Is There a Difference in The “Out-Of-Pocket” Costs of Cancer Treatment When Comparing Patients From The Brazilian National Health System With Patients Enrolled in Clinical Research Protocols?

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Thiago Artioli, Karine Corcione Turke, Aline Hernandez Marquez Sarafyan, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-807102/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 Introduction: Economic burden of cancer treatment does not fall only on the Brazilian National Health System (“SUS”) but also on patients. Nonreimbursed indirect costs include noncovered oral medications, food, transportation, and others. Our study compares out-of-pocket costs of cancer treatment between patients from the SUS and patients enrolled in research protocols. Methods Observational, cross-sectional and analytical study conducted in 2021. Patients undergoing chemotherapy were divided into 2 groups: patients from a tertiary hospital affiliated with the SUS and patients enrolled in research protocols at a research center. The primary outcome was the evaluation of out-of-pocket costs using a socioeconomic questionnaire to identify the cost and time spent by patients during treatment. This study was approved by the Research Ethics Committee. Results 195 patients were included, of whom 165 (84.6%) were treated by the SUS and 30 (15.4%) by research protocols. Of the total, 61% were female, and the mean age of the patients was 57 years. The median total out-of-pocket costs of SUS patients was Brazilian reais (R $ ) 453.80 (US $ 78.92), and that of patients who were enrolled in research protocols was R $ 448.00 (US $ 77.91) (P = 0.317). A comparison of the groups by multivariate analysis showed that only the time spent by patients on chemotherapy and radiotherapy was significantly different, being higher in the SUS group (OR 2.58, 95% CI 1.03–6.50). Conclusion Total out-of-pocket spending by SUS patients is similar in magnitude to that by patients in research protocols, although the reasons for the spending are different. Critical Care & Emergency Medicine Cancer Biology Oncology Neoplasms Costs SUS Research protocols Chemotherapy. Introduction The World Health Organization (WHO), through the International Agency for Research on Cancer, reports that in 2020, more than 19 million new cases of cancer were recorded worldwide, considering all ages and sexes [ 1 ]. In addition, projections indicate that cancer will become the leading cause of death in the world, surpassing cardiovascular disease [ 2 ]. The increased incidence of cancer reflects a combination of factors, such as population growth and aging, in addition to social and economic development [ 3 ]. Coupled with the increased incidence of cancer is an increase in the direct cost of the disease, which involves prevention, diagnosis, treatment and follow-up [ 4 ]. In Brazil, between 1999 and 2015, spending related only to cancer treatment increased from R $ 470 million (US $ 81.7 million) to R $ 3.3 billion (US $ 573.9 million) [ 5 ]. In the United States in 2020, cancer was the second highest health cost, behind only cardiovascular disease [ 6 ]. Although the Brazilian National Health System (SUS, acronym in Portuguese) and other cancer research institutions can fully fund the treatment of patients with cancer [ 7 ], the economic burden of the disease also includes additional costs for patients, which increases their financial concerns and that of their relatives [ 8 ]. These costs, called indirect or out-of-pocket costs [ 9 ], can be basic, for example, transportation, food and medications for symptom control, or complex, for example, economic losses related to loss of income due to treatment. The analysis of the out-of-pocket costs of cancer treatment is extremely important because these costs can be extremely burdensome and can reduce the quality of life of patients and their caregivers during and after treatment [ 6 ]. Despite the magnitude of out-of-pocket costs, there is still little description in the literature of the components making up these costs and the impact on these costs when comparing patients covered by the SUS and by research protocols [ 6 ]. Thus, the aim of our study is to characterize and investigate the differences between the out-of-pocket costs of patients undergoing cancer treatment, comparing such costs between patients in the SUS and those enrolled in research protocols. Methods Study design This is a cross-sectional study that evaluates the out-of-pocket costs of patients undergoing cancer treatment, comparing patients covered by the SUS and patients enrolled in research protocols. We created a database with data from questionnaires answered by patients between November 2020 and February 2021. The study was conducted at Hospital das Clínicas de São Bernardo do Campo and at the Research Center for Hematology and Oncology (CEPHO, acronym in Portuguese), both associated services of the University Center of the School of Medicine of the ABC (FMABC, acronym in Portuguese) located in Santo André, São Paulo, Brazil. Participants Nonselected patients older than 18 years with a confirmed diagnosis of malignant neoplasia who were undergoing active cancer treatment (chemotherapy and/or radiotherapy), who adequately completed the questionnaires, and who agreed to participate in the study by signing the informed consent form were included in the study. Patients were included at 2 locations: Patients treated through the SUS at Hospital das Clínicas de São Bernardo do Campo; and Patients enrolled in research protocols at CEPHO. If the patients met the inclusion criteria, no exclusion criteria were applied. Questionnaires and study variables Our cross-sectional study was based on the application of 2 questionnaires. The epidemiological characteristics of the patients were obtained from the first applied questionnaire. It included demographic data such as sex, age, race, marital status, education level, occupation, origin, comorbidities and medications used and socioeconomic factors such as type of occupation, monthly income, housing and transportation. The cost-time questionnaire was the second applied questionnaire and included an evaluation of the amounts spent on transportation, medications, food and supplies and the minutes or hours spent on activities related to cancer treatment not covered by the SUS. With this questionnaire, we calculated the costs not covered by the SUS or by research protocols (known as indirect or out-of-pocket costs) of patients with cancer incurred during treatment. The currency considered in the questionnaires was the Brazilian real (R $ ), and the Brazilian minimum wage in 2021 was used as the unit of measurement. The values in Brazilian reais were then converted into US dollars (US $ ) based on the exchange rate in February 2021 (R $ 5.75 = US $ 1.00), the date of the final data collection. The following points explain how the variables were calculated in Brazilian reais: Time: We converted time into money by calculating the mean hourly wage based on the mean number of minimum wages received by patients, number of days in the month and hours of work per month. We assumed that the work week was a maximum of 40 hours and that individuals worked 4 weeks per month. Hours were converted into reais so that we could represent the hours spent as part of the total additional costs. Transportation: For patients who used a car, the cost was calculated as the product of the distance (in kilometers) from their residence to certain places (hospital, pharmacy and health center) and the cost of the fuel used in 2021 in Brazil. In the case of public transportation (bus, alternative transport), the cost considered was the transport fare multiplied by the number of trips; for taxis, the cost considered was the amount charged by the driver for each trip; and for cyclists or for those who walked, no expense was calculated. Medications: Only the costs of the medications acquired by the patient were added; those provided by health units were not counted. For the calculation, the patient provided the medication name, dosage and amount used per month. For supplies, patients named the supplies and listed the amount spent in the last month related to treatment. Definition of study outcomes The primary outcome chosen to compare patients from the