining their psychological resilience in confronting stress. Consequently, it is imperative for healthcare providers to vigilantly monitor the coping strategies of ovarian cancer patients during clinical care, with focused attention on those prone to resignation and associated social avoidance. Timely psychological intervention, provision of structured training to enhance coping competencies when necessary, and encouraging engagement with peers who demonstrate proactive coping are recommended to steer patients toward more adaptive strategies for accepting alterations in their physical function.\u003c/p\u003e \u003cp\u003eOur study revealed that patients who actively confront their illness are more likely to fall into the mild rather than the moderate financial toxicity group, a finding consistent with the work of Chen et al.\u003csup\u003e[\u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e67\u003c/span\u003e]\u003c/sup\u003e. This association can be attributed to the multifaceted benefits of a proactive coping style. Such patients demonstrate a greater capacity to acknowledge and adapt to disease-induced alterations in bodily appearance and function. They actively mobilize support networks\u0026mdash;including family, friends, healthcare providers, and peer groups\u0026mdash;to secure informal financial, informational, and emotional resources\u003csup\u003e[\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e]\u003c/sup\u003e. This robust support system aids in sustaining a positive psychological state, alleviating anxiety, and mitigating overall distress. Concurrently, through active disease self-management\u0026mdash;such as acquiring medical knowledge, comparing treatment options, and engaging in financial navigation (e.g., applying for subsidies or liaising with insurance agencies)\u0026mdash;they can optimize treatment-related expenditures and reduce unnecessary out-of-pocket costs. Furthermore, their enhanced adaptability correlates with better treatment adherence, which helps maintain or improve physical health. This favorable biopsychosocial status may subsequently reduce the risk of additional healthcare costs stemming from psychological complications or poor clinical management. Consequently, bolstering social support for vulnerable populations\u0026mdash;through mechanisms such as living allowances, subsidized healthcare, or charitable donations\u0026mdash;is imperative. Mobilizing multi-layered societal resources to provide tangible, informational, and emotional aid can help patients tangibly experience societal care, thereby mitigating the systemic drivers of financial toxicity.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eIn this study, financial toxicity among ovarian cancer patients was categorized into three levels: mild, moderate, and severe. The research emphasizes that intervention strategies should be patient-centered and individually tailored based on the distinct characteristics of each category, including demographic profiles, disease-related information, and economic burdens. Specifically, patients who are unemployed, covered by urban resident basic medical insurance, supporting more than one elderly family member, diagnosed within 1\u0026ndash;5 years, at stage IV of the disease, with comorbidities, having out-of-pocket medication expenses exceeding 50,000RMB, or adopting a resigned coping style toward their illness should be prioritized for interventions aimed at alleviating financial toxicity. These findings are significant for implementing targeted measures to improve financial well-being in this patient population.\u003c/p\u003e \u003cdiv id=\"Sec24\" class=\"Section2\"\u003e \u003ch2\u003elimitations\u003c/h2\u003e \u003cp\u003eThis study has several limitations. First, the cross-sectional design only reflects the current status of financial toxicity among ovarian cancer patients. Financial toxicity is a dynamic process that persists throughout the entire treatment journey. Our research team is currently planning a longitudinal study on the financial toxicity of ovarian cancer patients to assess its changes over time and the dynamic evolution of influencing factors, aiming to provide a scientific basis for developing effective interventions and policies. Second, the study was conducted at a single tertiary cancer hospital in Shandong Province, and although it included a small number of patients from other provinces, its generalizability remains limited. Future research should adopt a multi-center, stratified random sampling approach to include ovarian cancer patients from various regions across the country. Third, while this study presented detailed statistical data and charts to illustrate the characteristics of patients in different latent profiles of financial toxicity, further investigation into the influencing factors of these latent profiles is needed. Future studies should incorporate qualitative methods such as in-depth interviews or focus group discussions to gain a more comprehensive understanding of the factors influencing different latent profiles of financial toxicity, thereby providing a scientific basis for developing targeted interventions.