Prevalence and risk factors of self-reported financial toxicity in cancer survivors: A systematic review and meta-analysis

Prevalence and risk factors of self-reported financial toxicity in cancer survivors: A systematic review and meta-analysis | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence and risk factors of self-reported financial toxicity in cancer survivors: A systematic review and meta-analysis QingHua Jiang, Jiang Hua, Mou Wenxuan, Jiang Luxi, Lyu Jianxia, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-1383681/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: Similar to the side effects of cancer treatment，financial toxicity can affect the quality of life of patients, which has attracted increasing attention in the field of oncology. Despite the fact that the estimated prevalence and risk factors of financial toxicity are widely reported, these results have not been synthesized. Objectives: This review aimed to systematically assess the prevalence and risk factors of self-reported financial toxicity. Design: Systematic review and meta-analysis. Data Sources: A computer search of English literature using the database of PubMed, EMBASE, Web of Science, PsycINFO, CHINAHL, and reference list of the included articles between 2010 and September 2021. The observational studies that reported the prevalence or risk factors of financial toxcity used subjective measures will be included. Methods: A systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The risk of bias was assessed by the NIH observational cohort and cross-sectional study quality assessment tool. The data were extracted by two reviewers and listed in a descriptive table for meta-analysis. Results: In the 22 studies available for the meta-analysis, the pooled prevalence of financial toxicity was estimated to be 45% (95% CI: 38% to 53%, I 2 = 97.3%, P < 0.001), which was based on a random-effects model. The pooled analysis identified 9 potential risk factors of financial toxicity(7 in β and 8 in OR) : low income (OR = 2.48, 95% CI: 1.72 to 3.24, I 2 =3.1%, P < 0.001), greater annual OOP(β = -4.26, 95% CI: -6.95 to -1.57, I 2 =0%, P=0.002), younger age(OR = 2.05, 95% CI: 1.56 to 2.54, I 2 =0%, P < 0.001), no private insurance(OR = 1.69, 95% CI: 1.02 to 2.37, I 2 =0%, P < 0.001), unmarried(OR = 1.10, 95% CI: 0.95 to 1.25, I 2 =53,3%, P < 0.001), non-white(OR = 1.59, 95% CI: 1.33 to 1.85, I 2 =0%, P < 0.001), advanced cancer(β = -4.74, 95% CI: -6.90 to -2.57, I 2 =0%, P < 0.001), unemployed(β = -2.90, 95% CI: -5.71 to -0.63, I 2 =75,7%, P < 0.001), more recent diagnosis(OR = 1.31, 95% CI: 1.04 to 1.57, I 2 =0%, P < 0.001). Conclusion This systematic review found a pooled prevalence of self-reported financial toxicity of 45%. Low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis constituted risk factors for self-reported financial toxicity. The Research on risk factors for financial toxicity can provide a theoretical basis for nursing staff to evaluate and intervene in the financial toxicity among cancer survivors. Financial stress Prevalence Risk factors Cancer survivor Review Figures Figure 1 Figure 2 Figure 3 What Is Already Known About The Topic? Financial toxicity is closely related to cancer treatment ,which negatively impacts the quality of life, mental health, and treatment adherence of cancer survivors. The measures of FT varied widely among previous studies, categorized as monetary measures, objective measures, and subjective measures, and most were not validated. A large number of observational studies using subjective measures have reported the estimated prevalence and risk factors of financial toxicity , but the related systematic review is not available. What this paper adds? This paper provides the estimates of the pooled prevalence of self-reported financial toxicity, which was 45% (95% CI: 48%-56%). Low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis are associated with self-reported financial toxicity. 1. Introduction Cancer treatment is a complex process, which often requires the use of innovative treatment and drugs. With the advancement of the medical level, especially the development of precision radiotherapy, widespread used of targeted therapy and immunotherapy, the clinical efficacy of patients has been significantly improved 1 – 3 . However, the new treatment not only improve the prognosis of patients, but also bring heavy financial burdens and side effects, which have a negative impact on the long-term quality of life of cancer survivors 4 – 7 . Similar to the side effects of cancer treatment, financial toxicity is defined as: "The subjective burden and objective financial distress of cancer patients after treatment with innovative drugs and accompanying health services. 2 , 8 The measures of FT varied widely among previous studies, categorized as monetary measures, objective measures, and subjective measures, and most were not validated 9 . In addition, the use of survey tools lacks consistency 9 – 11 , prior studies suggested that FT should be measured using patient-reported outcomes(PROMs)to reflect cancer survivors’ thoughts, complaints and opinions that any numbers or observers cannot 10 – 11 . However, the development and verification of current PROMs vary greatly, and none of them are considered the gold standard. Several instruments have been developed, validated, and intended for self-reported financial toxicity in cancer patients: Breast Cancer Finances Survey Inventory(BCFS) 12 – 13 , Socioeconomic Wellbeing scale(SWS) 14 , the InCharge Financial Distress/Financial Well-Being Scale(InCharge/FWS) 15 , the Financial Distress Questionnaire(FDQ) 16 , Financial Index of Toxicity(FIT) 17 , and the Comprehensive Score for financial Toxicity (COST) 18 – 19 . Among all measures, the COST tools was the most commonly used survey tools and was developed by de Souza 18 to meet the financial toxicity investigations of cancer patients in the United States, which has been verified in many countries around the world, including China 20 , India 21 , Italy 22 , Australia 23 , Japan 24 , etc., and has achieved good reliability and validity.Based on differences in health related quality of life(HRQoL), analogous to the NCI-Common Terminology Criteria for Adverse Events, the COST-PROM grading system was developed by de Souza with 4 FT grades (G) 25 : Grade0, no FT, COST score ≥ 26 ; Grade1, mild FT:COST score ≥ 14–26; Grade2, moderate FT: score > 0–14; and Grade3, severe FT: COST score = 0. To date, although there have been a large number of observational studies on financial toxicity, PROMs have been applied to the investigation of financial toxicity, and the estimated prevalence and risk factors of financial toxicity are widely reported, these results have not been synthesized. Existing evidence about the risk factors of FT are inconsistent varied by cancer type, survey tools, population and health insurance system, which was lack of comparison between the results of multiple studies. The aim of this systematic review is two-fold: 1. to determine a pooled prevalence of self-reported financial toxicity and explore its potential risk factors, and 2. to provide evidence-based recommendations for financial toxicity towards ensuring improved the awareness and measures of self-reported financial toxicity for nurses. 2. Material 2.1. Protocol and Registration This review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement 26 and is registered in PROSPERO (CRD42021254332). 2.2. Literature search A comprehensive search of English literature using the database of PubMed, EMBASE, Web of science, PsycINFO, CHINAHL. Screen the reference list of the included articles to identify any other eligible studies. The search strategies were performed through a combination of the Medical Subject Heading (MESH)and free words. The following Mesh terms and free words were include: 'oncology', 'neoplasms*', 'cancer survivors', 'cancer[MeSH]', 'cost', 'expense', 'out-of-pocket', 'financial hardship', 'financial burden', 'financial stress[MeSH]', 'economic burden', 'financial toxicity', 'Prevalence[MeSH]','Epidemiology[MeSH Terms]', 'Risk Factors[Mesh]', 'Health Risk Behaviors[Mesh]', 'Observational Studies[MeSH Terms]'. Search terms and strategy are delineated in (Appendix figure A.1). We use the Boolean operators "OR" and "AND" between the groups. The publication year of these articles was limited to January 1, 2010 to the second week of September 2021, and only full-text original research articles published in English are considered. All search results are downloaded and imported directly into EndNote, versionX9. 2.3. Eligibility Criteria The inclusion criteria were as follows: (1) the type of studies had to be observational; (2) study subjects were patients with cancers of any disease site and stage; (3) age > 18 years old; (4) prevalence or risk factors of self-reported financial toxicity was reported; (5) study must use subjective measures.The exclusion criteria are: (1) the sample size was less than 40; (2) lack of reliability and validity of survey tools. (3) studies contained incomplete data. 2.4. Data extraction The data extraction was completed by two reviewers, who screened the title and abstract of the literature to identify articles that might meet the inclusion criteria. The reasons for the exclusion were recorded, and the differences in the process were discussed until an agreement was reached. Subsequently, a researcher extracted data from all eligible full-text articles, including publication year, main author, country, study design, FT assessment, HRQOL measurement, statistical methods. and main findings. Another reviewer checked the completeness and accuracy of the information. The entire literature screening process is carried out independently by two researchers. If there were any disagreements, they will be resolved through discussion and consensus. When the discussion still fails to resolve the differences, it will be handed over to a third party for judgment. The PRISMA flowchart is displayed in (Fig. 1 ). 2.5. Quality appraisal Two reviewers independently using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies 27 (Appendix table A.1) to ascertain the risk of bias and overall study quality (the individual study was rated “good” if it met all applicable criteria, and if it met most of the criteria, then rated as "fair", and if it met a few criteria, rated as "poor"). This tool has a total of 14 questions related to the risk of bias in the study and is designed to help researchers focus on the key concepts for evaluating the internal validity of a study 27 . 2.6. Data synthesis For analysis, the results extracted from the included studies were input into Stata 15.0 software package. We then conducted several meta-analyses of identified studies to pooled prevalence and risk factors of self-reported financial toxicity. The proportions of patients with financial toxicity were extracted from all included studies in order to calculate the pooled prevalence. The risk estimates (β and OR) and associated 95% CIs were extracted from included studies to assess the risk factors of self-reported financial toxicity. We pooled the coefficient(β) of Multivariate linear regression model and the Odd ritio(OR )value in the Logistic regression. The degree of heterogeneity was tested by Cochrane’s Q test (P value) and the I 2 statistic 28 . We set the I 2 values as 25%, 50%, and 75%, indicating low, medium, and high heterogeneity, respectively. When no significant heterogeneity was detected (I 2 ≤ 50), the fixed-effects model was used for pooled prevalence and risk estimates, otherwise the random-effects model was used 28 . We also employed funnel plot asymmetry to detect the potential publication bias. An Egger's regression was applied to test the funnel plot symmetry 29 . Finally, the sensitivity analyses was performed to test the robustness of our results. The data of included studies were divided into subgroups according to the demographic characteristics and clinical characteristics. Because some subgroup analyses included very few studies, we only conducted sensitivity analyses for the meta-analyses that included more than two studies. All statistical tests were two-sided, and P < 0.05 was considered statistically significant. 3. Results 3.1. Study Selection In total, 4913 related citations (PubMed: 2559, EMBASE: 746, PsycINFO: 160, CINAHL: 203，Web of science:1245) were identified and qualified through electronic database search, of which 1167 were duplicates. After screening titles and abstracts and removing duplicate references, 402 articles were selected on the basis of inclusion criteria.. Of these studies, 153 were excluded because of irrelevant results , wrong populations , wrong disease, use objective or monetary measure, sample size smaller than 50, qualitative study, and duplicate reporting. A total of 33 studies 30-62 were utilized for the meta-analysis.The selection process for the study is shown in the PRISMA flow chart (Fig 1). 3.2. Characteristics of the included primary studies The characteristics of the 33 studies are summarized in Table 1. 3.3. Prevalence of self-reported financial toxicity In the 22 studies available for the meta-analysis, the pooled prevalence of financial toxicity was estimated to be 45% (95% CI: 38% to 53%, I 2 = 97.3%, P < 0.0001), which was based on a random-effects model. Among them, the mild financial toxicity(grade1) was estimated to be 42% (95% CI: 28% to 55%, I 2 = 95.9%, P < 0.0001), the moderate financial toxicity(grade2) was estimated to be 17% (95% CI: 13% to 22%, I 2 = 82.9%, P < 0.0001), the severe financial toxicity(grade3) was estimated to be 1% (95% CI: 0% to 1%, I 2 = 0%, P =0.475)(Fig 2). 3.4. Subgroup analyses of self-reported financial toxicity The subgroup analysis of financial toxicity was divided into two parts: demographic characteristics and clinical characteristics. In demographic characteristics, we stratified prevalence of financial toxicity according to gender, age, race, marital status, employment status, education level, health insurance, and country. In clinical characteristics, we stratified prevalence of financial toxicity according to cancer type, cancer stage, treatment, and survey intrument. The estimated pooled results obtained in subgroup analyses are shown in Table2. 