Fertility Preservation,fertility concerns and Decision-Making in Breast Cancer Patients of Childbearing Age: A Cross-sectional Study

Fertility Preservation,fertility concerns and Decision-Making in Breast Cancer Patients of Childbearing Age: A Cross-sectional Study | 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 Fertility Preservation,fertility concerns and Decision-Making in Breast Cancer Patients of Childbearing Age: A Cross-sectional Study Yujiao Li, Yanhui Zhou, Wangmu Lazhen, Can Gu, Xiuzhen Luo, Hongxia Zhou, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7011387/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Breast cancer (BC) incidence in adults younger than 45 years is steadily increasing in China, raising concerns about the long-term quality of life for young survivors. As many of these patients are of reproductive age, treatment-related gonadotoxicity poses a significant threat to their future fertility.While fertility preservation (FP) options such as egg/embryo freezing or ovarian suppression exist, FP decision-making in BC patients remains inconsistent. Factors such as limited awareness, time constraints during cancer treatment, and conflicting medical advice may contribute to this variability. Understanding how fertility concerns influence FP choices is critical to improving patient-centered care. Purpose This study examines the association between fertility preservation choices and fertility-related concerns in BC patients, aiming to identify key factors that shape FP decision-making. Methods From February 2024 to June 2024,279 female BC patients were selected from the cancer centers of 3 tertiary Level A general hospitals in Hengyang cities of Hunan Province.The patients completed the Chinese version of the Reproductive Concerns After Cancer Scale(RCACS), the Decision Regret Scale(DRS), the Decision Conflict Scale(DCS), and the Decision Self-Efficacy Scale(DES).A binary logistic regression model was used to explore the relationships among FP choice,decision-making and fertility concerns. Result Correlation analyses revealed significant correlations( p < 0.01 ) with decision regret, decision conflict, and self-efficacy, but non-significant correlations( p = 0.306 ) with fertility concerns.However, binary logistic regression showed that FP choices were statistically significantly associated with decision regret (OR = 1.053, 95%CI 1.025–1.082, p < 0.05) as well as fertility concerns (OR = 0.95, 95%CI 0.921–0.981, p < 0.05).This suggests that the relationship between fertility protection and fertility concerns may be influenced by a combination of factors rather than a simple linear relationship. Conclusion Fertility preservation choices in young breast cancer patients are significantly influenced by decision psychological experience and fertility concerns. Breast cancer Fertility preservation Fertility concern Decision-making Decision regret Figures Figure 1 Introduction The incidence of BC in younger women has been observed to steadily increase both in China and globally [1, 2].In China,it is hypothesized that the age distributions of pregnancy and breast cancer may exhibit an overlap, as women become pregnant at a comparatively later age[3].The age of breast cancer diagnosis is decreasing, while social trends delay childbearing. As a result, many women diagnosed with breast cancer have not yet completed their family planning and may desire future children[4].With the development of multi-mode diagnosis and progressive treatment,the long-term survival rate of breast cancer patients has greatly improved ,however,we can’t only pay attention to patients’ survival but not their lives.In China, the desire of offspring is often shaped by Confucian values emphasizing family continuity, where infertility may be perceived as a social stigma or familial responsibility failure[5]. In particular,it’s worth noting that treatments such as chemotherapy and radiotherapy are potentially damaging to ovarian function, putting patients at risk of reduced or lost fertility[6].For example, commonly used chemotherapeutic agents such as anthracyclines and cyclophosphamide can significantly increase the risk of premature ovarian failure, especially in older patients[7, 8].Therefore, FP is necessary for breast cancer patients of reproductive age as well as making informed FP decisions for these patients[9, 10].Nevertheless, such decisions often carry a psychological burden, as concerns about future fertility may cause significant distress and persistent fertility-related anxiety. For instance,breast cancer patients have higher levels of fertility concerns.The mean total score of the Reproductive Concerns After Cancer Scale(RCACS) in female patients with breast cancer was found to be 55.84(95%CI: 53.26-58.43)[11].Common sense would suggest that fertility concerns should be lower in cancer patients after FP.Benedict et al. Reported that high fertility concerns and avoidant coping were associated with poorer quality decision making about family building after cancer[12].Patients faced with FP choices are often caught in a decision-making dilemma as they need to weigh complex medical information, personal values, and emotional factors[13, 14].According to clinical guidelines (e.g., ASCO), clinicians should routinely discuss fertility preservation with premenopausal breast cancer patients, including fertility counseling on treatment impacts and options like oocyte/embryo cryopreservation and GnRH agonists. [15].Women with breast cancer who are of childbearing age face two forms of pressure: treatment and childbearing. This combination of factors can render them more vulnerable to decision-making dilemmas.It is evident that individuals grappling with more severe levels of decision-making dilemmas are susceptible to adverse emotions, including anxiety and depression[16].It can therefore be concluded that such moods can act on the decision maker, causing difficulties in decision-making to intensify[16].It can further impair their ability to make informed choices.[16].However, it remains unclear how fertility concerns and decisional conflict influence FP choices in reproductive-age breast cancer patients. Guided by the Decision Conflict Theory—which suggests that uncertainty and information gaps contribute to decisional distress—this study examines how fertility concerns interact with psychological factors (e.g., regret, self-efficacy) in FP decisions among Chinese breast cancer patients. Some patients pursue FP before treatment, while others do not. Yet, it is unknown whether undergoing FP actually reduces fertility concerns. Therefore, this study compares psychological outcomes between these two groups. Based on existing evidence, we propose two hypotheses: 1. FP choices and fertility concerns are positively correlated, as patients who pursue FP may remain anxious about their reproductive future despite taking protective measures. 2. Patients who choose for FP experience higher decision regret and decision conflict, given the complex trade-offs involved in the process.. Methods Study design, setting, and Participants This cross-sectional study was conducted from February 2024 to June 2024 at three tertiary hospitals in Hunan Province. We enrolled 279 female BC patients who met the following criteria:(1) pathological confirmed breast cancer; (2)age 20 to 45 years(aligned with China's legal marriage age);(3)Normal cognitive and communication abilities; (4) Willing to participate with informed consent.The following exclusion criteria were used:(1)other malignancies and advanced tumors or brain metastases; (2) Neurological disorders or psychiatric history;(3)non Chinese speakers.The sample size was calculated using Spss 27.0 software. According to empirical methods,sample sizes are usually 5 to 10 times the size of the study variable[17].The present study incorporated a comprehensive array of 28 potential factors influencing FP decision-making in female breast cancer patients of reproductive age.Considering a missing data rate of 10% - 20%, the final sample size was determined to be 168 - 336 persons.In this investigation, 320 questionnaires were retrieved, out of which 279 were deemed valid, resulting in a valid response rate of 87.12%. Procedure The researchers first contacted the nursing departments of each hospital and sought consent from the nursing administrators. Subsequently, members of the research team visited breast disease centres in various hospitals and contacted nurses in the departments to ascertain the characteristics of the patients.The members of the follow-up group communicated the purpose and significance of the study to breast cancer patients through face-to-face communication. Patients who consented to participation in the study were included in subsequent analyses by the researcher during the follow-up visit. This was confirmed both by the researcher and the breast cancer patient. A time was then arranged to complete the questionnaire.The participants completed a pen-and-paper survey in a quiet, private room. First, the investigators described the purpose, significance, and methods of the study to the patients who met the inclusion criteria. After the breast cancer patients signed the informed consent form, they were given standardized instructions and self-administered questionnaires were used for data collection. The entire survey took approximately 30 min to complete and all the participants were given small gifts with a value of no more than 10 RMB to compensate them for their time. Measures General demographic questionnaire Demographic and clinical variables were evaluated through General demographic questionnaire including demographic information such as age,ethnicity,marital status,education,economic conditions and occupation, as well as clinical information like cancer stage. Fertility concerns Fertility concerns was measured using the Chinese version of the Reproductive Concerns After Cancer Scale (RCACS; 18 items), which includes six domains: fertility potential, becoming pregnant, personal health, child’s health, partner disclosure, and acceptance[18]. Responses are on a 5-point Likert scale from “1=strongly disagree” to“5=strongly agree.” RCACS mean scores range from 18 to 90 with higher scores indicating higher levels of distress.The RCACS is relatively mature and has strong validity.And the scale demonstrated good internal consistency (Cronbach’s alpha=0.912). Decision conflict scale The Decision Conflict Scale (DCS; 16 items) assesses personal uncertainty in making health decisions and includes five domains: feeling uncertain, feeling uninformed, feeling unclear about values,feeling unsupported, and ineffective decision making[19]. The DCS is scored on a 5-point scale from 0 to 4, with scores ranging from 0 to 64. Higher scores indicate greater decision conflict.The DCS is widely used and has excellent validity.And the DCS demonstrated very good internal consistency ( Cronbach’s alpha=0.923). Decision self-efficacy scale The Decision Self-Efficacy