\u003c/p\u003e \u003c/div\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eaBIC \u0026nbsp; \u0026nbsp; \u0026nbsp;Adjusted Bayesian Information Criteria\u003c/p\u003e\n\u003cp\u003eAIC \u0026nbsp; \u0026nbsp; \u0026nbsp; Akaike Information Criterion\u003c/p\u003e\n\u003cp\u003eBIC \u0026nbsp; \u0026nbsp; \u0026nbsp; Bayesian Information Criteria\u003c/p\u003e\n\u003cp\u003eBLRT \u0026nbsp; \u0026nbsp; \u0026nbsp; Bootstrap Likelihood Ratio Test\u003c/p\u003e\n\u003cp\u003eLMRT \u0026nbsp; \u0026nbsp; \u0026nbsp; Lo\u0026ndash;Mendell\u0026ndash;Rubin Test\u003c/p\u003e\n\u003cp\u003eLog(L) \u0026nbsp; \u0026nbsp; \u0026nbsp;Log-likelihood value\u003c/p\u003e\n\u003cp\u003eOR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Odds Ratio\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to express our gratitude to all the participants in the department of ovarian tumor ward, who voluntarily participated and provided sincere responses.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSun F was responsible for the writing of the original draft and data analysis. Wang Q was responsible for the conceptual design, data analysis, obtaining funds, and strictly revised the manuscript. Zhang Y was responsible for the conceptual design, method design, and editing of the manuscript. Meng Y was responsible for the project management, supervision, and obtaining funds.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the Chronic Disease Management Research Project of National Health Commission Capacity Building and Continuing Education Center (GWJJMB202510022147), Collaborative Academic Innovation Project of Shandong Cancer Hospital(No.FC010) and Research and Practice on the Innovation of Moral Education Model for Medical Students during Their Internship Period under the Context of the Comprehensive Ideological and Political Education(XM2024123).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe data that support the results of this study are available on request from\u0026nbsp;\u003c/p\u003e\n\u003cp\u003ethe corresponding author, researcher Yingtao Meng, upon reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been successfully approved by the Ethics Committee of Shandong First Medical University Affiliated Tumor Hospital (Approval Number: 202508030). All research procedures strictly followed the ethical guidelines of the Helsinki Declaration, ensuring the informed consent, voluntariness, absence of harm, and privacy protection rights of the participants.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor details\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eShandong Cancer Hospital and Institute, Shandong First Medical University and Shandong Academy of Medical Sciences, No. 440, Jizuan Road, Jinan, Shandong, China.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n \u003cli\u003eGaona-Luviano, P., Medina-Gaona, L. A., \u0026amp; Maga\u0026ntilde;a-P\u0026eacute;rez, K. (2020). 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Increased healthcare costs by later stage cancer diagnosis. \u003cem\u003eBMC health services research\u003c/em\u003e, \u003cem\u003e22\u003c/em\u003e(1), 1155.\u003c/li\u003e\n \u003cli\u003eChin, L., Hansen, R. N., \u0026amp; Carlson, J. J. (2020). Economic Burden of Metastatic Ovarian Cancer in a Commercially Insured Population: A Retrospective Cohort Analysis. \u003cem\u003eJournal of managed care \u0026amp; specialty pharmacy\u003c/em\u003e, \u003cem\u003e26\u003c/em\u003e(8), 962\u0026ndash;970.\u003c/li\u003e\n \u003cli\u003eJing J, Feng R, Zhang X, Li M, Gao J (2020) Financial toxicity and its associated patient and cancer factors among women with breast cancer: a single-center analysis of low-middle income region in China. \u003cem\u003eBreast Cancer Res Treat\u003c/em\u003e 181(2):435\u0026ndash;443\u003c/li\u003e\n \u003cli\u003eXu, B., So, W. K. W., Choi, K. C., Huang, Y., Liu, M., Qiu, L., et al. (2024). Disparities in cancer-related financial toxicity across economically diverse provinces in China: A multi-center cross-sectional study. \u003cem\u003eAsia-Pacific journal of oncology nursing\u003c/em\u003e, \u003cem\u003e12\u003c/em\u003e, 100636.\u003c/li\u003e\n \u003cli\u003eSmith, J., Yu, J., Gordon, L. G., \u0026amp; Chilkuri, M. (2023). Financial Toxicity and Out-of-Pocket Costs for Patients with Head and Neck Cancer. \u003cem\u003eCurrent oncology (Toronto, Ont.)\u003c/em\u003e, \u003cem\u003e30\u003c/em\u003e(5), 4922\u0026ndash;4935.\u003c/li\u003e\n \u003cli\u003eSmith, G. L., Banegas, M. P., Acquati, C., Chang, S., Chino, F., Conti, R. M., et al. (2022). Navigating financial toxicity in patients with cancer: A multidisciplinary management approach. \u003cem\u003eCA: a cancer journal for clinicians\u003c/em\u003e, 72(5), 437\u0026ndash;453.