3.5 Risk factors A total of 28 studies reported the risk factors associated with financial toxicity (additional details in Appendix table A.2). The pooled analysis identified 9 potential risk factors of financial toxicity(7 in β and 8 in OR) : low income, younger age, no private insurance, greater annual OOP, non-white, advanced cancer, unemployed, and more recent diagnosis, unmarried(Appendix figure A.2). The results of risk factors analysis are listed in Table 3. 3.6. Publication bias Funnel plot asymmetry (Fig 3) revealed evidence of publication bias between study heterogeneity. Results of Egger’s test further confirmed the funnel plot asymmetry. 4. Discussion This study systematically reviewed 33 studies, which involved a total of 13,025 cancer survivors. The overall prevalence of financial toxicity was 45%, and most of patients was in Grade1 stage, which showed that the problem of financial toxicity urgently needs to be resolved. Risk factors related to financial toxicity include: low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis(Table 3 ). Since most of the included literature comes from the United States, the result may more reflect the pooled prevalence of financial toxicity in the United States(pooled prevalence: 44%, 95%CI: 35%-52%)(Appendix Figure A.3). In a systematic review of the financial burden of cancer patients in the United States, Smith et al. reported that the sample-weighted prevalence was 49% (95% CI, 41–56%) of patients with cancer with any financial burden 63 . Indeed, there were certain differences of pooled prevalence between this systematic review and Smith et al.. This discrepancy may be due to the fact that Smith et al.’ results were based on a wider range of measures about financial burden, including subjective measures, objective measures and monetary measures, while the measures of our study focuses on PROMs. In this systematic review, all self-reported financial toxicity of patients was measured by subjective intrument, which was used scales or questionnaires to explore patients' subjective feelings about their own financial burden. This review mainly include 5 survey tools, most of the included studies used the COST-PROM. After data synthesis, we observed that there are big differences between survey tools. In the study using COST tool, the pooled prevalence of financial toxicity was 51%(95% CI: 49–52%, I 2 = 95.7%, P < 0.0001). However, the studies using other tools to measure financial toxicity, the pooled prevalence of financial toxicity was 27%(95% CI: 25–29%, I 2 = 75.1%, P < 0.0001). This disparity may reflect the fact that COST tool and other tools have certain differences in specificity and sensitivity, which leads to different pooled prevalence. Currently, the PROMs used to assess self-reported financial toxicity are lacking consistency on a global scale, and the data on self-reported financial toxicity has not yet been quantified in a standardized way 9 – 11 . In the long term, a lack of standardization in measurement can hinder the choice of PROMs for subsequent cross-sectional surveys and comparisons across studies. Consequently, based on this result, the criteria for the measure of financial toxicity needs to be further improved and reached a consensus. Clinicians and nurses should strengthen multidisciplinary cooperation to improve the sensitivity and specificity of economic toxicity assessment tools, and verify them in various cancer types, improve their universality, and reach agreement in clinical applications. It is suggested that multidisciplinary collaboration with the clinicians, nurses and researchers jointly strive to define the criteria to assess financial toxicity and improve its sensitivity and specificity. The criteria of survey intrument must be refined, verifying them in various cancer types, and their consistent application with high sensitivity and specificity must be promoted in the future. In the subgroup analysis on the demographic characteristics of patients, a stratified analysis has conducted among all cancer survivors, including gender, age, race, country, marital status, employment status, education level, and medical insurance. The age-stratified analysis indicated that the pooled prevalence of self-reported financial toxicity was higher in the younger than in the older patients. This discrepancy may be due to younger patients saving less and having a higher burden of living 64 – 65 . The present meta-analysis has demonstrated that the pooled prevalence of self-reported financial toxicity varies with the difference of races. Compared with other races, the pooled prevalence of financial toxicity of white people was the lowest. The pooled prevalence of financial toxicity of patients with supplemental insurance was obviously lower. This finding was not unexpected, because better medical insurance means that patients pay lower out-of-pocket expenses and less financial burden they need to bear during the treatment process 66 – 68 . This systematic review further validated the findings of Alison and Floortje et al. that unemployed patients have a higher risk of financial toxicity 69 – 70 . The results of their studies showed that increased risk of financial toxicity was associated with both unemployment, changed or reduced employment, lost days at work, or poor work ability 69 – 70 . In addition, we compared the prevalence of self-reported financial toxicity between developing and developed countries, and the results showed that the prevalence of financial toxicity in developed countries was lower. This result needs to be further verified because we incorporated less studies from developing countries. It is undeniable that there are differences in healthcare systems, economic level and cultural background between developed and developing countries. However, most of the literature on financial toxicity were concentrated on developed countries, so more observational studies are needed to supple in developing countries to fill this gap in our knowledge. Nevertheless, in our limited literature review, financial toxicity specific survey tools, such as COST tool, are rarely used in developing countries. Developing countries need to do more to recognize the challenges associated with financial toxicity. In a subgroup analysis regarding the clinical characteristics of the patients, we discussed the gender, type of cancer, and stage of cancer, in a stratified analysis. Given the wide variation in treatment and medication across cancers, patients' out-of-pocket costs varied. However, we did not find differences in the pooled prevalence of financial toxicity among several cancer types, such as breast cancer, renal cell carcinoma, head and neck cancer(HNC), and gynecologic cancer(Appendix Figure A.3). Despite lower prevalence of financial toxicity was observed in lung and urologic cancers (29% and 11%), this result needs to be further validated due to limited included literature and sample size. For example, in a retrospective study of the Medical Expenditure Panel Survey (MEPS), HNC patients had disproportionately higher financial burden in the form of higher total and relative OOP expenses compared to other cancers, because HNC patients were more often of a minority race/ethnicity, poor, less educated, publicly insured, and of lower health status 71 . Consistent with the results of risk factor analysis, more advanced cancer stages have a higher prevalence of financial toxicity. The treatment of advanced cancer is more complicated because it are more likely to require a multimodal treatment regimen (i.e., targeted therapy and radiation therapy in addition to surgery) and novel chemotherapeutic agents72. Similarly, in the comparison of different treatment, patients who have received targeted therapy have a higher prevalence of financial toxicity, and patients who receive surgery alone have the lowest prevalence of financial toxicity( ). In the included prospective studies 38 , 40 , 46 , 50 , 52 , 53 , we focused on the question of whether self-reported financial toxicity will change dynamically over time. The results reported by Liang et al.40 and Stone et al. 50 conducted that the severity of financial toxicity will decrease over time. However, Friedes et al. 52 reported that FT was pervasive from diagnosis through the first 6 months of cancer therapy. The patient's out-of-pocket costs gradually increased when the length of stay was prolonged, which may be one of the reasons why the patient's self-reported financial toxicity gradually increased over time. However, some patients may adopt coping strategies at the beginning of treatment (e.g., via the Internet or by asking their physicians) to anticipate their potential future treatment costs in advance; some patients may be unaware of the medical costs they are spending, for example, when their children are paying for their medical expenses. Therefore, the discrepancy in information acquisition between patients should be controlled in subsequent longitudinal studies to ensure consistency at baseline. To the best of our knowledge, this systematic review is the first to provide both the estimate of the pooled prevalence of self-reported financial toxicity and an assessment of risk factors associated with this condition. The current study further confirms the influence of sociodemographic factors (e.g., age, gender, employment status, health insurance, etc.) and clinical factors (cancer stage, treatment modality, time to disease diagnosis, etc.) on financial toxicity when measured by PROMs. In future studies, we need to identify differences in risk factors for financial toxicity between different countries given different medical backgrounds and economic levels. At the same time, it is necessary to explore the differences in the prevalence of financial toxicity among different cancer types in consideration of the differences in treatment, drugs, and medical expenses. Despite there is currently no gold standard for survey tools related financial toxicity, COST-PROM has been demonstrated to have good generalizability and specificity. Oncology nurses should play a vital role in the assessment of a patient with financial toxicity, so as to improve the quality of life of cancer survivors. Therefore, should be advocated nurses actively apply COST-PROM to clinical work, adopt a corresponding nursing management model for patients according to the COST grading system, providing financial information assistance and psychological interventions. 5. Limitations It is noteworthy that some of the potential limitations cannot be ignored. Firstly, limited by cross-sectional studies, we found high or moderate heterogeneities in most of the subgroup meta-analyses, although less heterogeneity was found in some subgroups. These findings indicate that the heterogeneity of included studies may also be affected by other factors, such as grading criteria. Therefore, further meta-analyses are necessary to explore the sources of heterogeneity as more original studies will be conducted in the future. Secondly, the language of included studies were limited in English, the exclusion of works published in other languages limited the comprehensiveness of the literature included. Future studies will need to overcome these limitations and assess the prevalence and risk factors of financial toxicity in a more comprehensive manner. 6. Conclusion In summary, this systematic review found a pooled prevalence of self-reported financial toxicity of 45%. Low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis constituted risk factors for self-reported financial toxicity. Such high prevalence indicates an urgent need for ongoing efforts to develop interventions to respond to the adverse impact of financial burdens in patients with cancer. Addressing the problem of cancer-related financial toxicity will require joint efforts at the policy, provider, health system and patient levels. The Research on risk factors for financial toxicity can provide a theoretical basis for nursing staff to evaluate and intervene in the financial toxicity in cancer survivors. Declarations Funding This study was funded by the 2020 Key R&D Project of Social Development of Sichuan Provincial Department of Science and Technology. Conflicts of interest/Competing interests The authors declare no conflict of interest. Availability of supporting data Not applicable Authors' contributions Hua Jiang and QinghuaJiang conceived the idea and registered the protocol in PROSPERO; Ying Liu and Yu Zeng were responsible for establishing and performing the systematic literature search; LX Jiang and Hua Jiang were responsible for the quality of assessment; Jianxia Lyu and Aiping Hu performed the Data synthesis and designed tables and figures; Wenxuan Mou, Jianxia Lyu, LX Jiang, and Hua Jiang constituted the writing committee. Ethical Approval and Consent to participate Not applicable Consent for publication The authors declare their consent to publish this work Acknowledgements Not applicable References Tran, G., & Zafar, S. Y. (2018). Financial toxicity and implications for cancer care in the era of molecular and immune therapies. Annals of translational medicine , 6 (9), 166. https://doi.org/10.21037/atm.2018.03.28 Zafar, S. Y., & Abernethy, A. P. (2013). 