Scale(DSE; 11 items) measures self-confidence or belief in one’s abilities in decision making(e.g., ability to seek and obtain information about options, express concerns and views,and make an informed choice)[20].DSE comprises five domains: information acquisition efficacy, information comprehension and decision-making efficacy,communication and expression efficacy,social support efficacy and stress coping and decision autonomy. The DSE is scored on a 5-point scale from 0 to 4, with scores ranging from 0 to 44. Higher scores indicate greater decision self-efficacy. In this study ,we chose the Chinese version of the decision self-efficacy scale,which has strong validity.The DSE demonstrated very good internal consistency ( Cronbach’s alpha=0.743). Decision regret scale The Decision Regret Scale(DRS;5 items) is a widely used instrument designed to measure the level of regret or distress experienced by individuals following a healthcare decision[21].Higher scores on the DRS indicate greater decision regret.The DRS has excellent reliability and validity. The DRS demonstrated very good internal consistency ( Cronbach’s=0.727) in this research. Data analysis plan All data were analyzed using SPSS version 27.0. Descriptive statistics were used to report the demographics, the characteristics of the clinical variables, and the means of all the variables.After the normality test,it is found that the data is skewed,so the Mann-Whitney U test is used to investigate the associations between various arguments and fertility conservation decisions.According to Hosmer who reported on the use of logistic regression analysis, a binary logistic regression model can be chosen when the dependent variable is a binary categorical variable and the independent variable is continuous and/or categorical[22].In this study, reproductive distress, decisional conflict,decision self-efficacy and decision regret were treated as continuous variables,while fertility conservation decision is a bitaxonomic variable, so binary logistic regression analyses were performed on them in relation to demographic and clinical characteristics.The variables were subjected to screening using a backwards stepwise regression (BSR) model with a p-value cut-off of less than 0.1. This approach was employed to circumvent issues of multicollinearity.Statistically significant OR values ( p < 0.05) for independent variables, along with their 95% confidence intervals not including 1, indicate that the variables have a significant impact on the odds of the binary outcome. Results Individual characteristic information The sample consisted of 279 female participants aged from 20 to 45.All participants were patients suffering from breast cancer and were of reproductive age.The distribution of educational levels was as follows:30.5%(n = 85) had a lower secondary school diploma,15.8%(n = 44) had a high school diploma,28.7%(n = 80) had an associate degree,25.1%(n = 70) had a bachelor’s degree.The details of the descriptive analysis are shown in Table 1 . Table 1 Descriptive statistics for sociodemographic and clinical characteristics( N = 279) Variable n % Variable n % Age(year) 20–24 22 8.1 Marital status 25–29 62 22.8 Single 72 26.5 30–34 87 32 Married 189 69.5 35–40 64 23.5 Divorced or Widowed 11 4 40–55 37 13.6 Number of offspring Ethnicity Ethnic Han 254 93.4 0 102 37.5 National minority 18 6.6 1 34 12.5 Occupation 2 136 50 Employed 164 60.3 Fertility desire Unemployed 108 39.7 Yes 157 57.7 Family monthly wage (CNY/person) No 115 42.3 ≤ 1000CNY 28 10.3 Breast cancer stage 1001-5000CNY 75 27.6 I 47 17.3 5001-10000CNY 99 36.4 II 67 24.6 ≥ 10000CNY 70 25.7 III 118 43.4 Education level IV 40 14.7 Junior high school or Below 83 30.5 Operation 202 74.3 High school or technical 43 15.8 Radiotherapy 95 34.9 Associate Degree 78 28.7 Chemotherapy 210 77.2 Bachelor's Degree or Above 68 25 Oral drugs 24 8.8 With regard to the participants' decision “to have fertility preservation or not”, 62%(n = 173) of the participants chose “yes”.The mean score of the RCACS was 55.27 (SD = 13.44). The scores ranged from 30 to 76. The scores, maxima, minima and ranges of the other scales are shown in Table 2 . The results of the normality test showed that the scales data were skewed. Table 2 Descriptive statistics of the scales n Range Min Max Mean SD RCACS 279 46 30 76 55.27 13.44 DSE 279 77.27 15.91 93.18 42.42 13.70 DRS 279 80 20 100 53.92 16.58 DCS 279 78.13 14.06 92.19 54.61 20.63 Differences between fertility preservation and non-preservation groups The Shapiro-Wilk test yielded a p-value of less than 0.05, thereby indicating that the sample does not conform to a normal distribution.So we used the Mann-Whitney U test to measure the relationship between FP and the other scales.The findings of the study demonstrated that there was no difference between fertility concerns and the decision to opt for FP.But whether or not fertility protection makes a difference between decision conflict, decision self-efficacy, and decision regret.And the specific data results of this study are shown in Table 3 and Fig. 1 . Table 3 Mann-Whitney U test for FP and each scales Fertility Preservation Group Difference No(n = 106) Yes(n = 173) Z P RCACS (39.00,68.25) (44.00,68.00) 1.024 0.306 DCS (29.69,56.25) (50.78,80.47) 6.795 < 0.01 DRS (32.00,52.00) (52.00,68.00) 7.321 < 0.01 DSE (36.36,54.55) (29.55,47.73) -3.898 < 0.01 The correlations among fertility concerns,decision-making and characteristic information The chi-square value of the model is 108.485 with 22 degrees of freedom, p < 0.001, indicating that the model is statistically significantly better than the model containing only the intercept.The results showed that the x² of the Hosmer-Lemeshaw test in the binary logistic regression analysis was 5.844 with p = 0.665 > 0.05, indicating a good model match.Using p < 0.05 as the test level, it was found that the patients' place of residence, fertility intentions, decision-making regrets, and fertility worries had a statistically significant effect on whether or not they chose fertility preservation.The specific modeling is shown in Table 4 . Table 4 Binary logistic regression analysis with FP as the dependent variable. B SE Wald P Exp(B) 95%CI Low Up Step 1a Place of residence 5.961 0.051 Place of residence(Urban) -0.688 0.385 3.195 0.074 0.503 0.236 1.069 Place of residence(Rural) -1.075 0.462 5.407 0.02 0.341 0.138 0.845 Occupation (Employed) -0.491 0.401 1.505 0.22 0.612 0.279 1.341 Family monthly wage 2.122 0.547 Family monthly wage (≤ 1000CNY) -0.265 0.538 0.243 0.622 0.767 0.267 2.202 Family monthly wage (1001-5000CNY) -0.659 0.601 1.202 0.273 0.517 0.159 1.681 Family monthly wage (5001-10000CNY) -0.837 0.63 1.765 0.184 0.433 0.126 1.489 Education level 1.063 0.786 Junior high school or Below -0.291 0.474 0.379 0.538 0.747 0.295 1.89 High school or technical -0.318 0.458 0.481 0.488 0.728 0.297 1.785 Associate Degree 0.053 0.505 0.011 0.917 1.054 0.391 2.84 Marital status 6.416 0.04 Married 0.642 0.411 2.443 0.118 1.901 0.849 4.254 single/divorced/widowed -2.551 1.342 3.613 0.057 0.078 0.006 1.083 Number of offspring 3.193 0.203 Number of offspring(0) 0.711 0.585 1.478 0.224 2.036 0.647 6.402 Number of offspring(1) -0.361 0.488 0.547 0.46 0.697 0.268 1.815 Fertility desire (Yes) 0.851 0.434 3.834 0.05 2.341 0.999 5.484 Medical insurance(Yes) 0.844 0.701 1.451 0.228 2.325 0.589 9.178 Breast cancer stage 4.664 0.198 Breast cancer stage(I) -0.118 0.557 0.045 0.833 0.889 0.298 2.649 Breast cancer stage(II) -0.317 0.521 0.37 0.543 0.729 0.263 2.021 Breast cancer stage(III) -1.224 0.651 3.532 0.06 0.294 0.082 1.054 DCS 0.02 0.016 1.708 0.191 1.021 0.99 1.052 DSE -0.013 0.013 0.965 0.326 0.987 0.962 1.013 DRS 0.052 0.014 14.05 < 0.001 1.053 1.025 1.082 RCACS -0.051 0.016 10.17 0.001 0.95 0.921 0.981 Constant 1.341 1.532 0.766 0.381 3.822 Discussion Our study investigate that the relationship between the psychological experience of fertility concerns and decision-making in two groups of breast cancer patients who took FP and those who did not.In order to resolve the issue, binary logistic regression analysis was employed to examine the correlation between the two groups.We reached two main conclusions.On the one hand,our study confirmed that fertility concerns is prevalent in young female breast cancer patients with fertility intention and that their level of fertility concerns is higher than that of breast cancer patients who did not take FP. On the other hand,our findings also show that Patients who elected to opt for FP exhibited elevated levels of decision regret and decision conflict. Patients who chose FP had stronger fertility intentions and higher fertility concerns.Armuand et alreported that failure to achieve fertility aspirations after cancer treatment may lead to the deterioration of patients’ mental health[23].Specifically,failure to achieve fertility aspirations may increase patients’ fertility concerns. In contrast to the hypothesis, FP choices reduces fertility concerns.Based on the study results, fertility concerns were high in both groups, and the difference between them was not statistically significant.This implies that the decision to opt for FP may not be significantly affected by a patient's degree of fertility concern.On the one hand,the relationship between fertility protection and fertility concerns may be influenced by a combination of factors rather than a simple linear relationship.So the result of their correlation analysis showed no significant relationship.On the other hand, it may also be limited by scale dimensions - for example, the RCACS does not distinguish between ‘short-term concerns’ (e.g., immediate ovarian damage from treatment) and ‘long-term concerns’(e.g., FP success).Therefore, it is not possible to confirm whether the absence of a statistically significant difference in fertility concerns between the two groups is attributable to confounding. This is due to the fact that the two groups exhibited differences in both long-term and short-term concerns.At present, the majority of cancer patients have limited knowledge of FP[24, 25].Consequently, most patients are skeptical about the effectiveness of FP.According to the perceived benefits in the Health Belief Model[26], the degree to which patients expect FP to be successful also influences their decision[27].Moreover,the long-term benefits of FP are underestimated.Since cancer patients believe that their top priority is to overcome cancer, they may be more concentrated on current cancer treatments[28, 29].Conversely, the benefits of fertility protection are regarded as long-term, so the immediate benefits of fertility protection are not apparent.Therefore,in clinical work,it suggests that clinics need to strengthen ‘expectation management’ in FP counselling to avoid patients' subsequent psychological fallout due to overly high expectations. A considerable number of breast cancer patients encounter difficulties in making decisions regarding FP following cancer diagnosis, as evidenced by patients