different groups (SUS vs. research protocols) was the total out-of-pocket costs in Brazilian reais. The secondary analysis included stratified variables of the cost-time questionnaire, comparing the 2 groups. Ethics committee approval The study was conducted in accordance with the principles of the Declaration of Helsinki [ 10 ]. The study protocol was approved by the Research Ethics Committee of FMABC University Center (approval number: 30524420.3.0000.0082). We adhered to the STROBE guidelines for observational studies (Supplementary Table 1) [ 11 ]. Statistical analysis The questionnaire responses were collected and tabulated in an anonymous fashion in Microsoft Excel, creating a database, and the data were subsequently subjected to statistical analysis. Categorical variables are presented as numbers and percentages (frequencies) and were analyzed using Fisher's exact test. Continuous variables are presented as means and standard deviations or as medians and interquartile ranges depending on normality, as determined by the Shapiro-Wilk test. Normal continuous variables were analyzed by Student’s t-test. Nonnormally distributed continuous variables were analyzed using the Mann-Whitney test. For the multivariate analysis, we calculated the 95% confidence intervals (95% CIs) and P values using multivariate logistic regression to adjust for confounding variables. Clinical, demographic and socioeconomic variables significant in the univariate analysis were included in the multivariate model. Based on the number of events and the consensus of 10 events for each independent variable, we considered all variables with P < 0.05 in the univariate analysis. The level of significance was set at 95% (P < 0.05). Statistical analyses were performed using R (R Core Team, 2020 - R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/ ). Results Sociodemographic characteristics of the study population Between November 2020 and February 2021, 195 participants were included in the study (Table 1 ). Among the 195 patients, 165 were in the SUS group, and 30 were in the research protocol (RP) group. The mean age of patients in the SUS group was 56 ± 11 years, and the mean age of patients in the RP group was 60 ± 14 years. In the SUS group, 106 (64.2%) were female, and 59 (35.8%) were male; in the RP group, 13 (43.3%) were female, and 17 (56.7%) were male. Hypertension and diabetes were the most prevalent comorbidities in both groups. Regarding cancer treatment through the SUS, cancer affecting the breast as the primary organ was the most frequent, present in 40 patients (24.2%), followed by gastrointestinal (large intestine) cancer in 28 patients (17%). In this same group, most participants had been diagnosed with cancer less than 1 year prior (60.6%) and had no need to undergo radiotherapy as treatment (73.3%). In the RP group, breast (30%) and prostate (16.7%) cancer were the most prevalent, with only 20% of patients diagnosed less than 1 year prior and 76.7% with no need for radiotherapy. Table 1 Sociodemographic and clinical characteristics of the 195 patients undergoing cancer treatment. All patients n = 195 n (%) SUS n = 165 n (%) Research protocols n = 30 n (%) P-value Sex Female 119 (61%) 106 (64.2%) 13 (43.3%) 0.041 Male 76 (38.9%) 59 (35.8%) 17 (56.7%) Age (mean ± standard deviation) 57 ± 12 56 ± 11 60 ± 14 0.130 Ethnicity Non-white 78 (40%) 64 (61.2%) 14 (46.7%) 0.426 White 117 (60%) 101 (38.8%) 16 (53.3%) Marital status Single 38 (19.5%) 35 (21.2%) 3 (10%) 0.154 Married 110 (56.4%) 87 (52.7%) 23 (76.6%) Divorced 24 (12.3%) 22 (13.3%) 2 (6.7%) Widowed 23 (11.8%) 21 (12.7%) 2 (6.7%) Education level Illiterate 9 (4.6%) 8 (4.8%) 1 (3.3%) 0.577 Incomplete primary 71 (36.4%) 63 (38.2%) 8 (26.7%) Complete primary 18 (9.2%) 16 (9.7%) 2 (6.7%) Incomplete secondary 13 (6.7%) 12 (7.3%) 1 (3.3%) Complete secondary 58 (29.7%) 46 (27.9%) 12 (40%) Incomplete higher 7 (3.6%) 5 (3%) 2 (6.7%) Complete higher 19 (9.8%) 15 (9.1%) 4 (13.3%) Occupation Employed 68 (34.9%) 56 (34%) 12 (40%) 0.151 Unemployed 67 (33.8%) 62 (37.5%) 5 (16.7%) Retired 60 (30.8%) 47 (28.5%) 13 (43.3%) Alcohol consumption Yes 15 (7.7%) 14 (8.5%) 1 (3.3%) 0.475 Smoking Smoker 16 (8.2%) 16 (9.7%) 0 (0%) 0.154 Former smoker 78 (40%) 63 (38.2%) 15 (50%) Medications used (excluding cancer medications) 1 medication 49 (25.1%) 41 (24.8%) 8 (26.7%) 0.919 2 medications 40 (20.5%) 34 (20.6%) 6 (20%) ≥ 3 medications 45 (23.1%) 37 (22.4%) 8 (26.7%) Comorbidities Hypertension 66 (33.8%) 54 (32.7%) 12 (40%) 0.529 Diabetes 27 (13.8%) 21 (12.7%) 6 (20%) 0.386 Dyslipidemia 7 (3.6%) 7 (4.2%) 0 (0%) 0.598 Depression 7 (3.6%) 6 (3.6%) 1 (3.3%) 1.0 BMI (median, interquartile range) 26.45 (23.18–30.47) 26.02 (22.95–30.22) 27.4 (25.64–31.24) 0.041 Home Owned 140 (71.8%) 119 (72.1%) 21 (70%) < 0.001 Rented 41 (21%) 39 (23.6%) 2 (6.7%) Financed 14 (7.2%) 7 (4.2%) 7 (23.3%) Primary organ Large intestine 28 (14.4%) 28 (17%) 0 (0%) 0.003 Breast 49 (25.1%) 40 (24.2%) 9 (30%) Prostate 7 (3.6%) 2 (1.2%) 5 (16.7%) Cervix 4 (2.1%) 4 (2.4%) 0 (0%) Liver 8 (4.1%) 6 (3.6%) 2 (6.7%) Lung 4 (2.1%) 3 (1.8%) 1 (3.3%) Other 29 (14.9%) 27 (16.4%) 2 (6.7%) Time since diagnosis ˂ 6 m 48 (24.6%) 43 (26.1%) 5 (16.7%) 12 m 83 (42.6%) 63 (38.2%) 20 (66.7%) Radiotherapy Yes 51 (26.2%) 44 (26.7%) 7 (23.3%) 0.823 No 144 (73.8%) 121 (73.3%) 23 (76.7%) SUS: National Health System; BMI = body mass index. Cost-time questionnaire and socioeconomic characteristics The median monthly income (in number of minimum wages) of the patients was 1 minimum wage for both groups, with an interquartile range of 1–2.5 minimum wages for the SUS group and 1–4 minimum wages for the RP group. The highest monthly expenditure reported by patients was the same for both the SUS and RP groups: transportation. The SUS group spent a median of R $ 100.00 (US $ 17.39), with a median of 7 monthly trips related to treatment. The RP group spent a median R $ 117.00 (US $ 20.35), with a median of 4 monthly treatment-related trips. Another important expense was the number of telephone calls related to cancer treatment, with a median of R $ 50.00 spent per month (US $ 8.70) in the SUS group and a median of R $ 75.00 spent per month (US $ 13.04) in the RP group. The most amount of time spent by patients in cancer treatment was the monthly hours spent in chemotherapy or radiotherapy, with a median of 8 hours (IQR 6.0–12.0) in the SUS group and 4 hours (IQR 0.0–12.0) in the RP group. The data calculated from the cost-time questionnaire are provided in Table 2 . Table 2 Cost-time questionnaire: impact of costs on patients undergoing cancer treatment. All patients n = 195 SUS n = 165 Research protocols n = 30 P-value Monthly income (n of minimum wages) 1.0 (1.0-2.5) 1.0 (1.0-2.5) 1.0 (1.0–4.0) 0.026 Means of transport Own car 163 (83.6%) 138 (83.6%) 25 (83.3%) 1.0 Public 32 (16.4%) 27 (16.4%) 5 (16.7%) Number of trips 7.0 (4.0–10.0) 7.0 (5.0–12.0) 4.0 (2.25-8.0) 0.003 Spending on transportation (US$) 17.39 (2.96–39.13) 13.91 (1.74–41.74) 20.35 (9.57–34.78) 0.230 General food expenditure (US$) 0.0 (0.0-5.57) 0.0 (0.0-5.22) 2.09 (0.0-6.74) 0.093 Hotel stay (US$) 0 (0.0–0.0) 0 (0.0–0.0) 0 (0.0–0.0) NA Spending on phone (US$) 9.91 (4.78–14.43) 8.70 (3.48–13.74) 13.04 (8.35–22.17) 0.012 Spending on private medication (US$) 0.52 (0.0-17.39) 2.26 (0.0-17.39) 0.0 (0.0-10.13) 0.066 Spending on alternative therapies (US$) 0 (0.0–0.0) 0 (0.0–0.0) 0 (0.0–0.0) NA Time spent on consultations (hours) 1.0 (2.0–4.0) 2.0 (1.0–4.0) 1.0 (0.5–6.5) 0.345 Time spent on CT/RT (hours) 8.0 (5.0–12.0) 8.0 (6.0–12.0) 4.0 (0.0–12.0) < 0.001 Time spent purchasing medication (minutes) 15.0 (0.0–30.0) 20.0 (0.0–30.0) 5.5 (0.0–20.0) 0.052 Time spent on other activities (hours) 0.0 (0.0–1.0) 0.0 (0.0-0.5) 0.25 (0.0-2.75) 0.006 Hourly cost per individual (US$) 1.20 (1.20–2.99) 1.20 (1.20–2.99) 2.99 (1.20–4.78) 0.026 Cost-time spent on consultations (US$) 2.99 (0.61–9.57) 2.99 (0.60–7.17) 2.69 (1.20-28.25) 0.345 Cost-time spent on CT/RT (US$) 14.35 (3.59–29.59) 14.35 (4.78–28.70) 9.57 (0.0-32.28) 0.185 Cost-time spent purchasing medications (US$) 0.40 (0.0-0.90) 0.40 (0.0-0.90) 0.13 (0.0-0.71) 0.464 Cost-time spent on other activities (US$) 0 (0.0–0.0) 0 (0.0–0.0) 0.0 (0.0-4.48) N/A Total cost (US$) 78.92 (42.35–165.60) 78.92 (41.90-155.80) 77.91 (50.57-195.44) 0.317 Numerical variables are presented as medians and interquartile