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Are survivors who report cancer-related financial problems more likely to forgo or delay medical care?. Cancer , 119 (20), 3710–3717. https://doi.org/10.1002/cncr.28262 Tables Table 1 Characteristics of included studies First author Publication Years Country Study design Simple size Age (SD) Male(%) Survey instrument Cancer type Prevalence (%) Risk factors type (High FT) Ezeife et al. 30 2018 Canada Cross-sectional 200 64.3 (10.9) 44.25 COST Lung Not report D, S Offodile et al. 31 2021 United States Cross-sectional 571 58.0 (12.2) 0 COST Breast 51.3% S, T Huntington et al. 32 2015 United States Cross-sectional 100 64.1 (9.8) 47 COST Multiple myeloma 50.0% D, S Staehler et al. 33 2020 United States Cross-sectional 539 55.0 (9.3) 39 COST Renal cell carcinoma 59.0% D, S, T Marques et al. 34 2021 China Cross-sectional 640 59.9 (11.1) 35.8 COST Any cancer site 42.8% - Mejri et al. 35 2021 Tunisia Cross-sectional 179 52.0 (11.4) 29.1 COST Any cancer site 80.0% S, T Jing et al. 36 2020 China Cross-sectional 166 51.7 (10.8) 0 COST Breast 50% D, S, T LaRocca et al. 37 2020 United States Cross-sectional 1027 Not report 51.7 Support Screen Gastrointestinal Not report D, S Table 1 Characteristics of included studies(contined ) First author Publication Years Country Study design Simple size Age (SD) Male(%) Survey instrument Cancer type Prevalence (%) Risk factors (High FT) Palmer et al. 38 2018 United States Prospective 157 Not report 52.2 COST Any cancer site 21.7% D, S, T Huey et al. 39 2021 United States Cross-sectional 213 Not report 41.0 COST Any cancer site 71% D, S Liang et al. 40 2021 United States Prospective 121 Not report 0 COST Gynecologic 54.0% - Meeker et al. 41 2016 United States Cross-sectional 119 61.0 (22–87) 48.0 InCharge Any cancer site 29% - Knight et al. 42 2018 United States Cross-sectional 1988 59.0 (12.3) 37.7 PSQ-18 Any cancer site 26.4% D, T Koenig et al. 43 2021 United States Cross-sectional 93 64.0 (57-71) 47 InCharge Brain or Spine Metastases 24.7% S, T Whitney et al. 44 2015 United States Cross-sectional 1209 Not report 41.9 MEPS Any cancer site Not report D, S Wan et al. 45 2020 United States Cross-sectional 95 58.0 (49-66) 0 COST Breast Not report D, T Table1.Characteristics of included studies(contined ) First author Publication Years Country Study design Simple size Age (SD) Male(%) Survey instrument Cancer type Prevalence (%) Risk factors (High FT) Katharine et al. 46 2021 United States Prospective 308 62.0 (7.1) 0 COST Gynecologic 47.0% - Bauer et al. 47 2020 United States Cross-sectional 49 64.3 (7.3) 100 COST Prostate Not report S Esselen et al. 48 2021 United States Cross-sectional 334 55.0 (7.9) 0 COST Gynecologic 48.5 - Baddour et al. 49 2021 United States Cross-sectional 71 63.0 (10.4) 67.6 FDQ Head and neck 45% D, S Stone et al. 50 2021 United States Prospective 2121 Not report 100 DBS Prostate Not report D, S, T Boukovalas et al. 51 2021 United States Cross-sectional 294 Not report 0 COST Breast Not report D, S Friedes et al. 52 2021 United States Prospective 215 64 (29-90) 51.6 COST Lung 51.8% S,T Table 1 Characteristics of included studies(contined ) First author Publication Years Country Study design Simple size Age (SD) Male(%) Survey instrument Cancer type Prevalence (%) Risk factors (High FT) Honda et al. 53 2019 Japan Prospective 156 67 (30-87) 53 COST Any cancer site 34.6% D, S Meeker et al. 54 2017 United States Cross-sectional 120 62 (22-87) 48 InCharge Genitourinary 21.8% - de Souza et al. 55 2017 United States Cross-sectional 233 59 (27-88) 41.6 COST Any cancer site Not report D, S Durber et al. 56 2021 Australia Cross-sectional 257 63 (19-88) 46 COST Any cancer site Not report D, S, T Bouberhan et al. 57 2019 United States Cross-sectional 240 56 (44-66) 0 COST Gynecologic 31.7% S, T Rummo et al. 58 2019 United States Cross-sectional 167 64 (23-90) 45 COST Any cancer site 71.3% D, S, T Ehlers et al. 59 2020 United States Cross-sectional 226 Not report 64 COST Bladder Not report D, S Table 1 Characteristics of included studies(contined ) First author Publication Years Country Study design Simple size Age (SD) Male(%) Survey instrument Cancer type P revalence (%) Risk factors (FT) Mady et al. 60 2019 United States Cross-sectional 104 64 (29-92) 76.9 FDQ Head and neck 40.5% D, S Yu et al. 61 2021 China Cross-sectional 440 57.0 (9.2) 45.7% COST Stomach Colorectal Breast Lung Not report D, S Benedict et al. 62 2021 United States Cross-sectional 273 Not report 0 COST Breast Gynecologic 45.0% D, S, T Abbreviations: COST, Comprehensive Score forfinancial Toxicity; DBS, Disease burden scale; FT, financial toxicity; FDQ, Financial Distress Questionnaire; InCharge, the InCharge Financial Distress/Financial Well-being Scale; PSQ-18, the Patient Satisfaction Questionnaire; D, Demographic factors; S, Socioeconomic factors; T, Treatment factors . Table 2 Subgroup analyses by demographic characteristics Subgroups Number of include studies Prevalence (95%CI) Financial Toxicity Pooling Model P value I²(%) Sex male 4 36%(0.20,0.53) Random ＜0.001 98.0% female 5 53%(0.29,0.77) Random ＜0.001 93.4% Age ≥65 3 14%(0.12,0.17) Fixed 0.890 0.0% ＜65 3 32%(0.30,0.35) Fixed 0.660 0.0% Race/ethnicity White 8 34%(0.25,0.43) Random ＜0.001 95.3% Black 7 61%(0.45,0.77) Random ＜0.001 89.4% Hispanic 5 64%(0.52,0.75) Fixed 0.369 6.6% Asian 4 38%(0.13,0.63) Random ＜0.001 90.6% Marital status 4 Married 10 37%(028,0.46) Random ＜0.001 95.3% Unmarried 9 49%(0.37,0.61) Random ＜0.001 93.5% Employment status Employed 9 37%(0.28,0.47) Random ＜0.001 93.8% Not employed 10 52%(0.40,0.64) Random ＜0.001 96.1% Retired 5 30%(0.20,0.41) Random ＜0.001 82.9% Education level High school or less 8 50%(0.37,0.63) Random ＜0.001 92.3% Some college 8 48%(0.35,0.61) Random ＜0.001 90.5% College graduate or above 8 32%(0.21,0.42) Random ＜0.001 94.2% Health insurance Medicare or Medicaid 7 44%(0.29,0.58) Random ＜0.001 90.7% Supplemental insurance 6 27%(0.18,0.37) Random ＜0.001 80.2% Private insurance 6 37%(0.25,0.48) Random ＜0.001 88.6% Country Developed country 19 39%(0.38,0.40) Random ＜0.001 97.0% Developing country 3 53%(0.50,0.56) Random ＜0.001 98.2% Table 2 Subgroup analyses by clinical characteristics Subgroups Number of include studies Prevalence (95%CI) Financial Toxicity Pooling Model P value I²(%) Cancer type Lung 3 29%(0.04,0.55) Random ＜0.001 91.3% Breast 5 45%(0.38,0.52) Random 0.011 69.6% Renal cell carcinoma 4 45%(0.36,0.54) Random ＜0.001 88.2% Head and neck 3 42%(0.35,0.49) Random 0.815 0.0% Genitourinary 2 11%(-0.10,0.32) Random ＜0.001 96.8% Gynecologic 4 45%(0.36,0.54) Random ＜0.001 88.2% Ovarian 3 44%(0.34,0.53) Random 0.019 74.7% Uterine 3 35%(0.29,0.42) Random 0.250 27.9% Cervical 3 63%(0.54,0.72) Random 0.373 0.0% Cancer stage T0 3 23%(0.16,0.29) Fixd 0.797 0.0% T1 4 33%(020,0.46) Random ＜0.001 87.0% T2 4 39%(0.30,0.49) Random 0.008 74.7% T3 4 49%(0.31,0.68) Random ＜0.001 95.4% T4 4 42%(0.28,0.56) Random ＜0.001 90.4% Treatment Received radiotherapy 5 42%(0.28,0.55) Random 0.002 75.8% Received chmeotherapy 4 43%(0.33,0.53) Random 0.002 79.6% Received surgery 4 35%(0.22,0.49) Random ＜0.001 89.7% Received hormonal therapy 4 44%(0.34,0.54) Fixd 0.248 27.3% Received targeted therapy 2 54%(0.48,0.59) Fixd 0.330 0.0% Survey intrument COST 16 51%(0.49,0.52) Random ＜0.001 95.7% Other 5 27%(0.25,0.29) Random 0.001 75.1% Table 3 Pooled risk factors of self-reported financial toxicity Risk factors Number of include studies OR (95%CI) P value I²(%) Low income 5 2.48(1.72-3.24) <0.001 3.1% Unemployed 4 0.74(0.52,0.96) <0.001 55.5% No private insurance 3 1.69(1.02,2.37) <0.001 0.0% Younger age 5 2.05(1.56,2.54) <0.001 0.0% Being female 2 0.86(0.58,1.14) <0.001 63.4% Non-white 4 1.59(1.33,1.85) <0.001 0.0% Unmarried 6 1.10(0.95,1.25) <0.001 53.3% Complted college 4 0.56(0.47,0.66) <0.001 63.3% Long distance from hospital 3 0.71(0.49,0.95) <0.001 0..2% Cancer stage(T3-T4) 2 1.39(1.08,1.70) <0.001 0.0% More recent diagnosis 2 1.31(1.04,1.57) <0.001 0.0% Table 3 Pooled risk factors of self-reported financial toxicity Risk factors Number of include studies β (95%CI) P value I²(%) Low income 10 5.66(2.78-8.53) <0.001 95.1% Unemployed 4 -2.90(-5.71,-0.63) <0.001 75.7% Supplemental insurance 3 1.29(- 1.39,3.97) 0.004 76.8% Greater annual OOP 2 -4.26(-6.95,-1.57) 0.002 0.0% Older age 5 0.34(0.12,0.55) <0.001 80.3% Being female 2 -0.81(-2.03,0.41) 0.195 0.0% Non-white 2 -2.19(-8.12,3.73) 0.261 77.9% Unmarried 4 -1.84(-5.13,1.45) 0.008 74.7% Complted college 3 0.59(-1.40,2.58) 0.559 0.0% Cancer stage(T3-T4) 3 -4.74(-6.90,-2.57) <0.001 0.0% More inpatient admission 2 -2.36(-7.61,2.89) 0.528 82.9% Supplementary Files Supplementalmateials.docx 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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Jiang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAzUlEQVRIiWNgGAWjYBAC+/bmA8Y/KmyY+dkbiNRiwHMsoZjhTBq7ZM8BYrVI+Bh8Zmw7zG9wI4FILeYSPIabC84clma4+XjjDYYam2iCWixntxUbz6hIN2acnVZswXAsLbeBoJ47h7cZ8JyxTmaWzjGTYGw4TISWGwnmP3jbmOvbJM8QqcXgRoqBMW+bMzOPBA+RWiR7jiUYzjiTxizBA/RLAjF+4WdvPmDwARiV9scPb7zxocaGCL8gO1IigRTlEC2k6hgFo2AUjIKRAQDTwEHN3ZCX0AAAAABJRU5ErkJggg==","orcid":"","institution":"Sichuan Cancer Hospital and Research Institute: Sichuan Cancer Hospital and Institute","correspondingAuthor":true,"submittingAuthor":false,"prefix":"","firstName":"QingHua","middleName":"","lastName":"Jiang","suffix":""},{"id":91892616,"identity":"93a3dc95-12c6-4094-8869-e1120c6648a5","order_by":1,"name":"Jiang Hua","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jiang","middleName":"","lastName":"Hua","suffix":""},{"id":91892617,"identity":"975f3c39-9fae-4415-b2c8-8242ef6fb184","order_by":2,"name":"Mou Wenxuan","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Mou","middleName":"","lastName":"Wenxuan","suffix":""},{"id":91892618,"identity":"7d08c0b0-d534-4754-9b69-b5d48bcb1279","order_by":3,"name":"Jiang Luxi","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Jiang","middleName":"","lastName":"Luxi","suffix":""},{"id":91892619,"identity":"1992ab1b-3829-481d-951d-1ab09acdb52b","order_by":4,"name":"Lyu Jianxia","email":"","orcid":"","institution":"Sichuan Cancer Hospital and Research Institute: Sichuan Cancer Hospital and Institute","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Lyu","middleName":"","lastName":"Jianxia","suffix":""},{"id":91892620,"identity":"54134430-58f4-4465-942b-235e7fcb132b","order_by":5,"name":"Zeng Yu","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Zeng","middleName":"","lastName":"Yu","suffix":""},{"id":91892621,"identity":"2b3b8531-d1cd-4d2b-b2de-dfe7a60010e0","order_by":6,"name":"Liu Ying","email":"","orcid":"","institution":"Chengdu Medical College","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Liu","middleName":"","lastName":"Ying","suffix":""},{"id":91892622,"identity":"442f6b40-d3a6-42cd-8ab1-2232de9ca674","order_by":7,"name":"Hu Aiping","email":"","orcid":"","institution":"University of Electronic Science and Technology of China","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Hu","middleName":"","lastName":"Aiping","suffix":""}],"badges":[],"createdAt":"2022-02-22 06:54:30","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-1383681/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-1383681/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":19449488,"identity":"9da75544-9045-4825-ae50-6cf1732c3dba","added_by":"auto","created_at":"2022-03-21 20:01:11","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3383998,"visible":true,"origin":"","legend":"\u003cp\u003eThe article selection process \u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-1383681/v1/08d67c535fe0822934b3afdd.png"},{"id":19449184,"identity":"9d834fa5-1279-4e8d-ada1-10a8050eaa89","added_by":"auto","created_at":"2022-03-21 19:58:11","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":601344,"visible":true,"origin":"","legend":"\u003cp\u003eForest plots for the pooled prevalence of self-reported financial toxicity\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-1383681/v1/adbf358fbaee596bbbcd5eef.png"},{"id":19449183,"identity":"285b59a7-50fe-49c1-a577-e9c469b94b8c","added_by":"auto","created_at":"2022-03-21 19:58:11","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":130182,"visible":true,"origin":"","legend":"\u003cp\u003eFunnel plot for assessing publication biases\u003c/p\u003e\u003cp\u003e\u003cbr\u003e\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-1383681/v1/5469688c9f0a36f1ccb86762.png"},{"id":20220707,"identity":"af11e8aa-4992-4dd7-839f-a7b5dbf1d296","added_by":"auto","created_at":"2022-04-12 02:57:14","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1642202,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-1383681/v1/f8457987-20e4-4cac-8ee2-f7777d205b8d.pdf"},{"id":19449186,"identity":"71814ef5-04bb-4789-adc5-7c8064edb13c","added_by":"auto","created_at":"2022-03-21 19:58:12","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":15207818,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementalmateials.docx","url":"https://assets-eu.researchsquare.com/files/rs-1383681/v1/a32a53fb23114b7297578791.docx"}],"financialInterests":"","formattedTitle":"Prevalence and risk factors of self-reported financial toxicity in cancer survivors: A systematic review and meta-analysis","fulltext":[{"header":"What Is Already Known About The Topic?","content":"\u003cul\u003e\n \u003cli\u003eFinancial toxicity is closely related to cancer treatment ,which negatively impacts the quality of life, mental health, and treatment adherence of cancer survivors.\u003c/li\u003e\n \u003cli\u003eThe measures of FT varied widely among\u0026nbsp;previous\u0026nbsp;studies, categorized as monetary measures, objective measures, and subjective measures, and most were not validated.\u003c/li\u003e\n \u003cli\u003eA large number of observational studies using subjective measures have reported the estimated prevalence and risk factors of financial toxicity , but the related systematic review is not available.\u003c/li\u003e\n\u003c/ul\u003e\n\u003ch2\u003e\u003cstrong\u003eWhat this paper adds?\u003c/strong\u003e\u003c/h2\u003e\n\u003cul\u003e\n \u003cli\u003eThis paper provides the estimates of the pooled prevalence of self-reported financial toxicity, which was 45% (95% CI: 48%-56%).\u003c/li\u003e\n \u003cli\u003eLow income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis are associated with self-reported financial toxicity.\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"1. Introduction","content":"\u003cp\u003eCancer treatment is a complex process, which often requires the use of innovative treatment and drugs. With the advancement of the medical level, especially the development of precision radiotherapy, widespread used of targeted therapy and immunotherapy, the clinical efficacy of patients has been significantly improved\u003csup\u003e\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. However, the new treatment not only improve the prognosis of patients, but also bring heavy financial burdens and side effects, which have a negative impact on the long-term quality of life of cancer survivors\u003csup\u003e\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e. Similar to the side effects of cancer treatment, financial toxicity is defined as: \"The subjective burden and objective financial distress of cancer patients after treatment with innovative drugs and accompanying health services.