who chose FP had higher levels of decision regret and decision conflict.This hypothesis was based upon previous research showing that young adult breast cancer patients who received fertility counseling prior to beginning treatment had increased reproductive concerns relative to patients who did not receive counseling[30].Moreover,most of people who chose FP were received fertility counseling.However,there are study show that regret scores will decrease as fertility information adequacy increases[31].In our research,patients who chose FP had higher decision regret scores than those who did not.In other words,this suggests that fertility counselling for patients opting for FP is not adequate.Drawing on the Self-efficacy Theory [32], the higher decision regret in the FP group may stem from the mismatch between patients’ optimistic expectations of FP success and the reality of potential ovarian failure after treatment. This aligns with Brehaut et al.’s finding that unmet expectations significantly drive post-decision regret in medical contexts[21].Limited knowledge regarding the FP process, success rates, and financial implications may aggravate decision-making conflicts among patients[33].This conflict may lead patients to regret their decisions later, especially when they discover better alternatives[34].Furthermore,the findings revealed statistically significant differences in decision conflict and decision regret between patients who chose fertility protection and those who did not.Notably, patients who chose FP exhibited higher levels of decision conflict and decision regret.It is hypothesized that patients who choose FP have higher expectations for future fertility[35].Once treatment leads to ovarian failure, the likelihood of regret increases.Patients may feel that although they have undergone FP procedures, they have not actually achieved FP.Consequently, they regret their previous decision.For patients, particularly female patients, cancer treatment itself poses a significant financial burden[36].It also adds to their feelings of regret.Therefore, clinical nursing practitioners should pay attention to the psychological and intellectual aspects support that they can provide to patients, especially through participating in enough fertility counseling, which can help alleviate the decision regret of young breast cancer patients and psychological burden.Clinicians should adopt a three-phase counseling model: (1) pre-diagnosis: provide simplified FP brochures in both Mandarin and local dialects; (2) treatment planning: involve spouses in shared decision-making sessions to address familial concerns; (3) post-decision: offer monthly group counseling for FP recipients to manage anxiety about treatment outcomes. Moreover,the negative emotions of breast cancer patients may influence their decisions regarding FP.Previous studies by Catherine B et al. have demonstrated that negative emotions in young breast cancer patients influence their treatment decisions[16].However, no prior studies have explored the direct relationship between the choice of FP in cancer patients and their fertility concerns.Meanwhile, this study offers a novel perspective.Our study has refined this point.We compared data from cross-sectional studies of patients who chose FP with those who did not.We found that current cancer patients have low satisfaction levels regarding FP decision-making.This study revealed that patients' educational attainment, economic status, marital status, and fertility intentions were positively correlated with the choice of FP,consistent with previous findings. In the Chinese context, FP decisions are often influenced by familial pressures to maintain generational continuity[5]. The high proportion of married patients (69.5%) in our sample suggests that spousal attitudes and parental expectations may implicitly pressure women to choose FP, even when they have reservations, potentially exacerbating decision conflict.Adequate fertility counselling has been demonstrated to reduce patient decision-making regrets and increase decision-making satisfaction[31].Greater awareness of fertility preservation helps patients to understand its benefits and enables them to make the most rational decisions.Therefore, clinical care practitioners not only need to readily answer patients‘confusion about their knowledge of FP, but also focus on and enhance fertility counselling for breast cancer patients, which may be an effective strategy to mitigate patients’ decision-making regrets and improve decision-making outcomes. Conclusions Female breast cancer of childbearing in China experience moderate levels of fertility concern.Fertility concern is negative factors against FP choices.High levels of fertility concern contribute to a greater preference for no FP among reproductive age breast cancer patients to withstand decision conflict, therefore the lower their decision-making dilemma.Therefore, multiple strategies should be explored by hospitals to reduce fertility concern, commencing with an objective assessment of the decision-making dilemma faced by young breast cancer patients, which is critical for enhancing their fertility preservation (FP) choices.Especially for patients with high level of fertility concern, clinical nursing practitioners should help make FP decision.Specifically, clinical nursing practitioners should guide patients to make FP decision with a reasonable choice to reduce their decision conflict. Furthermore, research should continue to explore the modifiable risk and protective factors associated with decision conflict, which will help promote mental health and improve the quality of life among breast cancer survivors in China.Given that FP is currently uninsured in most Chinese provinces, advocating for its inclusion in public healthcare policies or establishing hospital-based financial aid programs could mitigate the economic barriers highlighted in this study. Limitations This study has several limitations. First, the cross-sectional design precludes causal inference between FP choices, fertility concern, and psychological variables, necessitating longitudinal follow-up. Second, the sample from three Hunan Province hospitals may limit generalizability; multi-regional or international sampling could enhance validity. Third, the regression model did not account for contextual factors (e.g., physician recommendations, hospital FP services) or family-level influences (e.g., spousal attitudes, traditional childbearing values), which may improve model fit if incorporated. Additionally, slight demographic imbalances in the sample highlight the need for more balanced sampling in future research. Finally, while quantitative methods captured fertility concern, qualitative approaches could deeper explore how cultural values shape decision-making, a direction for future work. Declarations The study was approved by the medical ethics committee of the University of South China (approval number: 2023NHHL047).The researcher apprised all eligible patients of the objective of this study and ensured that their information would remain confidential and solely utilized for this study.Consent was acquired by filling out a form of agreement and a self-reported questionnaire. If, during the course of the study, the subject does not wish to continue in the study, they may withdraw without giving a reason. Acknowledgments The authors thank the participants of this study for their time and dedication. Funding This study was funded by Hunan Provincial Appraisal Committee for Social Science Achievements (grant number XSP2023JYZ030). Conflict of interest The authors declare that they have no conflict of interest. Ethica l approval All procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Medical Ethics Committee of University of South China(approval number:2023NHHL047). Inform consent All participants provided written informed consent before recruitment. Author contributions Yujiao Li, Wangmu Lazhen and Yanhui Zhou contributed to the study conception and design. Material preparation were performed by Yujiao Li, Wangmu Lazhen,Can Gu,Ling Zhao, Junrui Chen,Qiao Deng.Data collection were performed by Yujiao Li, Wangmu Lazhen, Qifan Ren, Xiuzhen Luo, Hongxia Zhou,Susan Qian,Huichang Tan and Shuying Xie under the supervision of Yanhui Zhou.Data analysis were performed by Yujiao Li and Wangmu Lazhen. The first draft of the manuscript was written by Yujiao Li and Wangmu Lazhen. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability the datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Interested stakeholders may communicate with the corresponding author (Yanhui Zhou) to access de-identified datasets. 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European Journal of Cancer Care , 2025 (1). https://doi.org/10.1155/ecc/1470807 Su HI, Lacchetti C, Letourneau J, Partridge AH, Qamar R, Quinn GP, Reinecke J, Smith JF, Tesch M, Wallace WH et al . (2025). Fertility Preservation in People With Cancer: ASCO Guideline Update. J Clin Oncol , 43 (12), 1488-1515. https://doi.org/10.1200/jco-24-02782 Catherine B, Alexandria LH, Alyssa M, Joanne FK, Michael D, Jennifer SF. (2020). Toward a theoretical understanding of young female cancer survivors’ decision-making about family-building post-treatment. Supportive Care in Cancer , 28 (10), 4857-4867. https://doi.org/10.1007/s00520-020-05307-1 Hanley JA. (2016). Simple and multiple linear regression: sample size considerations. J Clin Epidemiol , 79 , 112-119. https://doi.org/10.1016/j.jclinepi.2016.05.014 Gorman JR, Su HI, Pierce JP, Roberts SC, Dominick SA, Malcarne VL. (2014). A multidimensional scale to measure the reproductive concerns of young adult female cancer survivors. J Cancer Surviv , 8 (2), 218-228. https://doi.org/10.1007/s11764-013-0333-3 Lam WW, Kwok M, Liao Q, Chan M, Or A, Kwong A, Suen D, Fielding R. (2015). Psychometric assessment of the Chinese version of the decisional conflict scale in Chinese women making decision for breast cancer surgery. Health Expect , 18 (2), 210-220. https://doi.org/10.1111/hex.12021 O’Connor AM (2002) User manual—Decision Self-Efficacy Scale Ottawa [ https://decisionaid.ohri.ca/docs/develop/User_Manuals/UM_Decision_SelfEfficacy.pdf] Brehaut JC, O'Connor AM, Wood TJ, Hack TF, Siminoff L, Gordon E, Feldman-Stewart D. (2003). Validation of a decision regret scale. Med Decis Making , 23 (4), 281-292. https://doi.org/10.1177/0272989x03256005 Hosmer Jr DW, Lemeshow S, Sturdivant RX: Applied logistic regression: John Wiley & Sons; 2013. Armuand GM, Wettergren L, Rodriguez-Wallberg KA, Lampic C. (2014). Desire for children, difficulties achieving a pregnancy, and infertility distress 3 to 7 years after cancer diagnosis. Support Care Cancer , 22 (10), 2805-2812. https://doi.org/10.1007/s00520-014-2279-z Reza O-S, Samira V, Behnaz N, Marzieh M, Khadijeh Arjmandi R, Seyyedeh Zahra Nemati A, Maryam M. (2021). Adult cancer patients and parents of younger cancer patients have little information about fertility preservation: a survey