ranges (non-parametric distribution). The values were converted from reais to dollars, as explained in the methods section. SUS = National Health System; CT = chemotherapy; RT = radiotherapy. Primary outcome: total out-of-pocket costs In the SUS group, the interquartile range for the total monthly out-of-pocket expenditure by patients was R $ 240.90–895.90 (US $ 41.90–155.81), with a median of R $ 453.8 (US $ 78.92). In the RP group, the interquartile range for the total monthly out-of-pocket expenditure by patients was R $ 290.80–1123.80 (US $ 50.57–195.44), with a median of R $ 448.00 (US $ 77.91). In the univariate analysis, there was no significant difference between the total out-of-pocket expenditure when comparing the SUS and RP groups (P = 0.317). After adjusting for confounders in the multivariate analysis (Table 3 ), only the time spent by patients on chemotherapy and radiotherapy was significantly different, being higher in the SUS group (OR 2.58, 95% CI 1.03–6.50, P = 0.043). Table 3 Multivariate analysis by binary logistic regression. Adjusted OR (95% CI) P value Treatment center Female sex 12.67 (0.0 – inf) 0.999 Time since diagnosis 6–12 months 0.037 (0.0–3.47) 0.155 > 12 months 0.213 (0.01–4.33) 0.315 Primary organ Large intestine Ref Ref Breast 0.0 (0.0 – inf) 0.999 Prostate 0.0 (0.0 – inf) 0.997 Cervix 0.012 (0.0 – inf) 0.999 Liver 297.02 (0.0 – inf) 0.999 Lung 0.279 (0.0 – inf) 1.0 Home Rented 0.176 (0.0–7.37) 0.362 Financed 0.0 (0.0–10.37) 0.106 Number of trips 0.556 (0.29–1.08) 0.083 Telephone costs 0.996 (0.97–1.02) 0.717 Time spent on CT/RT 2.586 (1.03–6.50) 0.043 Time spent on other activities 0.963 (0.89–1.05) 0.379 Discussion Cancer is an important cause of mortality worldwide, with a trend that seems to only increase. Along with the growth in morbidity and mortality, the economic burden of direct and indirect costs is also increasing. This study aimed to characterize the out-of-pocket costs of cancer treatment incurred by patients during treatment, either through the SUS or research protocols. Our study population was mostly female (61%), with a mean age older than 50 years, findings that are consistent with those in other studies involving patients with cancer [ 6 , 12 – 19 ]. There was greater participation by individuals who reported being white (60%), although the majority of the Brazilian population self-reports as black [ 20 ]. Based on the literature, the main comorbidities of patients with cancer are hypertension, diabetes and dyslipidemia, consistent with the results of our study [ 6 ]. Regarding cancer characteristics, breast cancer is the most prevalent among patients both in our study and in the literature, but the time since diagnosis differs, and in our study, most patients had been diagnosed more than 12 months prior (42.6%) [ 12 , 13 , 20 ]. In the analysis of the total out-of-pocket costs incurred by patients, the mean final value, i.e., R $ 453.80 (US $ 78.92) per month, was lower than that found in a similar study conducted in the United States, in which the monthly mean was approximately R $ 1071.00 (based on the dollar exchange rate at the time) [ 21 ]. In addition, the total monthly expenditure found in this study was also substantially lower than that found in another study conducted in northern India in which the mean out-of-pocket expenditure by patients with head and neck cancer was R $ 2123.86 (US $ 369.37) based on the rupee/real exchange rate in 2019 [ 14 ]. This difference may be explained by the type of cancer investigated, indicating that there is a difference in spending not only between different regions but also between different types of cancer. When comparing our results with the Brazilian reality, 43.4% (R $ 1045.00/US $ 181.74) of 1 minimum wage in 2020 was spent by patients on out-of-pocket expenses; however, in another Brazilian study, the total out-of-pocket spending represented 78.4% of the minimum wage at the time (2018) [ 6 ], indicating that even though the value is high, the percentage found in this study was not higher than that in 2018. Stratifying the out-of-pocket costs surveyed, the transportation expenditure was the highest, approximately R $ 100.00 (US $ 17.39) per month, a finding similar to that in another Brazilian study and to that in a Canadian review that also found transportation among the top 4 highest expenses for patients with cancer [ 21 ]. This finding indicates that transportation to treatment-related commitments (consultations, chemotherapy, radiotherapy, and laboratory tests, among others) is a critical part of out-of-pocket costs and, thus, where patients would benefit the most from receiving aid. No significant difference was found between the SUS and RP groups regarding the means of transportation, and the proportion of patients who used cars or public transportation was similar in each group; however, compared to previous studies conducted in Brazil, in this study, there was an increase in the proportion of patients who used their own car [ 12 ]. Despite the similarity in the use of means of transportation and the finding that SUS patients make more trips, the RP patients had a 46.25% higher mean transportation expenditure. Interestingly, the 2 groups spent more on transportation than did patients in a previous study [ 17 ] but less on transportation than did patients in studies from other regions and countries, indicating perhaps greater difficulty in accessing health services in these locations [ 6 , 20 ]. However, we cannot exclude the roles of inflation and our setting as causes of the differences in transportation costs between studies conducted at different times. The results of the multivariate analysis show that there was no significant difference between the SUS and RP groups. This may be due to the balance between some expenses among the evaluated costs. For example, while the RP group spent more on telephones, the SUS group had higher expenses related to the number of trips. Differently from another study conducted on the costs incurred by cancer patients that found that employed patients incurred higher costs, in this study, patient occupation was not significant in determining the difference between costs. In contrast, education level, type of cancer, sex, age and ethnicity were not significant either in our study or in another study conducted in Brazil [ 6 ]. Because of the observational nature of our study, the limitations include the impossibility of establishing cause and effect relationships and include the possible presence of biases and confounding factors. Our questionnaires, especially those related to cost-time, required that patients remember various expenses and situations, potentially introducing recall bias. Additionally, the different proportion of patients from the SUS and RP may have influenced the results, but unfortunately, in the context of the COVID-19 pandemic, several patients were lost to follow-up, especially in the RP group. Last, our patient sample represents only a portion of patients undergoing cancer treatment, which includes patients from several other health centers that may have their own patient protocols and services. Conclusion Although research protocols reduce the costs related to cancer treatment for the SUS and other paying sources, there was no impact on the out-of-pocket costs incurred by the patients. These out-of-pocket costs represent an important portion of the costs incurred by patients undergoing cancer treatment through the SUS and those enrolled in research protocols. The data reported here suggest that government aid in the form of a grant of approximately 1 minimum wage for patients diagnosed with cancer in our setting could mitigate these out-of-pocket costs. Declarations Funding The authors did not receive support from any organization for the submitted work. Authors Contribution All authors were part in the designing, data collection, data analysis and writing of this article, and all have approved the final version for publication. Conflicts of Interest The authors have no relevant financial or non-financial interests to disclose related to this work. Availability of Data and Material Every available data and material is declared in the manuscript text. Ethics Approval The study was conducted in accordance with the principles of the Declaration of Helsinki [10]. The study protocol was approved by the Research Ethics Committee of FMABC University Center (approval number: 30524420.3.0000.0082). Consent to Participate Written informed consent was obtained from all individual participants included in the study. Consent for Publication Not applicable. References World Health Organization. GLOBOCAN 2021. Cancer Today. Disponível em . Acesso em: 21 de maio de 2021. World Health Organization. 