\u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e,\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e The measures of FT varied widely among previous studies, categorized as monetary measures, objective measures, and subjective measures, and most were not validated\u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition, the use of survey tools lacks consistency\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, prior studies suggested that FT should be measured using patient-reported outcomes(PROMs)to reflect cancer survivors\u0026rsquo; thoughts, complaints and opinions that any numbers or observers cannot\u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. However, the development and verification of current PROMs vary greatly, and none of them are considered the gold standard. Several instruments have been developed, validated, and intended for self-reported financial toxicity in cancer patients: Breast Cancer Finances Survey Inventory(BCFS)\u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e, Socioeconomic Wellbeing scale(SWS)\u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e, the InCharge Financial Distress/Financial Well-Being Scale(InCharge/FWS)\u003csup\u003e15\u003c/sup\u003e, the Financial Distress Questionnaire(FDQ)\u003csup\u003e\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e, Financial Index of Toxicity(FIT)\u003csup\u003e\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e, and the Comprehensive Score for financial Toxicity (COST)\u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Among all measures, the COST tools was the most commonly used survey tools and was developed by de Souza\u003csup\u003e18\u003c/sup\u003eto meet the financial toxicity investigations of cancer patients in the United States, which has been verified in many countries around the world, including China\u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e, India\u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e, Italy\u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u003c/sup\u003e, Australia\u003csup\u003e\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e, Japan\u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e\u003c/sup\u003e, etc., and has achieved good reliability and validity.Based on differences in health related quality of life(HRQoL), analogous to the NCI-Common Terminology Criteria for Adverse Events, the COST-PROM grading system was developed by de Souza with 4 FT grades (G)\u003csup\u003e\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e: Grade0, no FT, COST score\u0026thinsp;\u0026ge;\u0026thinsp;26 ; Grade1, mild FT:COST score\u0026thinsp;\u0026ge;\u0026thinsp;14\u0026ndash;26; Grade2, moderate FT: score\u0026thinsp;\u0026gt;\u0026thinsp;0\u0026ndash;14; and Grade3, severe FT: COST score\u0026thinsp;=\u0026thinsp;0.\u003c/p\u003e \u003cp\u003eTo date, although there have been a large number of observational studies on financial toxicity, PROMs have been applied to the investigation of financial toxicity, and the estimated prevalence and risk factors of financial toxicity are widely reported, these results have not been synthesized. Existing evidence about the risk factors of FT are inconsistent varied by cancer type, survey tools, population and health insurance system, which was lack of comparison between the results of multiple studies. The aim of this systematic review is two-fold: 1. to determine a pooled prevalence of self-reported financial toxicity and explore its potential risk factors, and 2. to provide evidence-based recommendations for financial toxicity towards ensuring improved the awareness and measures of self-reported financial toxicity for nurses.\u003c/p\u003e"},{"header":"2. Material","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003e2.1. Protocol and Registration\u003c/h2\u003e\n \u003cp\u003eThis review was conducted following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e and is registered in PROSPERO (CRD42021254332).\u003c/p\u003e\n \u003ch2\u003e2.2. Literature search\u003c/h2\u003e\n \u003cp\u003eA comprehensive search of English literature using the database of PubMed, EMBASE, Web of science, PsycINFO, CHINAHL. Screen the reference list of the included articles to identify any other eligible studies. The search strategies were performed through a combination of the Medical Subject Heading (MESH)and free words. The following Mesh terms and free words were include: \u0026apos;oncology\u0026apos;, \u0026apos;neoplasms*\u0026apos;, \u0026apos;cancer survivors\u0026apos;, \u0026apos;cancer[MeSH]\u0026apos;, \u0026apos;cost\u0026apos;, \u0026apos;expense\u0026apos;, \u0026apos;out-of-pocket\u0026apos;, \u0026apos;financial hardship\u0026apos;, \u0026apos;financial burden\u0026apos;, \u0026apos;financial stress[MeSH]\u0026apos;, \u0026apos;economic burden\u0026apos;, \u0026apos;financial toxicity\u0026apos;, \u0026apos;Prevalence[MeSH]\u0026apos;,\u0026apos;Epidemiology[MeSH Terms]\u0026apos;, \u0026apos;Risk Factors[Mesh]\u0026apos;, \u0026apos;Health Risk Behaviors[Mesh]\u0026apos;, \u0026apos;Observational Studies[MeSH Terms]\u0026apos;. Search terms and strategy are delineated in (Appendix figure A.1).\u003c/p\u003e\n \u003cp\u003eWe use the Boolean operators \u0026quot;OR\u0026quot; and \u0026quot;AND\u0026quot; between the groups. The publication year of these articles was limited to January 1, 2010 to the second week of September 2021, and only full-text original research articles published in English are considered. All search results are downloaded and imported directly into EndNote, versionX9.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003e2.3. Eligibility Criteria\u003c/h2\u003e\n \u003cp\u003eThe inclusion criteria were as follows: (1) the type of studies had to be observational; (2) study subjects were patients with cancers of any disease site and stage; (3) age\u0026thinsp;\u0026gt;\u0026thinsp;18 years old; (4) prevalence or risk factors of self-reported financial toxicity was reported; (5) study must use subjective measures.The exclusion criteria are: (1) the sample size was less than 40; (2) lack of reliability and validity of survey tools. (3) studies contained incomplete data.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003e2.4. Data extraction\u003c/h2\u003e\n \u003cp\u003eThe data extraction was completed by two reviewers, who screened the title and abstract of the literature to identify articles that might meet the inclusion criteria. The reasons for the exclusion were recorded, and the differences in the process were discussed until an agreement was reached. Subsequently, a researcher extracted data from all eligible full-text articles, including publication year, main author, country, study design, FT assessment, HRQOL measurement, statistical methods. and main findings. Another reviewer checked the completeness and accuracy of the information. The entire literature screening process is carried out independently by two researchers. If there were any disagreements, they will be resolved through discussion and consensus. When the discussion still fails to resolve the differences, it will be handed over to a third party for judgment. The PRISMA flowchart is displayed in (Fig. \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003e2.5. Quality appraisal\u003c/h2\u003e\n \u003cp\u003eTwo reviewers independently using the NIH Quality Assessment Tool for Observational Cohort and Cross-Sectional Studies\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e (Appendix table A.1) to ascertain the risk of bias and overall study quality (the individual study was rated \u0026ldquo;good\u0026rdquo; if it met all applicable criteria, and if it met most of the criteria, then rated as \u0026quot;fair\u0026quot;, and if it met a few criteria, rated as \u0026quot;poor\u0026quot;). This tool has a total of 14 questions related to the risk of bias in the study and is designed to help researchers focus on the key concepts for evaluating the internal validity of a study\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003e2.6. Data synthesis\u003c/h2\u003e\n \u003cp\u003eFor analysis, the results extracted from the included studies were input into Stata 15.0 software package. We then conducted several meta-analyses of identified studies to pooled prevalence and risk factors of self-reported financial toxicity. The proportions of patients with financial toxicity were extracted from all included studies in order to calculate the pooled prevalence. The risk estimates (\u0026beta; and OR) and associated 95% CIs were extracted from included studies to assess the risk factors of self-reported financial toxicity. We pooled the coefficient(\u0026beta;) of Multivariate linear regression model and the Odd ritio(OR )value in the Logistic regression. The degree of heterogeneity was tested by Cochrane\u0026rsquo;s Q test (P value) and the I\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e statistic\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. We set the I\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e values as 25%, 50%, and 75%, indicating low, medium, and high heterogeneity, respectively. When no significant heterogeneity was detected (I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;\u0026le;\u0026thinsp;50), the fixed-effects model was used for pooled prevalence and risk estimates, otherwise the random-effects model was used\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. We also employed funnel plot asymmetry to detect the potential publication bias. An Egger\u0026apos;s regression was applied to test the funnel plot symmetry\u003csup\u003e\u003cspan class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e\n \u003cp\u003eFinally, the sensitivity analyses was performed to test the robustness of our results. The data of included studies were divided into subgroups according to the demographic characteristics and clinical characteristics. Because some subgroup analyses included very few studies, we only conducted sensitivity analyses for the meta-analyses that included more than two studies. All statistical tests were two-sided, and P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"3. Results","content":"\u003ch2\u003e3.1. Study Selection\u003c/h2\u003e\n\u003cp\u003eIn total, 4913 related citations (PubMed: 2559, EMBASE: 746, PsycINFO: 160, CINAHL: 203，Web of science:1245) were identified and qualified through electronic database search, of which 1167 were duplicates. After screening titles and abstracts and removing duplicate references, 402 articles were selected on the basis of inclusion criteria.. Of these studies, 153 were excluded because of irrelevant results , wrong populations , wrong disease, use objective or monetary measure, sample size smaller than 50, qualitative study, and duplicate reporting. A total of 33 studies\u003csup\u003e30-62\u003c/sup\u003e were utilized for the meta-analysis.The selection process for the study is shown in the PRISMA flow chart (Fig 1).\u003c/p\u003e\n\u003ch2\u003e3.2. Characteristics of the included primary studies\u003c/h2\u003e\n\u003cp\u003eThe characteristics of the 33 studies are summarized in Table 1.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.3. Prevalence of self-reported financial toxicity\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eIn the 22 studies available for the meta-analysis, the pooled prevalence of financial toxicity was estimated to be 45% (95% CI: 38% to 53%, I\u003csup\u003e2\u003c/sup\u003e = 97.3%, P \u0026lt; 0.0001), which was based on a random-effects model. Among them, the mild financial toxicity(grade1) was estimated to be 42% (95% CI: 28% to 55%, I\u003csup\u003e2\u003c/sup\u003e = 95.9%, P \u0026lt; 0.0001), the moderate financial toxicity(grade2) was estimated to be 17% (95% CI: 13% to 22%, I\u003csup\u003e2\u003c/sup\u003e = 82.9%, P \u0026lt; 0.0001), the severe financial toxicity(grade3) was estimated to be 1% (95% CI: 0% to 1%, I\u003csup\u003e2\u003c/sup\u003e = 0%, P =0.475)(Fig 2).\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.4. Subgroup analyses of self-reported financial toxicity\u003c/h2\u003e\n\u003cp\u003eThe subgroup analysis of financial toxicity was divided into two parts: demographic characteristics and clinical characteristics. In demographic characteristics, we stratified prevalence of financial toxicity according to gender, age, race, marital status, employment status, education level, health insurance, and country. In clinical characteristics, we stratified prevalence of financial toxicity according to cancer type, cancer stage, treatment, and survey intrument. The estimated pooled results obtained in subgroup analyses are shown in Table2.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.5 Risk factors\u003c/h2\u003e\n\u003cp\u003eA total of 28 studies reported the risk factors associated with financial toxicity (additional details in Appendix table A.2). The pooled analysis identified 9 potential risk factors of financial toxicity(7 in \u0026beta; and 8 in OR) : low income, younger age, no private insurance, greater annual OOP, non-white, advanced cancer, unemployed, and more recent diagnosis, unmarried(Appendix figure A.2). The results of risk factors analysis are listed in Table 3.\u0026nbsp;\u003c/p\u003e\n\u003ch2\u003e3.6. Publication bias\u003c/h2\u003e\n\u003cp\u003eFunnel plot asymmetry (Fig 3) revealed evidence of publication bias between study heterogeneity. Results of Egger\u0026rsquo;s \u0026nbsp;test further confirmed the funnel plot asymmetry.\u003c/p\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eThis study systematically reviewed 33 studies, which involved a total of 13,025 cancer survivors. The overall prevalence of financial toxicity was 45%, and most of patients was in Grade1 stage, which showed that the problem of financial toxicity urgently needs to be resolved. Risk factors related to financial toxicity include: low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis(Table\u0026nbsp;\u003cspan refid=\"Tab5\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Since most of the included literature comes from the United States, the result may more reflect the pooled prevalence of financial toxicity in the United States(pooled prevalence: 44%, 95%CI: 35%-52%)(Appendix Figure A.3). In a systematic review of the financial burden of cancer patients in the United States, Smith et al. reported that the sample-weighted prevalence was 49% (95% CI, 41\u0026ndash;56%) of patients with cancer with any financial burden\u003csup\u003e\u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e63\u003c/span\u003e\u003c/sup\u003e. Indeed, there were certain differences of pooled prevalence between this systematic review and Smith et al.. This discrepancy may be due to the fact that Smith et al.\u0026rsquo; results were based on a wider range of measures about financial burden, including subjective measures, objective measures and monetary measures, while the measures of our study focuses on PROMs.