of knowledge and attitude. Middle East Fertility Society Journal , 26 (1). https://doi.org/10.1186/s43043-021-00072-5 Meng W, Lixia Z, Hua X, Jiaming W, Zhou L, Liu Y, Lei J, Qingsong X. (2020). Lack of Knowledge, the main Stumbling Block of Fertility Preservation Promotion in China. Journal of Cancer Education , 37 (3), 739-747. https://doi.org/10.1007/s13187-020-01875-2 Irwin MR. (2000). Health Belief Model. Encyclopedia of psychology, Vol 4 , 78-80. https://doi.org/10.1037/10519-035 Jones G, Hughes J, Mahmoodi N, Smith E, Skull J, Ledger W. (2017). What factors hinder the decision-making process for women with cancer and contemplating fertility preservation treatment? Hum Reprod Update , 23 (4), 433-457. https://doi.org/10.1093/humupd/dmx009 Garvelink MM, ter Kuile MM, Fischer MJ, Louwé LA, Hilders CG, Kroep JR, Stiggelbout AM. (2013). Development of a Decision Aid about fertility preservation for women with breast cancer in The Netherlands. J Psychosom Obstet Gynaecol , 34 (4), 170-178. https://doi.org/10.3109/0167482x.2013.851663 Perz J, Ussher J, Gilbert E. (2014). Loss, uncertainty, or acceptance: subjective experience of changes to fertility after breast cancer. Eur J Cancer Care (Engl) , 23 (4), 514-522. https://doi.org/10.1111/ecc.12165 Young K, Shliakhtsitsava K, Natarajan L, Myers E, Dietz AC, Gorman JR, Martínez ME, Whitcomb BW, Su HI. (2019). Fertility counseling before cancer treatment and subsequent reproductive concerns among female adolescent and young adult cancer survivors. Cancer , 125 (6), 980-989. https://doi.org/10.1002/cncr.31862 Campbell AG, Hillemeier M. (2021). Fertility counseling information adequacy as a moderator of regret among adolescent and young adult breast cancer survivors. Support Care Cancer , 29 (5), 2689-2697. https://doi.org/10.1007/s00520-020-05771-9 Albert B. (1977). Self-efficacy: Toward a unifying theory of behavioral change. Psychological Review , 84 (2), 191-215. https://doi.org/10.1037/0033-295x.84.2.191 Yan W, Qingyue Z, Jianmei P, Liyuan S, Xiaoyuan W, Di Y, Jian Y, Wanmin Q. (2021). Relationship Between Decision Conflict and Decision Regret Among Postoperative Breast Cancer Patients in China: The Regulating Role of Decision-Making Preparation. https://doi.org/10.21203/rs.3.rs-442596/v1 Angela GC, Marianne H. (2020). Fertility counseling information adequacy as a moderator of regret among adolescent and young adult breast cancer survivors. Supportive Care in Cancer , 29 (5), 2689-2697. https://doi.org/10.1007/s00520-020-05771-9 Tomomi A, Akemi K, Natsue U, Nao Y, Meiko N, Yukinori O, Takahiro K, Toshimi T, Shinji O, Takayuki U. (2024). Desire for pregnancy and fertility preservation in young patients with breast cancer. Breast Cancer , 31 (6), 1137-1143. https://doi.org/10.1007/s12282-024-01633-y Jingfeng J, Ran F, Xiaojun Z, Ming L, Jinnan G. (2020). Financial toxicity and its associated patient and cancer factors among women with breast cancer in China. Journal of Clinical Oncology , 38 . https://doi.org/10.1200/jco.2020.38.15_suppl.e19402 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Groups\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-7011387/v1/88603ddfc741399d5fad645f.jpg"},{"id":100949557,"identity":"02dc06f2-0283-4a06-a289-163c35b086d5","added_by":"auto","created_at":"2026-01-23 07:04:13","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":954553,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7011387/v1/a1fdcc26-5a33-48bd-b6fd-939b39fac164.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Fertility Preservation,fertility concerns and Decision-Making in Breast Cancer Patients of Childbearing Age: A Cross-sectional Study","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe incidence of BC in younger women has been observed to steadily increase both in China and globally [1, 2].In China,it is hypothesized that the age distributions of pregnancy and breast cancer may exhibit an overlap, as women become pregnant at a comparatively later age[3].The age of breast cancer diagnosis is decreasing, while social trends delay childbearing. As a result, many women diagnosed with breast cancer have not yet completed their family planning and may desire future children[4].With the development of multi-mode diagnosis and progressive treatment,the long-term survival rate of breast cancer patients has greatly improved ,however,we can\u0026rsquo;t only pay attention to patients\u0026rsquo; survival but not their lives.In China, the\u0026nbsp;desire\u0026nbsp;of offspring\u0026nbsp;is often shaped by Confucian values emphasizing family continuity, where infertility may be perceived as a social stigma or familial responsibility failure[5].\u003c/p\u003e\n\u003cp\u003eIn particular,it\u0026rsquo;s worth noting that\u0026nbsp;treatments such as chemotherapy and radiotherapy are potentially damaging to ovarian function, putting patients at risk of reduced or lost fertility[6].For example, commonly used chemotherapeutic agents such as anthracyclines and cyclophosphamide can significantly increase the risk of premature ovarian failure, especially in older patients[7, 8].Therefore, FP is necessary for breast cancer patients of reproductive age\u0026nbsp;as well as\u0026nbsp;making informed FP decisions\u0026nbsp;for these patients[9, 10].Nevertheless, such decisions often carry a psychological burden, as concerns about future fertility may cause significant distress and persistent fertility-related anxiety.\u003c/p\u003e\n\u003cp\u003eFor instance,breast cancer patients have higher levels of fertility concerns.The mean total score of the Reproductive Concerns After Cancer Scale(RCACS) in female patients with breast cancer was found to be 55.84(95%CI: 53.26-58.43)[11].Common sense would suggest that fertility concerns should be lower in cancer patients after FP.Benedict et al. Reported that high fertility concerns and avoidant coping were associated with poorer quality decision making about family building after cancer[12].Patients faced with FP choices are often caught in a decision-making dilemma as they need to weigh complex medical information, personal values, and emotional factors[13, 14].According to clinical guidelines (e.g., ASCO), clinicians should routinely discuss fertility preservation with premenopausal breast cancer patients, including fertility counseling on treatment impacts and options like oocyte/embryo cryopreservation and GnRH agonists. [15].Women with breast cancer who are of childbearing age face two forms of pressure: treatment and childbearing. This combination of factors can render them more vulnerable to decision-making dilemmas.It is evident that individuals grappling with more severe levels of decision-making dilemmas are susceptible to adverse emotions, including anxiety and depression[16].It can therefore be concluded that such moods can act on the decision maker, causing difficulties in decision-making to intensify[16].It can further impair their ability to make informed choices.[16].However, it remains unclear how fertility concerns and decisional conflict influence FP choices in reproductive-age breast cancer patients.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eGuided by the Decision Conflict Theory\u0026mdash;which suggests that uncertainty and information gaps contribute to decisional distress\u0026mdash;this study examines how fertility concerns interact with psychological factors (e.g., regret, self-efficacy) in FP decisions among Chinese breast cancer patients. Some patients pursue FP before treatment, while others do not. Yet, it is unknown whether undergoing FP actually reduces fertility concerns. Therefore, this study compares psychological outcomes between these two groups. Based on existing evidence, we propose two hypotheses:\u003c/p\u003e\n\u003cp\u003e1. FP choices and fertility concerns are positively correlated, as patients who pursue FP may remain anxious about their reproductive future despite taking protective measures.\u003c/p\u003e\n\u003cp\u003e2. Patients who choose for FP experience higher decision regret and decision conflict, given the complex trade-offs involved in the process..\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eStudy design, setting, and Participants\u003c/p\u003e\n\u003cp\u003eThis cross-sectional study was conducted from February 2024 to June 2024 at three tertiary hospitals in Hunan Province. We enrolled 279 female BC patients who met the following criteria:(1) pathological confirmed breast cancer; (2)age 20 to 45 years(aligned with China's legal marriage age);(3)Normal cognitive and communication abilities; (4) Willing to participate with informed consent.The following exclusion criteria were used:(1)other malignancies and advanced tumors or brain metastases; (2) Neurological disorders or psychiatric history;(3)non Chinese speakers.The sample size was calculated using Spss 27.0 software. According to empirical methods,sample sizes are usually 5 to 10 times the size of the study variable[17].The present study incorporated a comprehensive array of 28 potential factors influencing FP decision-making in female breast cancer patients of reproductive age.Considering a missing data rate of 10% - 20%, the final sample size was determined to be 168 - 336 persons.In this investigation, 320 questionnaires were retrieved, out of which 279 were deemed valid, resulting in a valid response rate of 87.12%.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eProcedure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe researchers first contacted the nursing departments of each hospital and sought consent from the nursing administrators. Subsequently, members of the research team visited breast disease centres in various hospitals and contacted nurses in the departments to ascertain the characteristics of the patients.The members of the follow-up group communicated the purpose and significance of the study to breast cancer patients through face-to-face communication. Patients who consented to participation in the study were included in subsequent analyses by the researcher during the follow-up visit. This was confirmed both by the researcher and the breast cancer patient. A time was then arranged to complete the questionnaire.The participants completed a pen-and-paper survey in a quiet, private room. First, the investigators described the purpose, significance, and methods of the study to the patients who met the inclusion criteria. After the breast cancer patients signed the informed consent form, they were given standardized instructions and self-administered questionnaires were used for data collection. The entire survey took approximately 30 min to complete and all the participants were given small gifts with a value of no more than 10 RMB to compensate them for their time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasures\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eGeneral demographic questionnaire\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDemographic and clinical variables were evaluated through General demographic questionnaire including demographic information such as age,ethnicity,marital status,education,economic conditions and occupation, as well as clinical information like cancer stage.