\u003c/li\u003e\n \u003cli\u003eChen, C., Cao, J., Wang, L., Zhang, R., Li, H., \u0026amp; Peng, J. (2020). Body image and its associated factors among Chinese head and neck cancer patients undergoing surgical treatment: a cross-sectional survey. \u003cem\u003eSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer\u003c/em\u003e, 28(3), 1233\u0026ndash;1239.\u003c/li\u003e\n \u003cli\u003eLuo, Q., Chen, X., Liu, L., Peng, J., \u0026amp; Tang, F. (2025). Financial toxicity-related factors in patients with nasopharyngeal carfcinoma: a cross-sectional study. \u003cem\u003eSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer\u003c/em\u003e, \u003cem\u003e33\u003c/em\u003e(3), 201.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false},"keywords":"Ovarian Cancer, Financial Toxicity, Latent Profile Analysis, China","lastPublishedDoi":"10.21203/rs.3.rs-8660541/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8660541/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eFinancial toxicity is a ubiquitous challenge for the ovarian cancer patient population. Targeting high-risk groups for financial toxicity with precise interventions can alleviate this burden and enhance patients' quality of life. Therefore, this study aimed to analyze the current status and latent profiles of financial toxicity among ovarian cancer patients and explore the factors influencing different profiles of financial toxicity.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA cross-sectional study design was employed. Using convenience sampling, 342 ovarian cancer patients hospitalized in a provincial cancer hospital in Shandong Province from July to November 2025 were enrolled. Data were collected using self-designed questionnaires for general and clinical information, Comprehensive Scores for Financial toxicity based on Patient‑Reported Outcome Measures (COST‑PROM), Simplified version of the 10‑item Connor‑Davidson Resilience Scale (CD‑RISC‑ 10), the Medical Coping Modes Questionnaire (MCMQ), and Social Support Rating Scale (SSRS). Latent profile analysis (LPA) was conducted to identify subgroups based on financial toxicity levels. Multinomial logistic regression was used to analyze the factors influencing financial toxicity across different profiles.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eAmong the 342 ovarian cancer patients, the median financial toxicity score was 17.10\u0026plusmn;(7.88). Latent profile analysis identified three distinct financial toxicity profiles: mild (27.2%), moderate (50.9%), and severe (21.9%). Multinomial logistic regression revealed that the severity of financial toxicity was significantly associated with employment status, type of medical insurance, number of dependent elders, time since diagnosis, disease stage, comorbid chronic conditions, out-of-pocket medication expenses, confrontation, resignation.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eSignificant variability in financial toxicity exists among the three groups of ovarian cancer patients, with over 70% experiencing moderate to severe levels. Healthcare professionals can develop precise nursing interventions based on the profile characteristics and influencing factors of financial toxicity to alleviate patients' financial burden, optimize treatment outcomes, and enhance their quality of life.\u003c/p\u003e","manuscriptTitle":"Financial toxicity profiles and influencing factors among ovarian cancer Patients: a latent profile analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-08 17:22:55","doi":"10.21203/rs.3.rs-8660541/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewersInvited","content":"","date":"2026-03-01T22:32:14+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-01T22:30:56+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-03T04:05:41+00:00","index":"","fulltext":""},{"type":"submitted","content":"Supportive Care in Cancer","date":"2026-01-21T13:28:23+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"supportive-care-in-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"jscc","sideBox":"Learn more about [Supportive Care in Cancer](https://www.springer.com/journal/520)","snPcode":"520","submissionUrl":"https://submission.nature.com/new-submission/520/3","title":"Supportive Care in Cancer","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Springer Hybrid","inReviewEnabled":true,"inReviewRevisionsEnabled":false}}],"origin":"","ownerIdentity":"3d4373f1-829a-4c74-80ef-425ad690f647","owner":[],"postedDate":"March 8th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-08T17:22:56+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-08 17:22:55","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8660541","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8660541","identity":"rs-8660541","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}