\u003c/p\u003e \u003cp\u003eIn this systematic review, all self-reported financial toxicity of patients was measured by subjective intrument, which was used scales or questionnaires to explore patients' subjective feelings about their own financial burden. This review mainly include 5 survey tools, most of the included studies used the COST-PROM. After data synthesis, we observed that there are big differences between survey tools. In the study using COST tool, the pooled prevalence of financial toxicity was 51%(95% CI: 49\u0026ndash;52%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;95.7%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). However, the studies using other tools to measure financial toxicity, the pooled prevalence of financial toxicity was 27%(95% CI: 25\u0026ndash;29%, I\u003csup\u003e2\u003c/sup\u003e\u0026thinsp;=\u0026thinsp;75.1%, P\u0026thinsp;\u0026lt;\u0026thinsp;0.0001). This disparity may reflect the fact that COST tool and other tools have certain differences in specificity and sensitivity, which leads to different pooled prevalence. Currently, the PROMs used to assess self-reported financial toxicity are lacking consistency on a global scale, and the data on self-reported financial toxicity has not yet been quantified in a standardized way\u003csup\u003e\u003cspan additionalcitationids=\"CR10\" citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e. In the long term, a lack of standardization in measurement can hinder the choice of PROMs for subsequent cross-sectional surveys and comparisons across studies. Consequently, based on this result, the criteria for the measure of financial toxicity needs to be further improved and reached a consensus. Clinicians and nurses should strengthen multidisciplinary cooperation to improve the sensitivity and specificity of economic toxicity assessment tools, and verify them in various cancer types, improve their universality, and reach agreement in clinical applications. It is suggested that multidisciplinary collaboration with the clinicians, nurses and researchers jointly strive to define the criteria to assess financial toxicity and improve its sensitivity and specificity. The criteria of survey intrument must be refined, verifying them in various cancer types, and their consistent application with high sensitivity and specificity must be promoted in the future.\u003c/p\u003e \u003cp\u003eIn the subgroup analysis on the demographic characteristics of patients, a stratified analysis has conducted among all cancer survivors, including gender, age, race, country, marital status, employment status, education level, and medical insurance. The age-stratified analysis indicated that the pooled prevalence of self-reported financial toxicity was higher in the younger than in the older patients. This discrepancy may be due to younger patients saving less and having a higher burden of living\u003csup\u003e\u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e64\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e65\u003c/span\u003e\u003c/sup\u003e. The present meta-analysis has demonstrated that the pooled prevalence of self-reported financial toxicity varies with the difference of races. Compared with other races, the pooled prevalence of financial toxicity of white people was the lowest. The pooled prevalence of financial toxicity of patients with supplemental insurance was obviously lower. This finding was not unexpected, because better medical insurance means that patients pay lower out-of-pocket expenses and less financial burden they need to bear during the treatment process\u003csup\u003e\u003cspan additionalcitationids=\"CR67\" citationid=\"CR66\" class=\"CitationRef\"\u003e66\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR68\" class=\"CitationRef\"\u003e68\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis systematic review further validated the findings of Alison and Floortje et al. that unemployed patients have a higher risk of financial toxicity\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e. The results of their studies showed that increased risk of financial toxicity was associated with both unemployment, changed or reduced employment, lost days at work, or poor work ability\u003csup\u003e\u003cspan citationid=\"CR69\" class=\"CitationRef\"\u003e69\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR70\" class=\"CitationRef\"\u003e70\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eIn addition, we compared the prevalence of self-reported financial toxicity between developing and developed countries, and the results showed that the prevalence of financial toxicity in developed countries was lower. This result needs to be further verified because we incorporated less studies from developing countries. It is undeniable that there are differences in healthcare systems, economic level and cultural background between developed and developing countries. However, most of the literature on financial toxicity were concentrated on developed countries, so more observational studies are needed to supple in developing countries to fill this gap in our knowledge. Nevertheless, in our limited literature review, financial toxicity specific survey tools, such as COST tool, are rarely used in developing countries. Developing countries need to do more to recognize the challenges associated with financial toxicity.\u003c/p\u003e \u003cp\u003eIn a subgroup analysis regarding the clinical characteristics of the patients, we discussed the gender, type of cancer, and stage of cancer, in a stratified analysis. Given the wide variation in treatment and medication across cancers, patients' out-of-pocket costs varied. However, we did not find differences in the pooled prevalence of financial toxicity among several cancer types, such as breast cancer, renal cell carcinoma, head and neck cancer(HNC), and gynecologic cancer(Appendix Figure A.3). Despite lower prevalence of financial toxicity was observed in lung and urologic cancers (29% and 11%), this result needs to be further validated due to limited included literature and sample size. For example, in a retrospective study of the Medical Expenditure Panel Survey (MEPS), HNC patients had disproportionately higher financial burden in the form of higher total and relative OOP expenses compared to other cancers, because HNC patients were more often of a minority race/ethnicity, poor, less educated, publicly insured, and of lower health status\u003csup\u003e\u003cspan citationid=\"CR71\" class=\"CitationRef\"\u003e71\u003c/span\u003e\u003c/sup\u003e. Consistent with the results of risk factor analysis, more advanced cancer stages have a higher prevalence of financial toxicity. The treatment of advanced cancer is more complicated because it are more likely to require a multimodal treatment regimen (i.e., targeted therapy and radiation therapy in addition to surgery) and novel chemotherapeutic agents72. Similarly, in the comparison of different treatment, patients who have received targeted therapy have a higher prevalence of financial toxicity, and patients who receive surgery alone have the lowest prevalence of financial toxicity( ).\u003c/p\u003e \u003cp\u003eIn the included prospective studies\u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e,\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e,\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e,\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e,\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e,\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e\u003c/sup\u003e, we focused on the question of whether self-reported financial toxicity will change dynamically over time. The results reported by Liang et al.40 and Stone et al.\u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e conducted that the severity of financial toxicity will decrease over time. However, Friedes et al.\u003csup\u003e52\u003c/sup\u003ereported that FT was pervasive from diagnosis through the first 6 months of cancer therapy. The patient's out-of-pocket costs gradually increased when the length of stay was prolonged, which may be one of the reasons why the patient's self-reported financial toxicity gradually increased over time. However, some patients may adopt coping strategies at the beginning of treatment (e.g., via the Internet or by asking their physicians) to anticipate their potential future treatment costs in advance; some patients may be unaware of the medical costs they are spending, for example, when their children are paying for their medical expenses. Therefore, the discrepancy in information acquisition between patients should be controlled in subsequent longitudinal studies to ensure consistency at baseline.\u003c/p\u003e \u003cp\u003eTo the best of our knowledge, this systematic review is the first to provide both the estimate of the pooled prevalence of self-reported financial toxicity and an assessment of risk factors associated with this condition. The current study further confirms the influence of sociodemographic factors (e.g., age, gender, employment status, health insurance, etc.) and clinical factors (cancer stage, treatment modality, time to disease diagnosis, etc.) on financial toxicity when measured by PROMs. In future studies, we need to identify differences in risk factors for financial toxicity between different countries given different medical backgrounds and economic levels. At the same time, it is necessary to explore the differences in the prevalence of financial toxicity among different cancer types in consideration of the differences in treatment, drugs, and medical expenses. Despite there is currently no gold standard for survey tools related financial toxicity, COST-PROM has been demonstrated to have good generalizability and specificity. Oncology nurses should play a vital role in the assessment of a patient with financial toxicity, so as to improve the quality of life of cancer survivors. Therefore, should be advocated nurses actively apply COST-PROM to clinical work, adopt a corresponding nursing management model for patients according to the COST grading system, providing financial information assistance and psychological interventions.\u003c/p\u003e"},{"header":"5. Limitations","content":"\u003cp\u003eIt is noteworthy that some of the potential limitations cannot be ignored. Firstly, limited by cross-sectional studies, we found high or moderate heterogeneities in most of the subgroup meta-analyses, although less heterogeneity was found in some subgroups. These findings indicate that the heterogeneity of included studies may also be affected by other factors, such as grading criteria. Therefore, further meta-analyses are necessary to explore the sources of heterogeneity as more original studies will be conducted in the future. Secondly, the language of included studies were limited in English, the exclusion of works published in other languages limited the comprehensiveness of the literature included. Future studies will need to overcome these limitations and assess the prevalence and risk factors of financial toxicity in a more comprehensive manner.\u003c/p\u003e"},{"header":"6. Conclusion","content":"\u003cp\u003eIn summary, this systematic review found a pooled prevalence of self-reported financial toxicity of 45%. Low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis constituted risk factors for self-reported financial toxicity. Such high prevalence indicates an urgent need for ongoing efforts to develop interventions to respond to the adverse impact of financial burdens in patients with cancer. Addressing the problem of cancer-related financial toxicity will require joint efforts at the policy, provider, health system and patient levels. The Research on risk factors for financial toxicity can provide a theoretical basis for nursing staff to evaluate and intervene in the financial toxicity in cancer survivors.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was funded by the 2020 Key R\u0026amp;D Project of Social Development of Sichuan Provincial Department of Science and Technology.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicts of interest/Competing interests\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interest.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of supporting data\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003econtributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eHua Jiang and QinghuaJiang conceived the idea and registered the protocol in PROSPERO; Ying Liu and Yu Zeng were responsible for establishing and performing the systematic literature search; LX Jiang and Hua Jiang were responsible for the quality of assessment; Jianxia Lyu and Aiping Hu performed the Data synthesis and designed tables and figures; Wenxuan Mou, Jianxia Lyu, LX Jiang, and Hua Jiang constituted the writing committee.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and Consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare their consent to publish this work\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eNot applicable\u003c/p\u003e"},{"header":"References","content":"\u003col class=\"decimal_type\"\u003e\n \u003cli\u003eTran, G., \u0026amp; Zafar, S. 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Assessing the Financial Toxicity of Radiation Oncology Patients Using the Validated Comprehensive Score for Financial Toxicity as a Patient-Reported Outcome. \u003cem\u003ePractical radiation oncology\u003c/em\u003e, \u003cem\u003e10\u003c/em\u003e(5), e322\u0026ndash;e329. \u003ca href=\"https://doi.org/10.1016/j.prro.2019.10.005\"\u003ehttps://doi.org/10.1016/j.prro.2019.10.005\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eEhlers, M., Bjurlin, M., Gore, J., Pruthi, R., Narang, G., Tan, R., Nielsen, M., Zhu, A., Deal, A., \u0026amp; Smith, A. (2021). A national cross-sectional survey of financial toxicity among bladder cancer patients. \u003cem\u003eUrologic oncology\u003c/em\u003e, \u003cem\u003e39\u003c/em\u003e(1), 76.e1\u0026ndash;76.e7. \u003ca href=\"https://doi.org/10.1016/j.urolonc.2020.09.030\"\u003ehttps://doi.org/10.1016/j.urolonc.2020.09.030\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eMady, L. J., Lyu, L., Owoc, M. S., Peddada, S. D., Thomas, T. H., Sabik, L. 