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFertility\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econcerns\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFertility concerns was measured using the Chinese version of the Reproductive Concerns After Cancer Scale (RCACS; 18 items), which includes six domains: fertility potential, becoming pregnant, personal health, child’s health, partner disclosure, and acceptance[18]. Responses are on a 5-point Likert scale from “1=strongly disagree” to“5=strongly agree.” RCACS mean scores range from 18 to 90 with higher scores indicating higher levels of distress.The RCACS is relatively mature and has strong validity.And the scale demonstrated good internal consistency (Cronbach’s alpha=0.912).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecision conflict scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Decision Conflict Scale (DCS; 16 items) assesses personal uncertainty in making health decisions and includes five domains: feeling uncertain, feeling uninformed, feeling unclear about values,feeling unsupported, and ineffective decision making[19]. The DCS is scored on a 5-point scale from 0 to 4, with scores ranging from 0 to 64. Higher scores indicate greater decision conflict.The DCS is widely used and has excellent validity.And the DCS demonstrated very good internal consistency ( Cronbach’s alpha=0.923).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecision self-efficacy scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Decision Self-Efficacy Scale(DSE; 11 items) measures self-confidence or belief in one’s abilities in decision making(e.g., ability to seek and obtain information about options, express concerns and views,and make an informed choice)[20].DSE comprises five domains: information acquisition efficacy, information comprehension and decision-making efficacy,communication and expression efficacy,social support efficacy and stress coping and decision autonomy. The DSE is scored on a 5-point scale from 0 to 4, with scores ranging from 0 to 44. Higher scores indicate greater decision self-efficacy. In this study ,we chose the Chinese version of the decision self-efficacy scale,which has strong validity.The DSE demonstrated very good internal consistency ( Cronbach’s alpha=0.743).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDecision regret scale\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Decision Regret Scale(DRS;5 items) is a widely used instrument designed to measure the level of regret or distress experienced by individuals following a healthcare decision[21].Higher scores on the DRS indicate greater decision regret.The DRS has excellent reliability and validity.\u003c/p\u003e\n\u003cp\u003eThe DRS demonstrated very good internal consistency ( Cronbach’s=0.727) in this research.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData analysis plan\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data were analyzed using SPSS version 27.0. Descriptive statistics were used to report the demographics, the characteristics of the clinical variables, and the means of all the variables.After the normality test,it is found that the data is skewed,so the Mann-Whitney U test is used \u0026nbsp;to investigate the associations between various arguments and fertility conservation decisions.According to Hosmer who reported on the use of logistic regression analysis, a binary logistic regression model can be chosen when the dependent variable is a binary categorical variable and the independent variable is continuous and/or categorical[22].In this study, reproductive distress, decisional conflict,decision self-efficacy and decision regret were treated as continuous variables,while fertility conservation decision is a bitaxonomic variable, so binary logistic regression analyses were performed on them in relation to demographic and clinical characteristics.The variables were subjected to screening using a backwards stepwise regression (BSR) model with a p-value cut-off of less than 0.1. This approach was employed to circumvent issues of multicollinearity.Statistically significant OR values (\u003cem\u003ep\u003c/em\u003e\u0026lt; 0.05) for independent variables, along with their 95% confidence intervals not including 1, indicate that the variables have a significant impact on the odds of the binary outcome.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cb\u003eIndividual characteristic information\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe sample consisted of 279 female participants aged from 20 to 45.All participants were patients suffering from breast cancer and were of reproductive age.The distribution of educational levels was as follows:30.5%(n\u0026thinsp;=\u0026thinsp;85) had a lower secondary school diploma,15.8%(n\u0026thinsp;=\u0026thinsp;44) had a high school diploma,28.7%(n\u0026thinsp;=\u0026thinsp;80) had an associate degree,25.1%(n\u0026thinsp;=\u0026thinsp;70) had a bachelor\u0026rsquo;s degree.The details of the descriptive analysis are shown in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics for sociodemographic and clinical characteristics(\u003cem\u003eN\u003c/em\u003e\u0026thinsp;=\u0026thinsp;279)\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"8\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eVariable\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c8\"\u003e\u003cp\u003e%\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAge(year)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e20\u0026ndash;24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8.1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25\u0026ndash;29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eSingle\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e26.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30\u0026ndash;34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e189\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e69.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e35\u0026ndash;40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eDivorced or Widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e40\u0026ndash;55\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eNumber of offspring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEthnic Han\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e254\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e93.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e102\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e37.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNational minority\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e34\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e12.5\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eOccupation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e136\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e50\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEmployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e164\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e60.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eFertility desire\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eUnemployed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e108\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e39.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eYes\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e157\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e57.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eFamily monthly wage\u003c/p\u003e\u003cp\u003e(CNY/person)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eNo\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e115\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e42.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026le;\u0026thinsp;1000CNY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10.3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eBreast cancer stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1001-5000CNY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e75\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.6\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eI\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e17.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5001-10000CNY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e36.4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e24.6\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e\u0026ge;\u0026thinsp;10000CNY\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e70\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIII\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e43.4\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003eIV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e14.7\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJunior high school or Below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.5\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOperation\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e74.3\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school or technical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.8\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eRadiotherapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e34.9\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate Degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e78\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e28.7\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eChemotherapy\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e210\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e77.2\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBachelor's Degree or Above\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e\u003cp\u003e68\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eOral drugs\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e8.8\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eWith regard to the participants' decision \u0026ldquo;to have fertility preservation or not\u0026rdquo;, 62%(n\u0026thinsp;=\u0026thinsp;173) of the participants chose \u0026ldquo;yes\u0026rdquo;.The mean score of the RCACS was 55.27 (SD\u0026thinsp;=\u0026thinsp;13.44). The scores ranged from 30 to 76. The scores, maxima, minima and ranges of the other scales are shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. The results of the normality test showed that the scales data were skewed.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eDescriptive statistics of the scales\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003en\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eRange\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eMin\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eMax\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eMean\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\"\u003e\u003cp\u003eSD\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCACS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e76\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e55.