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Lancet 370(9596):1453–1457 Koskinen J-P, Färkkilä N, Sintonen H, Saarto T, Taari K, Roine RP (2019 Jul) The association of financial difficulties and out-of-pocket payments with health-related quality of life among breast, prostate and colorectal cancer patients. Acta Oncol 3(7):1062–1068 58( Dehghan M, Jazinizade M, Malakoutikhah A, Madadimahani A, Iranmanesh MH, Oghabian S et al (2020) Stress and Quality of Life of Patients with Cancer: The Mediating Role of Mindfulness. J Oncol 2020:3289521 Chauhan AS, Prinja S, Ghoshal S, Verma R (2019 Feb) Economic Burden of Head and Neck Cancer Treatment in North India. Asian Pac J Cancer Prev 26(2):403–409 20( Callahan C, Brintzenhofeszoc K (2015) Financial Quality of Life for Patients With Cancer: An Exploratory Study. J Psychosoc Oncol 33(4):377–394 Smith GL, Lopez-Olivo MA, Advani PG, Ning MS, Geng Y, Giordano SH et al (2019) Financial Burdens of Cancer Treatment: A Systematic Review of Risk Factors and Outcomes. J Natl Compr Canc Netw. 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Health Soc Care Community 27(5):e622–e636 Supplementary Files supplementarytable1outofpocketcosts.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. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-807102","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":49215569,"identity":"e586dd2c-2f6a-4df7-a145-570f3488eb24","order_by":0,"name":"Thiago 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Monteiro","email":"","orcid":"","institution":"Medical Faculty of the ABC: Faculdade de Medicina do ABC","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Pamela","middleName":"dos Santos","lastName":"Monteiro","suffix":""},{"id":49215579,"identity":"31dfb2b6-7e7c-4859-9971-6300f510454f","order_by":10,"name":"Camille Corcione Turke","email":"","orcid":"","institution":"Medical Faculty of the ABC: Faculdade de Medicina do ABC","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Camille","middleName":"Corcione","lastName":"Turke","suffix":""},{"id":49215580,"identity":"7494ec0b-e5ce-45a3-b6f1-1f7ea9f6781a","order_by":11,"name":"Daniel de Iracema Cubero","email":"","orcid":"","institution":"Medical Faculty of the ABC: Faculdade de Medicina do ABC","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Daniel","middleName":"de Iracema","lastName":"Cubero","suffix":""},{"id":49215581,"identity":"e2e46037-20f2-4a46-8da4-b9d8f7791f2f","order_by":12,"name":"Cláudia Vaz de Melo Sette","email":"","orcid":"","institution":"Medical Faculty of the ABC: Faculdade de Medicina do ABC","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Cláudia","middleName":"Vaz de Melo","lastName":"Sette","suffix":""},{"id":49215582,"identity":"18f4daa3-678e-49cb-86bf-0de407ee64c4","order_by":13,"name":"Auro del Giglio","email":"","orcid":"","institution":"Medical Faculty of the ABC: Faculdade de Medicina do ABC","correspondingAuthor":false,"submittingAuthor":false,"prefix":"","firstName":"Auro","middleName":"del","lastName":"Giglio","suffix":""}],"badges":[],"createdAt":"2021-08-13 01:39:14","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-807102/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-807102/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":16439471,"identity":"8819495a-1fc0-4372-af44-51333496490d","added_by":"auto","created_at":"2021-12-14 14:55:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":717451,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-807102/v1/75764db0-302f-4a5a-b8f1-77294779face.pdf"},{"id":13014782,"identity":"e12ada36-eb18-41a2-86cb-a2facfd5d16a","added_by":"auto","created_at":"2021-09-02 14:12:32","extension":"docx","order_by":21,"title":"","display":"","copyAsset":false,"role":"supplement","size":20462,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarytable1outofpocketcosts.docx","url":"https://assets-eu.researchsquare.com/files/rs-807102/v1/413f675f846b873fadb952ac.docx"}],"financialInterests":"","formattedTitle":"\u003cp\u003eIs There a Difference in The “Out-Of-Pocket” Costs of Cancer Treatment When Comparing Patients From The Brazilian National Health System With Patients Enrolled in Clinical Research Protocols?\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe World Health Organization (WHO), through the International Agency for Research on Cancer, reports that in 2020, more than 19\u0026nbsp;million new cases of cancer were recorded worldwide, considering all ages and sexes [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. In addition, projections indicate that cancer will become the leading cause of death in the world, surpassing cardiovascular disease [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. The increased incidence of cancer reflects a combination of factors, such as population growth and aging, in addition to social and economic development [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCoupled with the increased incidence of cancer is an increase in the direct cost of the disease, which involves prevention, diagnosis, treatment and follow-up [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In Brazil, between 1999 and 2015, spending related only to cancer treatment increased from R\u003cspan\u003e$\u003c/span\u003e 470\u0026nbsp;million (US\u003cspan\u003e$\u003c/span\u003e 81.7\u0026nbsp;million) to R\u003cspan\u003e$\u003c/span\u003e 3.3\u0026nbsp;billion (US\u003cspan\u003e$\u003c/span\u003e 573.9\u0026nbsp;million) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In the United States in 2020, cancer was the second highest health cost, behind only cardiovascular disease [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eAlthough the Brazilian National Health System (SUS, acronym in Portuguese) and other cancer research institutions can fully fund the treatment of patients with cancer [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], the economic burden of the disease also includes additional costs for patients, which increases their financial concerns and that of their relatives [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. These costs, called indirect or out-of-pocket costs [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], can be basic, for example, transportation, food and medications for symptom control, or complex, for example, economic losses related to loss of income due to treatment. The analysis of the out-of-pocket costs of cancer treatment is extremely important because these costs can be extremely burdensome and can reduce the quality of life of patients and their caregivers during and after treatment [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eDespite the magnitude of out-of-pocket costs, there is still little description in the literature of the components making up these costs and the impact on these costs when comparing patients covered by the SUS and by research protocols [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. Thus, the aim of our study is to characterize and investigate the differences between the out-of-pocket costs of patients undergoing cancer treatment, comparing such costs between patients in the SUS and those enrolled in research protocols.\u003c/p\u003e"},{"header":"Methods","content":"\u003cdiv class=\"Section2\" id=\"Sec3\"\u003e\n \u003ch2\u003eStudy design\u003c/h2\u003e\n \u003cp\u003eThis is a cross-sectional study that evaluates the out-of-pocket costs of patients undergoing cancer treatment, comparing patients covered by the SUS and patients enrolled in research protocols. We created a database with data from questionnaires answered by patients between November 2020 and February 2021. The study was conducted at Hospital das Cl\u0026iacute;nicas de S\u0026atilde;o Bernardo do Campo and at the Research Center for Hematology and Oncology (CEPHO, acronym in Portuguese), both associated services of the University Center of the School of Medicine of the ABC (FMABC, acronym in Portuguese) located in Santo Andr\u0026eacute;, S\u0026atilde;o Paulo, Brazil.