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(2022). Greater financial toxicity relates to greater distress and worse quality of life among breast and gynecologic cancer survivors. \u003cem\u003ePsycho-oncology\u003c/em\u003e, \u003cem\u003e31\u003c/em\u003e(1), 9\u0026ndash;20. \u003ca href=\"https://doi.org/10.1002/pon.5763\"\u003ehttps://doi.org/10.1002/pon.5763\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eSmith, G. L., Lopez-Olivo, M. A., Advani, P. G., Ning, M. S., Geng, Y., Giordano, S. H., \u0026amp; Volk, R. J. (2019). Financial Burdens of Cancer Treatment: A Systematic Review of Risk Factors and Outcomes. \u003cem\u003eJournal of the National Comprehensive Cancer Network : JNCCN\u003c/em\u003e, \u003cem\u003e17\u003c/em\u003e(10), 1184\u0026ndash;1192. \u003ca href=\"https://doi.org/10.6004/jnccn.2019.7305\"\u003ehttps://doi.org/10.6004/jnccn.2019.7305\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eSalsman, J. M., Danhauer, S. C., Moore, J. B., Ip, E. H., McLouth, L. E., Nightingale, C. L., Cheung, C. K., Bingen, K. M., Tucker-Seeley, R. D., Little-Greene, D., Howard, D. S., \u0026amp; Reeve, B. B. (2021). Systematic review of financial burden assessment in cancer: Evaluation of measures and utility among adolescents and young adults and caregivers. \u003cem\u003eCancer\u003c/em\u003e, \u003cem\u003e127\u003c/em\u003e(11), 1739\u0026ndash;1748. \u003ca href=\"https://doi.org/10.1002/cncr.33559\"\u003ehttps://doi.org/10.1002/cncr.33559\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eHastert, T. A., Young, G. S., Pennell, M. L., Padamsee, T., Zafar, S. Y., DeGraffinreid, C., Naughton, M., Simon, M., \u0026amp; Paskett, E. D. (2018). Financial burden among older, long-term cancer survivors: Results from the LILAC study. \u003cem\u003eCancer medicine\u003c/em\u003e, \u003cem\u003e7\u003c/em\u003e(9), 4261\u0026ndash;4272. \u003ca href=\"https://doi.org/10.1002/cam4.1671\"\u003ehttps://doi.org/10.1002/cam4.1671\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eMao, W., Tang, S., Zhu, Y., Xie, Z., \u0026amp; Chen, W. (2017). Financial burden of healthcare for cancer patients with social medical insurance: a multi-centered study in urban China. \u003cem\u003eInternational journal for equity in health\u003c/em\u003e, \u003cem\u003e16\u003c/em\u003e(1), 180. \u003ca href=\"https://doi.org/10.1186/s12939-017-0675-y\"\u003ehttps://doi.org/10.1186/s12939-017-0675-y\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eFitch, M. I., Sharp, L., Hanly, P., \u0026amp; Longo, C. J. (2021). Experiencing financial toxicity associated with cancer in publicly funded healthcare systems: a systematic review of qualitative studies. \u003cem\u003eJournal of cancer survivorship : research and practice\u003c/em\u003e, 10.1007/s11764-021-01025-7. Advance online publication. \u003ca href=\"https://doi.org/10.1007/s11764-021-01025-7\"\u003ehttps://doi.org/10.1007/s11764-021-01025-7\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eLongo, C. J., Fitch, M. I., Banfield, L., Hanly, P., Yabroff, K. R., \u0026amp; Sharp, L. (2020). Financial toxicity associated with a cancer diagnosis in publicly funded healthcare countries: a systematic review. \u003cem\u003eSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(10), 4645\u0026ndash;4665. \u003ca href=\"https://doi.org/10.1007/s00520-020-05620-9\"\u003ehttps://doi.org/10.1007/s00520-020-05620-9\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eMols, F., Tomalin, B., Pearce, A., Kaambwa, B., \u0026amp; Koczwara, B. (2020). Financial toxicity and employment status in cancer survivors. A systematic literature review. \u003cem\u003eSupportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer\u003c/em\u003e, \u003cem\u003e28\u003c/em\u003e(12), 5693\u0026ndash;5708. \u003ca href=\"https://doi.org/10.1007/s00520-020-05719-z\"\u003ehttps://doi.org/10.1007/s00520-020-05719-z\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003ePearce, A., Tomalin, B., Kaambwa, B., Horevoorts, N., Duijts, S., Mols, F., van de Poll-Franse, L., \u0026amp; Koczwara, B. (2019). Financial toxicity is more than costs of care: the relationship between employment and financial toxicity in long-term cancer survivors. \u003cem\u003eJournal of cancer survivorship : research and practice\u003c/em\u003e, \u003cem\u003e13\u003c/em\u003e(1), 10\u0026ndash;20. \u003ca href=\"https://doi.org/10.1007/s11764-018-0723-7\"\u003ehttps://doi.org/10.1007/s11764-018-0723-7\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eMassa, S. T., Osazuwa-Peters, N., Adjei Boakye, E., Walker, R. J., \u0026amp; Ward, G. M. (2019). Comparison of the Financial Burden of Survivors of Head and Neck Cancer With Other Cancer Survivors. \u003cem\u003eJAMA otolaryngology-- head \u0026amp; neck surgery\u003c/em\u003e, \u003cem\u003e145\u003c/em\u003e(3), 239\u0026ndash;249. \u003ca href=\"https://doi.org/10.1001/jamaoto.2018.3982\"\u003ehttps://doi.org/10.1001/jamaoto.2018.3982\u003c/a\u003e\u003c/li\u003e\n \u003cli\u003eKent, E. E., Forsythe, L. P., Yabroff, K. R., Weaver, K. E., de Moor, J. S., Rodriguez, J. L., \u0026amp; Rowland, J. H. (2013). Are survivors who report cancer-related financial problems more likely to forgo or delay medical care?. \u003cem\u003eCancer\u003c/em\u003e, \u003cem\u003e119\u003c/em\u003e(20), 3710\u0026ndash;3717. https://doi.org/10.1002/cncr.28262\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eCharacteristics of included studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePublication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYears\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey instrument\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.832369942196532%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.497109826589597%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.878612716763005%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(High FT)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"31.791907514450866%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eEzeife et al.\u003csup\u003e30\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eCanada\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e200\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e64.3\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(10.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e44.25\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eLung\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eOffodile\u0026nbsp;et al.\u003csup\u003e31\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e571\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e58.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(12.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e51.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eS, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eHuntington\u0026nbsp;et al.\u003csup\u003e32\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e64.1\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(9.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eMultiple\u003c/p\u003e\n \u003cp\u003emyeloma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e50.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eStaehler\u0026nbsp;et al.\u003csup\u003e33\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e539\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e55.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(9.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e39\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eRenal cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e59.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eMarques\u0026nbsp;et al.\u003csup\u003e34\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e640\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e59.9\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(11.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e35.8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e42.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eMejri\u0026nbsp;et al.\u003csup\u003e35\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eTunisia\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e179\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e52.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(11.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e29.1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e80.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eS, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eJing et al.\u003csup\u003e36\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003e51.7\u003c/p\u003e\n \u003cp\u003e(10.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003e50%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.909090909090908%\"\u003e\n \u003cp\u003eLaRocca\u0026nbsp;et al.\u003csup\u003e37\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.807486631016043%\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.235294117647058%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.122994652406417%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.737967914438503%\"\u003e\n \u003cp\u003e1027\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.449197860962567%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.8449197860962565%\"\u003e\n \u003cp\u003e51.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.556149732620321%\"\u003e\n \u003cp\u003eSupport\u003c/p\u003e\n \u003cp\u003eScreen\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.62566844919786%\"\u003e\n \u003cp\u003eGastrointestinal\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.946524064171124%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.764705882352942%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eCharacteristics of included studies(contined )\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePublication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYears\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey instrument\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.79202279202279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.51851851851852%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.78062678062678%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(High FT)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"31.90883190883191%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003ePalmer\u0026nbsp;et al.\u003csup\u003e38\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eProspective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e157\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e52.2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e21.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eHuey\u0026nbsp;et al.\u003csup\u003e39\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e213\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e41.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e71%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eLiang\u0026nbsp;et al.\u003csup\u003e40\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003e\u0026nbsp;Prospective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eGynecologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e54.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eMeeker\u0026nbsp;et al.\u003csup\u003e41\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2016\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e119\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e61.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(22\u0026ndash;87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e48.0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003e\u0026nbsp;InCharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e29%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eKnight\u0026nbsp;et al.\u003csup\u003e42\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2018\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e1988\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e59.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(12.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e37.7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003ePSQ-18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e26.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eKoenig\u0026nbsp;et al.\u003csup\u003e43\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e64.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(57-71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003e\u0026nbsp;InCharge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eBrain or Spine Metastases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e24.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eS, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eWhitney\u0026nbsp;et al.\u003csup\u003e44\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e1209\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e41.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eMEPS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eWan\u0026nbsp;et al.\u003csup\u003e45\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e58.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(49-66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTable1.Characteristics of included studies(contined )\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePublication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYears\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey instrument\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.79202279202279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.51851851851852%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.78062678062678%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(High FT)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"31.90883190883191%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eKatharine\u0026nbsp;et al.\u003csup\u003e46\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003e\u0026nbsp;United States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eProspective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e308\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e62.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(7.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eGynecologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e47.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eBauer\u0026nbsp;et al.\u003csup\u003e47\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e49\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e64.3\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(7.3)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eS\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eEsselen\u0026nbsp;et al.\u003csup\u003e48\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e334\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e55.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(7.