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13.44\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.27\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15.91\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e93.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e42.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e13.70\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e80\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e100\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e53.92\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e16.58\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e\u003cp\u003e279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e78.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e92.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c6\"\u003e\u003cp\u003e54.61\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e20.63\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eDifferences between fertility preservation and non-preservation groups\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe Shapiro-Wilk test yielded a p-value of less than 0.05, thereby indicating that the sample does not conform to a normal distribution.So we used the Mann-Whitney U test to measure the relationship between FP and the other scales.The findings of the study demonstrated that there was no difference between fertility concerns and the decision to opt for FP.But whether or not fertility protection makes a difference between decision conflict, decision self-efficacy, and decision regret.And the specific data results of this study are shown in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e and Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eMann-Whitney U test for FP and each scales\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"5\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e\u003cp\u003eFertility Preservation\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colspan=\"2\" nameend=\"c5\" namest=\"c4\"\u003e\u003cp\u003eGroup Difference\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNo(n\u0026thinsp;=\u0026thinsp;106)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003eYes(n\u0026thinsp;=\u0026thinsp;173)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003eZ\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRCACS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(39.00,68.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(44.00,68.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.024\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.306\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(29.69,56.25)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(50.78,80.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.795\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(32.00,52.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(52.00,68.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e7.321\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(36.36,54.55)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(29.55,47.73)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e-3.898\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.01\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003e\u003cb\u003eThe correlations among fertility concerns,decision-making and characteristic information\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe chi-square value of the model is 108.485 with 22 degrees of freedom, p\u0026thinsp;\u0026lt;\u0026thinsp;0.001, indicating that the model is statistically significantly better than the model containing only the intercept.The results showed that the x\u0026sup2; of the Hosmer-Lemeshaw test in the binary logistic regression analysis was 5.844 with \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.665\u0026thinsp;\u0026gt;\u0026thinsp;0.05, indicating a good model match.Using p\u0026thinsp;\u0026lt;\u0026thinsp;0.05 as the test level, it was found that the patients' place of residence, fertility intentions, decision-making regrets, and fertility worries had a statistically significant effect on whether or not they chose fertility preservation.The specific modeling is shown in Table\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eBinary logistic regression analysis with FP as the dependent variable.\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"9\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eWald\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eExp(B)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colspan=\"2\" nameend=\"c9\" namest=\"c8\"\u003e\u003cp\u003e95%CI\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003eLow\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u003cp\u003eUp\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\" morerows=\"28\" rowspan=\"29\"\u003e\u003cp\u003eStep 1a\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePlace of residence\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.961\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePlace of residence(Urban)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.688\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.385\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.195\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.074\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.503\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.236\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.069\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003ePlace of residence(Rural)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.075\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.462\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.407\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.138\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.845\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eOccupation (Employed)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.491\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.401\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.505\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.612\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.279\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.341\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamily monthly wage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.122\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.547\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamily monthly wage\u003c/p\u003e\u003cp\u003e(\u0026le;\u0026thinsp;1000CNY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.265\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.243\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.622\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.767\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.267\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.202\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamily monthly wage\u003c/p\u003e\u003cp\u003e(1001-5000CNY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.659\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.601\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.202\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.273\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.517\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.159\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.681\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFamily monthly wage (5001-10000CNY)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.837\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.765\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.184\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.433\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.126\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.489\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eEducation level\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.063\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.786\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eJunior high school or Below\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.291\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.474\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.379\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.538\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.747\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.295\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.89\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eHigh school or technical\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.318\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.458\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.481\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.728\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.297\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.785\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eAssociate Degree\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.505\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.011\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.917\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.054\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.391\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.84\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarital status\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e6.416\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMarried\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.642\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.411\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.443\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.901\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.849\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e4.254\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003esingle/divorced/widowed\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-2.551\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.342\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.613\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.057\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.078\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.083\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of offspring\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.193\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of