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec4\"\u003e\n \u003ch2\u003eParticipants\u003c/h2\u003e\n \u003cp\u003eNonselected patients older than 18 years with a confirmed diagnosis of malignant neoplasia who were undergoing active cancer treatment (chemotherapy and/or radiotherapy), who adequately completed the questionnaires, and who agreed to participate in the study by signing the informed consent form were included in the study. Patients were included at 2 locations:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003ePatients treated through the SUS at Hospital das Cl\u0026iacute;nicas de S\u0026atilde;o Bernardo do Campo; and\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003ePatients enrolled in research protocols at CEPHO.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n \u003cp\u003eIf the patients met the inclusion criteria, no exclusion criteria were applied.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec5\"\u003e\n \u003ch2\u003eQuestionnaires and study variables\u003c/h2\u003e\n \u003cp\u003eOur cross-sectional study was based on the application of 2 questionnaires. The epidemiological characteristics of the patients were obtained from the first applied questionnaire. It included demographic data such as sex, age, race, marital status, education level, occupation, origin, comorbidities and medications used and socioeconomic factors such as type of occupation, monthly income, housing and transportation.\u003c/p\u003e\n \u003cp\u003eThe cost-time questionnaire was the second applied questionnaire and included an evaluation of the amounts spent on transportation, medications, food and supplies and the minutes or hours spent on activities related to cancer treatment not covered by the SUS. With this questionnaire, we calculated the costs not covered by the SUS or by research protocols (known as indirect or out-of-pocket costs) of patients with cancer incurred during treatment. The currency considered in the questionnaires was the Brazilian real (R\u003cspan\u003e$\u003c/span\u003e), and the Brazilian minimum wage in 2021 was used as the unit of measurement. The values in Brazilian reais were then converted into US dollars (US\u003cspan\u003e$\u003c/span\u003e) based on the exchange rate in February 2021 (R\u003cspan\u003e$\u003c/span\u003e 5.75\u0026thinsp;=\u0026thinsp;US\u003cspan\u003e$\u003c/span\u003e 1.00), the date of the final data collection.\u003c/p\u003e\n \u003cp\u003eThe following points explain how the variables were calculated in Brazilian reais:\u003c/p\u003e\n \u003cul\u003e\n \u003cli\u003e\n \u003cp\u003eTime: We converted time into money by calculating the mean hourly wage based on the mean number of minimum wages received by patients, number of days in the month and hours of work per month. We assumed that the work week was a maximum of 40 hours and that individuals worked 4 weeks per month. Hours were converted into reais so that we could represent the hours spent as part of the total additional costs.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eTransportation: For patients who used a car, the cost was calculated as the product of the distance (in kilometers) from their residence to certain places (hospital, pharmacy and health center) and the cost of the fuel used in 2021 in Brazil. In the case of public transportation (bus, alternative transport), the cost considered was the transport fare multiplied by the number of trips; for taxis, the cost considered was the amount charged by the driver for each trip; and for cyclists or for those who walked, no expense was calculated.\u003c/p\u003e\n \u003c/li\u003e\n \u003cli\u003e\n \u003cp\u003eMedications: Only the costs of the medications acquired by the patient were added; those provided by health units were not counted. For the calculation, the patient provided the medication name, dosage and amount used per month. For supplies, patients named the supplies and listed the amount spent in the last month related to treatment.\u003c/p\u003e\n \u003c/li\u003e\n \u003c/ul\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec6\"\u003e\n \u003ch2\u003eDefinition of study outcomes\u003c/h2\u003e\n \u003cp\u003eThe primary outcome chosen to compare patients from the different groups (SUS vs. research protocols) was the total out-of-pocket costs in Brazilian reais. The secondary analysis included stratified variables of the cost-time questionnaire, comparing the 2 groups.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec7\"\u003e\n \u003ch2\u003eEthics committee approval\u003c/h2\u003e\n \u003cp\u003eThe study was conducted in accordance with the principles of the Declaration of Helsinki [\u003cspan class=\"CitationRef\"\u003e10\u003c/span\u003e]. The study protocol was approved by the Research Ethics Committee of FMABC University Center (approval number: 30524420.3.0000.0082).\u003c/p\u003e\n \u003cp\u003eWe adhered to the STROBE guidelines for observational studies (Supplementary Table\u0026nbsp;1) [\u003cspan class=\"CitationRef\"\u003e11\u003c/span\u003e].\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec8\"\u003e\n \u003ch2\u003eStatistical analysis\u003c/h2\u003e\n \u003cp\u003eThe questionnaire responses were collected and tabulated in an anonymous fashion in Microsoft Excel, creating a database, and the data were subsequently subjected to statistical analysis. Categorical variables are presented as numbers and percentages (frequencies) and were analyzed using Fisher\u0026apos;s exact test. Continuous variables are presented as means and standard deviations or as medians and interquartile ranges depending on normality, as determined by the Shapiro-Wilk test. Normal continuous variables were analyzed by Student\u0026rsquo;s t-test. Nonnormally distributed continuous variables were analyzed using the Mann-Whitney test.\u003c/p\u003e\n \u003cp\u003eFor the multivariate analysis, we calculated the 95% confidence intervals (95% CIs) and P values using multivariate logistic regression to adjust for confounding variables. Clinical, demographic and socioeconomic variables significant in the univariate analysis were included in the multivariate model. Based on the number of events and the consensus of 10 events for each independent variable, we considered all variables with P\u0026thinsp;\u0026lt;\u0026thinsp;0.05 in the univariate analysis.\u003c/p\u003e\n \u003cp\u003eThe level of significance was set at 95% (P\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Statistical analyses were performed using R (R Core Team, 2020 - R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.R-project.org/\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv class=\"Section2\" id=\"Sec10\"\u003e\n \u003ch2\u003eSociodemographic characteristics of the study population\u003c/h2\u003e\n \u003cp\u003eBetween November 2020 and February 2021, 195 participants were included in the study (Table \u003cspan class=\"InternalRef\"\u003e1\u003c/span\u003e). Among the 195 patients, 165 were in the SUS group, and 30 were in the research protocol (RP) group. The mean age of patients in the SUS group was 56\u0026thinsp;\u0026plusmn;\u0026thinsp;11 years, and the mean age of patients in the RP group was 60\u0026thinsp;\u0026plusmn;\u0026thinsp;14 years. In the SUS group, 106 (64.2%) were female, and 59 (35.8%) were male; in the RP group, 13 (43.3%) were female, and 17 (56.7%) were male. Hypertension and diabetes were the most prevalent comorbidities in both groups.\u003c/p\u003e\n \u003cp\u003eRegarding cancer treatment through the SUS, cancer affecting the breast as the primary organ was the most frequent, present in 40 patients (24.2%), followed by gastrointestinal (large intestine) cancer in 28 patients (17%). In this same group, most participants had been diagnosed with cancer less than 1 year prior (60.6%) and had no need to undergo radiotherapy as treatment (73.3%). In the RP group, breast (30%) and prostate (16.7%) cancer were the most prevalent, with only 20% of patients diagnosed less than 1 year prior and 76.7% with no need for radiotherapy.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eSociodemographic and clinical characteristics of the 195 patients undergoing cancer treatment.