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eGynecologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e48.5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eBaddour\u0026nbsp;et al.\u003csup\u003e49\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e63.0\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(10.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e67.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eFDQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eHead and neck\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e45%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eStone\u0026nbsp;et al.\u003csup\u003e50\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eProspective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e2121\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eDBS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eBoukovalas\u0026nbsp;et al.\u003csup\u003e51\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e294\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eFriedes\u0026nbsp;et al.\u003csup\u003e52\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eProspective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e215\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003cp\u003e(29-90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e51.6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e51.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eS,T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 1\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eCharacteristics of included studies(contined )\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePublication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYears\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey instrument\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.79202279202279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.51851851851852%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.78062678062678%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(High FT)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"31.90883190883191%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eHonda\u0026nbsp;et al.\u003csup\u003e53\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eJapan\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eProspective\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e156\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e67\u003c/p\u003e\n \u003cp\u003e(30-87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e53\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e34.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eMeeker\u0026nbsp;et al.\u003csup\u003e54\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e120\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e62\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(22-87)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e48\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eInCharge\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eGenitourinary \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e21.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003ede Souza\u0026nbsp;et al.\u003csup\u003e55\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e233\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e59\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;(27-88)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e41.6\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eDurber\u0026nbsp;et al.\u003csup\u003e56\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eAustralia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e257\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e63\u003c/p\u003e\n \u003cp\u003e(19-88)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e46\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eBouberhan\u0026nbsp;et al.\u003csup\u003e57\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e240\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e56\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(44-66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eGynecologic\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e31.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eS, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eRummo\u0026nbsp;et al.\u003csup\u003e58\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e64\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(23-90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eAny cancer site\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e71.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eEhlers\u0026nbsp;et al.\u003csup\u003e59\u003c/sup\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2020\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e226\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eBladder\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"1\" cellpadding=\"0\" cellspacing=\"0\" width=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 1\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eCharacteristics of included studies(contined )\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFirst author\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePublication\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003eYears\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003e\u003cstrong\u003eStudy design\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSimple size\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(SD)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey instrument\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd rowspan=\"2\" valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e\u003cstrong\u003eP\u003c/strong\u003e\u003cstrong\u003erevalence (%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"22.79202279202279%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"18.51851851851852%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"26.78062678062678%\"\u003e\n \u003cp\u003e\u003cstrong\u003e(FT)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"31.90883190883191%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eMady\u0026nbsp;et al.\u003csup\u003e60\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e104\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e64\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(29-92)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e76.9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eFDQ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eHead and neck\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e40.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eYu et al.\u003csup\u003e61\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eChina\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e440\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003e57.0\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e(9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e45.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eStomach\u003c/p\u003e\n \u003cp\u003eColorectal\u003c/p\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" width=\"10.982048574445617%\"\u003e\n \u003cp\u003eBenedict\u0026nbsp;et al.\u003csup\u003e62\u003c/sup\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"7.708553326293559%\"\u003e\n \u003cp\u003e2021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.236536430834214%\"\u003e\n \u003cp\u003eUnited States\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.19324181626188%\"\u003e\n \u003cp\u003eCross-sectional\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.75818373812038%\"\u003e\n \u003cp\u003e273\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.447729672650475%\"\u003e\n \u003cp\u003eNot report\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"6.863780359028511%\"\u003e\n \u003cp\u003e0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"8.553326293558607%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.503695881731785%\"\u003e\n \u003cp\u003eBreast Gynecologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"9.926082365364309%\"\u003e\n \u003cp\u003e45.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" width=\"11.826821541710665%\"\u003e\n \u003cp\u003eD, S, T\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"11\" valign=\"top\" width=\"100%\"\u003e\n \u003cp\u003eAbbreviations: COST, Comprehensive Score forfinancial Toxicity; DBS, Disease burden scale; FT, financial toxicity; FDQ, Financial Distress Questionnaire; InCharge, the InCharge Financial Distress/Financial Well-being Scale; PSQ-18, the Patient Satisfaction Questionnaire; \u003cstrong\u003eD, Demographic factors; S, Socioeconomic factors; T, Treatment factors\u003c/strong\u003e.\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"113%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 2\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003e\u0026nbsp;Subgroup analyses by demographic characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of include studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"47.8643216080402%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinancial Toxicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePooling Model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eI\u0026sup2;(%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003emale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e36%(0.20,0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e98.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003efemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e53%(0.29,0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e93.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u0026ge;65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e14%(0.12,0.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eFixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.890\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e＜65\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e32%(0.30,0.35)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eFixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.660\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRace/ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e34%(0.25,0.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e95.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e7\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e61%(0.45,0.77)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e89.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eHispanic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e64%(0.52,0.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eFixed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.369\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e6.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eAsian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e38%(0.13,0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e90.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e37%(028,0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e95.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e49%(0.37,0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e93.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEmployment status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e9\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e37%(0.28,0.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e93.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eNot employed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e52%(0.40,0.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e96.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e30%(0.20,0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e82.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eHigh school or less\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e50%(0.37,0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e92.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eSome college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e48%(0.35,0.61)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e90.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eCollege graduate or above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e8\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e32%(0.21,0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e94.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eHealth insurance\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eMedicare or Medicaid\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u003cstrong\u003e7\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e44%(0.29,0.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e90.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eSupplemental insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e27%(0.18,0.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e80.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003ePrivate insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e37%(0.25,0.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e88.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCountry\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eDeveloped country\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e19\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e39%(0.38,0.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e97.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eDeveloping country\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e53%(0.50,0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e98.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"113%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"6\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 2\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eSubgroup analyses by clinical characteristics\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSubgroups\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of include studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrevalence\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" width=\"47.8643216080402%\"\u003e\n \u003cp\u003e\u003cstrong\u003eFinancial Toxicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u003cstrong\u003ePooling Model\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eI\u0026sup2;(%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer type\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e29%(0.04,0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e91.