offspring(0)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.711\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.585\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.478\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.036\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.647\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e6.402\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eNumber of offspring(1)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.361\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.488\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.547\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.697\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.268\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.815\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eFertility desire\u003c/p\u003e\u003cp\u003e(Yes)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.851\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.434\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.834\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.999\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e5.484\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eMedical insurance(Yes)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.844\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.701\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.451\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.228\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e2.325\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.589\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e9.178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBreast cancer stage\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.664\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.198\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBreast cancer stage(I)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.118\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.557\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.045\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.833\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.889\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.298\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.649\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBreast cancer stage(II)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.317\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.521\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.543\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.729\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.263\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e2.021\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eBreast cancer stage(III)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-1.224\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.651\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3.532\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.294\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.082\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.054\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDCS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.708\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.191\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.021\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.99\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.052\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDSE\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.965\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.326\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.987\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.962\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eDRS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.052\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.014\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e14.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e1.053\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e1.025\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e1.082\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eRCACS\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e-0.051\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.016\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.001\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e0.95\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u003cp\u003e0.921\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c9\"\u003e\u003cp\u003e0.981\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003eConstant\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.341\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.532\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.766\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.381\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u003cp\u003e3.822\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eOur study investigate that the relationship between the psychological experience of fertility concerns and decision-making in two groups of breast cancer patients who took FP and those who did not.In order to resolve the issue, binary logistic regression analysis was employed to examine the correlation between the two groups.We reached two main conclusions.On the one hand,our study confirmed that fertility concerns is prevalent in young female breast cancer patients with fertility intention and that their level of fertility concerns is higher than that of breast cancer patients who did not take FP. On the other hand,our findings also show that Patients who elected to opt for FP exhibited elevated levels of decision regret and decision conflict.\u003c/p\u003e\u003cp\u003ePatients who chose FP had stronger fertility intentions and higher fertility concerns.Armuand et alreported that failure to achieve fertility aspirations after cancer treatment may lead to the deterioration of patients\u0026rsquo; mental health[23].Specifically,failure to achieve fertility aspirations may increase patients\u0026rsquo; fertility concerns. In contrast to the hypothesis, FP choices reduces fertility concerns.Based on the study results, fertility concerns were high in both groups, and the difference between them was not statistically significant.This implies that the decision to opt for FP may not be significantly affected by a patient's degree of fertility concern.On the one hand,the relationship between fertility protection and fertility concerns may be influenced by a combination of factors rather than a simple linear relationship.So the result of their correlation analysis showed no significant relationship.On the other hand, it may also be limited by scale dimensions - for example, the RCACS does not distinguish between \u0026lsquo;short-term concerns\u0026rsquo; (e.g., immediate ovarian damage from treatment) and \u0026lsquo;long-term concerns\u0026rsquo;(e.g., FP success).Therefore, it is not possible to confirm whether the absence of a statistically significant difference in fertility concerns between the two groups is attributable to confounding. This is due to the fact that the two groups exhibited differences in both long-term and short-term concerns.At present, the majority of cancer patients have limited knowledge of FP[24, 25].Consequently, most patients are skeptical about the effectiveness of FP.According to the perceived benefits in the Health Belief Model[26], the degree to which patients expect FP to be successful also influences their decision[27].Moreover,the long-term benefits of FP are underestimated.Since cancer patients believe that their top priority is to overcome cancer, they may be more concentrated on current cancer treatments[28, 29].Conversely, the benefits of fertility protection are regarded as long-term, so the immediate benefits of fertility protection are not apparent.Therefore,in clinical work,it suggests that clinics need to strengthen \u0026lsquo;expectation management\u0026rsquo; in FP counselling to avoid patients' subsequent psychological fallout due to overly high expectations.\u003c/p\u003e\u003cp\u003eA considerable number of breast cancer patients encounter difficulties in making decisions regarding FP following cancer diagnosis, as evidenced by patients who chose FP had higher levels of decision regret and decision conflict.This hypothesis was based upon previous research showing that young adult breast cancer patients who received fertility counseling prior to beginning treatment had increased reproductive concerns relative to patients who did not receive counseling[30].Moreover,most of people who chose FP were received fertility counseling.However,there are study show that regret scores will decrease as fertility information adequacy increases[31].In our research,patients who chose FP had higher decision regret scores than those who did not.In other words,this suggests that fertility counselling for patients opting for FP is not adequate.Drawing on the Self-efficacy Theory [32], the higher decision regret in the FP group may stem from the mismatch between patients\u0026rsquo; optimistic expectations of FP success and the reality of potential ovarian failure after treatment. This aligns with Brehaut et al.\u0026rsquo;s finding that unmet expectations significantly drive post-decision regret in medical contexts[21].Limited knowledge regarding the FP process, success rates, and financial implications may aggravate decision-making conflicts among patients[33].This conflict may lead patients to regret their decisions later, especially when they discover better alternatives[34].Furthermore,the findings revealed statistically significant differences in decision conflict and decision regret between patients who chose fertility protection and those who did not.Notably, patients who chose FP exhibited higher levels of decision conflict and decision regret.It is hypothesized that patients who choose FP have higher expectations for future fertility[35].Once treatment leads to ovarian failure, the likelihood of regret increases.Patients may feel that although they have undergone FP procedures, they have not actually achieved FP.Consequently, they regret their previous decision.For patients, particularly female patients, cancer treatment itself poses a significant financial burden[36].It also adds to their feelings of regret.Therefore, clinical nursing practitioners should pay attention to the psychological and intellectual aspects support that they can provide to patients, especially through participating in enough fertility counseling, which can help alleviate the decision regret of young breast cancer patients and psychological burden.Clinicians should adopt a three-phase counseling model: (1) pre-diagnosis: provide simplified FP brochures in both Mandarin and local dialects; (2) treatment planning: involve spouses in shared decision-making sessions to address familial concerns; (3) post-decision: offer monthly group counseling for FP recipients to manage anxiety about treatment outcomes.