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;195\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSUS\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;165\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eResearch protocols\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e\n \u003cp\u003en (%)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSex\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (61%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e106 (64.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76 (38.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e59 (35.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17 (56.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAge (mean\u0026thinsp;\u0026plusmn;\u0026thinsp;standard deviation)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57\u0026thinsp;\u0026plusmn;\u0026thinsp;12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56\u0026thinsp;\u0026plusmn;\u0026thinsp;11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60\u0026thinsp;\u0026plusmn;\u0026thinsp;14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.130\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEthnicity\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon-white\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e64 (61.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (46.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.426\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e117 (60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e101 (38.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (53.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMarital status\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSingle\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38 (19.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35 (21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"4\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMarried\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e110 (56.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e87 (52.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (76.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDivorced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (12.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e22 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eWidowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (4.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"7\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncomplete primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71 (36.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComplete primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (9.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncomplete secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (7.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComplete secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (29.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46 (27.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eIncomplete higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eComplete higher\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e19 (9.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (9.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (13.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eOccupation\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eEmployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (34.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (34%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.151\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eUnemployed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (33.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62 (37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRetired\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e60 (30.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (28.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13 (43.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eAlcohol consumption\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (8.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.475\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSmoking\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSmoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (8.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16 (9.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.154\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFormer smoker\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15 (50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMedications used (excluding cancer medications)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 medication\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (25.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (24.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (20.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34 (20.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026ge;\u0026thinsp;3 medications\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e45 (23.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eComorbidities\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e66 (33.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e54 (32.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.529\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDiabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (12.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.386\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDyslipidemia\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.598\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eDepression\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI (median, interquartile range)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.45\u003c/p\u003e\n \u003cp\u003e(23.18\u0026ndash;30.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26.02\u003c/p\u003e\n \u003cp\u003e(22.95\u0026ndash;30.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27.4\u003c/p\u003e\n \u003cp\u003e(25.64\u0026ndash;31.24)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.041\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHome\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOwned\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e140 (71.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e119 (72.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e21 (70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41 (21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (23.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinanced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003ePrimary organ\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (14.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e28 (17%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"7\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49 (25.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e40 (24.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9 (30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (1.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCervix\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6 (3.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3 (1.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime since diagnosis\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e˂ 6 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (26.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"3\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026ndash;12 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (29.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (34.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;12 m\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83 (42.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e63 (38.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20 (66.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eRadiotherapy\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e51 (26.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"2\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e144 (73.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e121 (73.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e23 (76.