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e45%(0.38,0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.011\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e69.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eRenal cell carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e45%(0.36,0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e88.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eHead and neck\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e42%(0.35,0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.815\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eGenitourinary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e11%(-0.10,0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e96.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eGynecologic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e45%(0.36,0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e88.2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eOvarian\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e44%(0.34,0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;Random\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.019\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e74.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eUterine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e35%(0.29,0.42)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.250\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e27.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eCervical\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e63%(0.54,0.72)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.373\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eCancer stage\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eT0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e23%(0.16,0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eFixd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.797\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eT1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e33%(020,0.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e87.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eT2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e39%(0.30,0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e74.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eT3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e49%(0.31,0.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e95.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eT4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e42%(0.28,0.56)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e90.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eReceived radiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e42%(0.28,0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e75.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eReceived chmeotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e43%(0.33,0.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e79.6%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eReceived surgery\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e35%(0.22,0.49)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e89.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eReceived hormonal therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e44%(0.34,0.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eFixd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.248\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e27.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eReceived targeted therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e54%(0.48,0.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eFixd\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.330\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003e\u003cstrong\u003eSurvey intrument\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eCOST\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e51%(0.49,0.52)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e＜0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e95.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"19.723618090452263%\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.190954773869347%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"19.22110552763819%\"\u003e\n \u003cp\u003e27%(0.25,0.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"17.964824120603016%\"\u003e\n \u003cp\u003eRandom\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.08040201005025%\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"13.819095477386934%\"\u003e\n \u003cp\u003e75.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003e\u0026nbsp;\u003c/p\u003e\n\u003cdiv align=\"center\"\u003e\n \u003ctable border=\"0\" cellpadding=\"0\" cellspacing=\"0\" width=\"87%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003ePooled risk factors of self-reported financial toxicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of include studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e\u003cstrong\u003eOR\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eI\u0026sup2;(%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eLow income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e2.48(1.72-3.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e3.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e0.74(0.52,0.96)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e55.5%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eNo private insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e1.69(1.02,2.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eYounger age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e2.05(1.56,2.54)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eBeing female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e0.86(0.58,1.14)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e63.4%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eNon-white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e1.59(1.33,1.85)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e6\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e1.10(0.95,1.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e53.3% \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eComplted college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e0.56(0.47,0.66)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e63.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eLong distance from hospital\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e0.71(0.49,0.95)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0..2%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eCancer stage(T3-T4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e1.39(1.08,1.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eMore recent diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e1.31(1.04,1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" width=\"100%\"\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003eTable 3\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp style=\"text-align: center;\"\u003e\u003cstrong\u003ePooled risk factors of self-reported financial toxicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003e\u003cstrong\u003eRisk factors\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of include studies\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026beta;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(95%CI)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eP\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003eI\u0026sup2;(%)\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eLow income\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e10\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e5.66(2.78-8.53)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e95.1%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-2.90(-5.71,-0.63)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e75.7%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eSupplemental insurance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e1.29(- 1.39,3.97)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e76.8%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eGreater annual OOP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-4.26(-6.95,-1.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eOlder age\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e0.34(0.12,0.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e80.3%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eBeing female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-0.81(-2.03,0.41)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.195\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eNon-white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-2.19(-8.12,3.73)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.261\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e77.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eUnmarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-1.84(-5.13,1.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e74.7% \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eComplted college\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e0.59(-1.40,2.58)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.559\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eCancer stage(T3-T4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-4.74(-6.90,-2.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e0.0%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd width=\"27.741935483870968%\"\u003e\n \u003cp\u003eMore inpatient admission\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"20.161290322580644%\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"21.29032258064516%\"\u003e\n \u003cp\u003e-2.36(-7.61,2.89)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"14.35483870967742%\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd width=\"16.451612903225808%\"\u003e\n \u003cp\u003e82.9%\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\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":"Financial stress, Prevalence, Risk factors, Cancer survivor, Review","lastPublishedDoi":"10.21203/rs.3.rs-1383681/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-1383681/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground: \u003c/strong\u003eSimilar to the side effects of cancer treatment，financial toxicity can affect the quality of life of patients, which has attracted increasing attention in the field of oncology. Despite the fact that the estimated prevalence and risk factors of financial toxicity are widely reported, these results have not been synthesized.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eObjectives:\u003c/strong\u003e This review aimed to systematically assess the prevalence and risk factors of self-reported financial toxicity.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eDesign: \u003c/strong\u003eSystematic review and meta-analysis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eData Sources:\u003c/strong\u003e A computer search of English literature using the database of PubMed, EMBASE, Web of Science, PsycINFO, CHINAHL, and reference list of the included articles between 2010 and September 2021. The observational studies that reported the prevalence or risk factors of financial toxcity used subjective measures will be included.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e A systematic review was guided by the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) statement. The risk of bias was assessed by the NIH observational cohort and cross-sectional study quality assessment tool. The data were extracted by two reviewers and listed in a descriptive table for meta-analysis.\u003c/p\u003e\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e In the 22 studies available for the meta-analysis, the pooled prevalence of financial toxicity was estimated to be 45% (95% CI: 38% to 53%, I\u003csup\u003e2\u003c/sup\u003e = 97.3%, P \u0026lt; 0.001), which was based on a random-effects model. The pooled analysis identified 9 potential risk factors of financial toxicity(7 in β and 8 in OR) : low income (OR = 2.48, 95% CI: 1.72 to 3.24, I\u003csup\u003e2\u003c/sup\u003e =3.1%, P \u0026lt; 0.001), greater annual OOP(β = -4.26, 95% CI: -6.95 to -1.57, I\u003csup\u003e2\u003c/sup\u003e =0%, P=0.002), younger age(OR = 2.05, 95% CI: 1.56 to 2.54, I\u003csup\u003e2\u003c/sup\u003e =0%, P \u0026lt; 0.001), no private insurance(OR = 1.69, 95% CI: 1.02 to 2.37, I\u003csup\u003e2\u003c/sup\u003e =0%, P \u0026lt; 0.001), unmarried(OR = 1.10, 95% CI: 0.95 to 1.25, I\u003csup\u003e2\u003c/sup\u003e =53,3%, P \u0026lt; 0.001), non-white(OR = 1.59, 95% CI: 1.33 to 1.85, I\u003csup\u003e2\u003c/sup\u003e =0%, P \u0026lt; 0.001), advanced cancer(β = -4.74, 95% CI: -6.90 to -2.57, I\u003csup\u003e2\u003c/sup\u003e =0%, P \u0026lt; 0.001), unemployed(β = -2.90, 95% CI: -5.71 to -0.63, I\u003csup\u003e2\u003c/sup\u003e =75,7%, P \u0026lt; 0.001), more recent diagnosis(OR = 1.31, 95% CI: 1.04 to 1.57, I\u003csup\u003e2\u003c/sup\u003e =0%, P \u0026lt; 0.001). \u003c/p\u003e\u003cp\u003e\u003cstrong\u003eConclusion \u003c/strong\u003eThis systematic review found a pooled prevalence of self-reported financial toxicity of 45%. Low income, greater annual OOP, younger age, unmarried, unemployed, non-white, no private insurance, advanced cancer, and more recent diagnosis constituted risk factors for self-reported financial toxicity. The Research on risk factors for financial toxicity can provide a theoretical basis for nursing staff to evaluate and intervene in the financial toxicity among cancer survivors.\u0026nbsp;\u003c/p\u003e","manuscriptTitle":"Prevalence and risk factors of self-reported financial toxicity in cancer survivors: A systematic review and meta-analysis","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2022-03-21 19:58:09","doi":"10.21203/rs.3.rs-1383681/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":"2910ca57-13a4-47f8-a2e2-353474ac09db","owner":[],"postedDate":"March 21st, 2022","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2022-04-12T02:57:07+00:00","versionOfRecord":[],"versionCreatedAt":"2022-03-21 19:58:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-1383681","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-1383681","identity":"rs-1383681","version":["v1"]},"buildId":"7rjqhiLT3MXkJMwkYKINL","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}