\u003c/p\u003e\u003cp\u003eMoreover,the negative emotions of breast cancer patients may influence their decisions regarding FP.Previous studies by Catherine B et al. have demonstrated that negative emotions in young breast cancer patients influence their treatment decisions[16].However, no prior studies have explored the direct relationship between the choice of FP in cancer patients and their fertility concerns.Meanwhile, this study offers a novel perspective.Our study has refined this point.We compared data from cross-sectional studies of patients who chose FP with those who did not.We found that current cancer patients have low satisfaction levels regarding FP decision-making.This study revealed that patients' educational attainment, economic status, marital status, and fertility intentions were positively correlated with the choice of FP,consistent with previous findings. In the Chinese context, FP decisions are often influenced by familial pressures to maintain generational continuity[5]. The high proportion of married patients (69.5%) in our sample suggests that spousal attitudes and parental expectations may implicitly pressure women to choose FP, even when they have reservations, potentially exacerbating decision conflict.Adequate fertility counselling has been demonstrated to reduce patient decision-making regrets and increase decision-making satisfaction[31].Greater awareness of fertility preservation helps patients to understand its benefits and enables them to make the most rational decisions.Therefore, clinical care practitioners not only need to readily answer patients\u0026lsquo;confusion about their knowledge of FP, but also focus on and enhance fertility counselling for breast cancer patients, which may be an effective strategy to mitigate patients\u0026rsquo; decision-making regrets and improve decision-making outcomes.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eFemale breast cancer of childbearing in China experience moderate levels of fertility concern.Fertility concern is negative factors against FP choices.High levels of fertility concern contribute to a greater preference for no FP among reproductive age breast cancer patients to withstand decision conflict, therefore the lower their decision-making dilemma.Therefore, multiple strategies should be explored by hospitals to reduce fertility concern, commencing with an objective assessment of the decision-making dilemma faced by young breast cancer patients, which is critical for enhancing their fertility preservation (FP) choices.Especially for patients with high level of fertility concern, clinical nursing practitioners should help make FP decision.Specifically, clinical nursing practitioners should guide patients to make FP decision with a reasonable choice to reduce their decision conflict. Furthermore, research should continue to explore the modifiable risk and protective factors associated with decision conflict, which will help promote mental health and improve the quality of life among breast cancer survivors in China.Given that FP is currently uninsured in most Chinese provinces, advocating for its inclusion in public healthcare policies or establishing hospital-based financial aid programs could mitigate the economic barriers highlighted in this study.\u003c/p\u003e\u003cp\u003eLimitations\u003c/p\u003e\u003cp\u003eThis study has several limitations. First, the cross-sectional design precludes causal inference between FP choices, fertility concern, and psychological variables, necessitating longitudinal follow-up. Second, the sample from three Hunan Province hospitals may limit generalizability; multi-regional or international sampling could enhance validity. Third, the regression model did not account for contextual factors (e.g., physician recommendations, hospital FP services) or family-level influences (e.g., spousal attitudes, traditional childbearing values), which may improve model fit if incorporated. Additionally, slight demographic imbalances in the sample highlight the need for more balanced sampling in future research. Finally, while quantitative methods captured fertility concern, qualitative approaches could deeper explore how cultural values shape decision-making, a direction for future work.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe study was approved by the medical ethics committee of the University of South China (approval number: 2023NHHL047).The researcher apprised all eligible patients of the objective of this study and ensured that their information would remain confidential and solely utilized for this study.Consent was acquired by filling out a form of agreement and a self-reported questionnaire. If, during the course of the study, the subject does not wish to continue in the study, they may withdraw without giving a reason.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors thank the participants of this study for their time and dedication.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by Hunan Provincial Appraisal Committee for Social Science Achievements (grant number XSP2023JYZ030).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthica\u003c/strong\u003e\u003cstrong\u003el approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll procedures performed in studies involving human participants were in accordance with the ethical standards of the institutional and/or national research committee and with the 1964 Helsinki Declaration and its later amendments or comparable ethical standards. The study was approved by the Medical Ethics Committee of University of South China(approval number:2023NHHL047).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInform\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll participants provided written informed consent before recruitment.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eYujiao Li, Wangmu Lazhen and Yanhui Zhou contributed to the study conception and design. Material preparation were performed by Yujiao Li, Wangmu Lazhen,Can Gu,Ling Zhao, Junrui Chen,Qiao Deng.Data collection were performed by Yujiao Li, Wangmu Lazhen, Qifan Ren, Xiuzhen Luo, Hongxia Zhou,Susan Qian,Huichang Tan and Shuying Xie under the supervision of Yanhui Zhou.Data analysis were performed by Yujiao Li and Wangmu Lazhen. The first draft of the manuscript was written by Yujiao Li and Wangmu Lazhen. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Data availability the datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request. Interested stakeholders may communicate with the corresponding author (Yanhui Zhou) to access de-identified datasets.\u0026nbsp;\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eWu Y, He S, Cao M, Teng Y, Li Q, Tan N, Wang J, Zuo T, Li T, Zheng Y\u003cem\u003e et al\u003c/em\u003e. (2024). Comparative analysis of cancer statistics in China and the United States in 2024. \u003cem\u003eChin Med J (Engl)\u003c/em\u003e,\u003cem\u003e 137\u003c/em\u003e(24), 3093-3100. https://doi.org/10.1097/cm9.0000000000003442\u003c/li\u003e\n\u003cli\u003eHuang Z, Wang J, Liu H, Wang B, Qi M, Lyu Z, Liu H. (2024). 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Financial toxicity and its associated patient and cancer factors among women with breast cancer in China. \u003cem\u003eJournal of Clinical Oncology\u003c/em\u003e,\u003cem\u003e 38\u003c/em\u003e. https://doi.org/10.1200/jco.2020.38.15_suppl.e19402 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breast cancer, Fertility preservation, Fertility concern, Decision-making, Decision regret","lastPublishedDoi":"10.21203/rs.3.rs-7011387/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7011387/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eBreast cancer (BC) incidence in adults younger than 45 years is steadily increasing in China, raising concerns about the long-term quality of life for young survivors. As many of these patients are of reproductive age, treatment-related gonadotoxicity poses a significant threat to their future fertility.While fertility preservation (FP) options such as egg/embryo freezing or ovarian suppression exist, FP decision-making in BC patients remains inconsistent. Factors such as limited awareness, time constraints during cancer treatment, and conflicting medical advice may contribute to this variability. Understanding how fertility concerns influence FP choices is critical to improving patient-centered care.\u003c/p\u003e\u003ch2\u003ePurpose\u003c/h2\u003e\u003cp\u003eThis study examines the association between fertility preservation choices and fertility-related concerns in BC patients, aiming to identify key factors that shape FP decision-making.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eFrom February 2024 to June 2024,279 female BC patients were selected from the cancer centers of 3 tertiary Level A general hospitals in Hengyang cities of Hunan Province.The patients completed the Chinese version of the Reproductive Concerns After Cancer Scale(RCACS), the Decision Regret Scale(DRS), the Decision Conflict Scale(DCS), and the Decision Self-Efficacy Scale(DES).A binary logistic regression model was used to explore the relationships among FP choice,decision-making and fertility concerns.\u003c/p\u003e\u003ch2\u003eResult\u003c/h2\u003e\u003cp\u003eCorrelation analyses revealed significant correlations( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.01 ) with decision regret, decision conflict, and self-efficacy, but non-significant correlations( \u003cem\u003ep\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.306 ) with fertility concerns.However, binary logistic regression showed that FP choices were statistically significantly associated with decision regret (OR\u0026thinsp;=\u0026thinsp;1.053, 95%CI 1.025\u0026ndash;1.082, \u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) as well as fertility concerns (OR\u0026thinsp;=\u0026thinsp;0.95, 95%CI 0.921\u0026ndash;0.981,\u003cem\u003ep\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).This suggests that the relationship between fertility protection and fertility concerns may be influenced by a combination of factors rather than a simple linear relationship.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eFertility preservation choices in young breast cancer patients are significantly influenced by decision psychological experience and fertility concerns.\u003c/p\u003e","manuscriptTitle":"Fertility Preservation,fertility concerns and Decision-Making in Breast Cancer Patients of Childbearing Age: A Cross-sectional Study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-08-18 07:59:14","doi":"10.21203/rs.3.rs-7011387/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"84fb3071-631a-42bf-a634-e72a48556376","owner":[],"postedDate":"August 18th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2026-01-22T05:25:19+00:00","versionOfRecord":[],"versionCreatedAt":"2025-08-18 07:59:14","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7011387","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7011387","identity":"rs-7011387","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}