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003eSUS: National Health System; BMI\u0026thinsp;=\u0026thinsp;body mass index.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cp\u003e\u003cbr\u003e\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec11\"\u003e\n \u003ch2\u003eCost-time questionnaire and socioeconomic characteristics\u003c/h2\u003e\n \u003cp\u003eThe median monthly income (in number of minimum wages) of the patients was 1 minimum wage for both groups, with an interquartile range of 1\u0026ndash;2.5 minimum wages for the SUS group and 1\u0026ndash;4 minimum wages for the RP group. The highest monthly expenditure reported by patients was the same for both the SUS and RP groups: transportation. The SUS group spent a median of R\u003cspan\u003e$\u003c/span\u003e 100.00 (US \u003cspan\u003e$\u003c/span\u003e17.39), with a median of 7 monthly trips related to treatment. The RP group spent a median R\u003cspan\u003e$\u003c/span\u003e 117.00 (US\u003cspan\u003e$\u003c/span\u003e 20.35), with a median of 4 monthly treatment-related trips. Another important expense was the number of telephone calls related to cancer treatment, with a median of R\u003cspan\u003e$\u003c/span\u003e 50.00 spent per month (US \u003cspan\u003e$\u003c/span\u003e8.70) in the SUS group and a median of R\u003cspan\u003e$\u003c/span\u003e 75.00 spent per month (US\u003cspan\u003e$\u003c/span\u003e 13.04) in the RP group.\u003c/p\u003e\n \u003cp\u003eThe most amount of time spent by patients in cancer treatment was the monthly hours spent in chemotherapy or radiotherapy, with a median of 8 hours (IQR 6.0\u0026ndash;12.0) in the SUS group and 4 hours (IQR 0.0\u0026ndash;12.0) in the RP group. The data calculated from the cost-time questionnaire are provided in Table \u003cspan class=\"InternalRef\"\u003e2\u003c/span\u003e.\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab2\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eCost-time questionnaire: impact of costs on patients undergoing cancer treatment.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAll patients\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;195\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSUS\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;165\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eResearch protocols\u003c/p\u003e\n \u003cp\u003en\u0026thinsp;=\u0026thinsp;30\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP-value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMonthly income\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e(n of minimum wages)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 (1.0-2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 (1.0-2.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0 (1.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eMeans of transport\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOwn car\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e163 (83.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e138 (83.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e25 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePublic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e32 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eNumber of trips\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0 (4.0\u0026ndash;10.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7.0 (5.0\u0026ndash;12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0 (2.25-8.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.003\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpending on transportation (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e17.39\u003c/p\u003e\n \u003cp\u003e(2.96\u0026ndash;39.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e13.91\u003c/p\u003e\n \u003cp\u003e(1.74\u0026ndash;41.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e20.35\u003c/p\u003e\n \u003cp\u003e(9.57\u0026ndash;34.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.230\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eGeneral food expenditure (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0-5.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0-5.22)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.09 (0.0-6.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHotel stay (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpending on phone (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e9.91 (4.78\u0026ndash;14.43)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.70 (3.48\u0026ndash;13.74)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13.04 (8.35\u0026ndash;22.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.012\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpending on private medication (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.52 (0.0-17.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.26 (0.0-17.39)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0 (0.0-10.13)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.066\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eSpending on alternative therapies (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNA\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent on consultations (hours)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0 (2.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.0 (1.0\u0026ndash;4.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.0 (0.5\u0026ndash;6.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent on CT/RT (hours)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.0 (5.0\u0026ndash;12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8.0 (6.0\u0026ndash;12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4.0 (0.0\u0026ndash;12.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026lt;\u0026thinsp;0.001\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent purchasing medication (minutes)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e15.0 (0.0\u0026ndash;30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e20.0 (0.0\u0026ndash;30.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.5 (0.0\u0026ndash;20.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.052\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTime spent on other activities (hours)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0\u0026ndash;1.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0-0.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.25 (0.0-2.75)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.006\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eHourly cost per individual (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20 (1.20\u0026ndash;2.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.20 (1.20\u0026ndash;2.99)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.99 (1.20\u0026ndash;4.78)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.026\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost-time spent on consultations (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.99 (0.61\u0026ndash;9.57)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2.99 (0.60\u0026ndash;7.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.69 (1.20-28.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.345\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost-time spent on CT/RT (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.35\u003c/p\u003e\n \u003cp\u003e(3.59\u0026ndash;29.59)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14.35\u003c/p\u003e\n \u003cp\u003e(4.78\u0026ndash;28.70)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9.57\u003c/p\u003e\n \u003cp\u003e(0.0-32.28)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.185\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost-time spent purchasing medications (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40 (0.0-0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.40 (0.0-0.90)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13 (0.0-0.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.464\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eCost-time spent on other activities (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0 (0.0\u0026ndash;0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.0 (0.0-4.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eN/A\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTotal cost (US$)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78.92\u003c/p\u003e\n \u003cp\u003e(42.35\u0026ndash;165.60)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e78.92\u003c/p\u003e\n \u003cp\u003e(41.90-155.80)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77.91\u003c/p\u003e\n \u003cp\u003e(50.57-195.44)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.317\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\u003eNumerical variables are presented as medians and interquartile ranges (non-parametric distribution). The values were converted from reais to dollars, as explained in the \u003cspan class=\"InternalRef\"\u003emethods\u003c/span\u003e section. SUS\u0026thinsp;=\u0026thinsp;National Health System; CT\u0026thinsp;=\u0026thinsp;chemotherapy; RT\u0026thinsp;=\u0026thinsp;radiotherapy.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv class=\"Section2\" id=\"Sec12\"\u003e\n \u003ch2\u003ePrimary outcome: total out-of-pocket costs\u003c/h2\u003e\n \u003cp\u003eIn the SUS group, the interquartile range for the total monthly out-of-pocket expenditure by patients was R\u003cspan\u003e$\u003c/span\u003e 240.90\u0026ndash;895.90 (US\u003cspan\u003e$\u003c/span\u003e 41.90\u0026ndash;155.81), with a median of R\u003cspan\u003e$\u003c/span\u003e 453.8 (US\u003cspan\u003e$\u003c/span\u003e 78.92). In the RP group, the interquartile range for the total monthly out-of-pocket expenditure by patients was R\u003cspan\u003e$\u003c/span\u003e 290.80\u0026ndash;1123.80 (US\u003cspan\u003e$\u003c/span\u003e 50.57\u0026ndash;195.44), with a median of R\u003cspan\u003e$\u003c/span\u003e 448.00 (US\u003cspan\u003e$\u003c/span\u003e 77.91). In the univariate analysis, there was no significant difference between the total out-of-pocket expenditure when comparing the SUS and RP groups (P\u0026thinsp;=\u0026thinsp;0.317).\u003c/p\u003e\n \u003cp\u003eAfter adjusting for confounders in the multivariate analysis (Table \u003cspan class=\"InternalRef\"\u003e3\u003c/span\u003e), only the time spent by patients on chemotherapy and radiotherapy was significantly different, being higher in the SUS group (OR 2.58, 95% CI 1.03\u0026ndash;6.50, P\u0026thinsp;=\u0026thinsp;0.043).\u003c/p\u003e\n \u003cdiv class=\"gridtable\"\u003e\u0026nbsp;\u003ctable border=\"1\" id=\"Tab3\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e\n \u003cdiv class=\"CaptionContent\"\u003e\n \u003cp\u003eMultivariate analysis by binary logistic regression.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAdjusted OR\u003c/p\u003e\n \u003cp\u003e(95% CI)\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003eTreatment center\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale sex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12.67 (0.0 \u0026ndash; inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime since diagnosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6\u0026ndash;12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.037 (0.0\u0026ndash;3.47)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.155\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;12 months\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.213 (0.01\u0026ndash;4.33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.315\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePrimary organ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLarge intestine\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRef\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0 \u0026ndash; inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eProstate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0 \u0026ndash; inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eCervix\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.012 (0.0 \u0026ndash; inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLiver\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e297.02 (0.0 \u0026ndash; inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLung\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.279 (0.0 \u0026ndash; inf)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1.0\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHome\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRented\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.176 (0.0\u0026ndash;7.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFinanced\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.0 (0.0\u0026ndash;10.37)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.106\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNumber of trips\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.556 (0.29\u0026ndash;1.08)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.083\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTelephone costs\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.996 (0.97\u0026ndash;1.02)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime spent on CT/RT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e2.586 (1.03\u0026ndash;6.50)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e0.043\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTime spent on other\u003c/p\u003e\n \u003cp\u003eactivities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.963 (0.89\u0026ndash;1.05)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0.379\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eCancer is an important cause of mortality worldwide, with a trend that seems to only increase. Along with the growth in morbidity and mortality, the economic burden of direct and indirect costs is also increasing. This study aimed to characterize the out-of-pocket costs of cancer treatment incurred by patients during treatment, either through the SUS or research protocols.\u003c/p\u003e \u003cp\u003eOur study population was mostly female (61%), with a mean age older than 50 years, findings that are consistent with those in other studies involving patients with cancer [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan additionalcitationids=\"CR13 CR14 CR15 CR16 CR17 CR18\" citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. There was greater participation by individuals who reported being white (60%), although the majority of the Brazilian population self-reports as black [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Based on the literature, the main comorbidities of patients with cancer are hypertension, diabetes and dyslipidemia, consistent with the results of our study [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRegarding cancer characteristics, breast cancer is the most prevalent among patients both in our study and in the literature, but the time since diagnosis differs, and in our study, most patients had been diagnosed more than 12 months prior (42.6%) [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn the analysis of the total out-of-pocket costs incurred by patients, the mean final value, i.e., R\u003cspan\u003e$\u003c/span\u003e 453.80 (US\u003cspan\u003e$\u003c/span\u003e 78.92) per month, was lower than that found in a similar study conducted in the United States, in which the monthly mean was approximately R\u003cspan\u003e$\u003c/span\u003e 1071.00 (based on the dollar exchange rate at the time) [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. In addition, the total monthly expenditure found in this study was also substantially lower than that found in another study conducted in northern India in which the mean out-of-pocket expenditure by patients with head and neck cancer was R\u003cspan\u003e$\u003c/span\u003e 2123.86 (US\u003cspan\u003e$\u003c/span\u003e 369.37) based on the rupee/real exchange rate in 2019 [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. This difference may be explained by the type of cancer investigated, indicating that there is a difference in spending not only between different regions but also between different types of cancer.\u003c/p\u003e \u003cp\u003eWhen comparing our results with the Brazilian reality, 43.4% (R\u003cspan\u003e$\u003c/span\u003e 1045.00/US\u003cspan\u003e$\u003c/span\u003e 181.74) of 1 minimum wage in 2020 was spent by patients on out-of-pocket expenses; however, in another Brazilian study, the total out-of-pocket spending represented 78.4% of the minimum wage at the time (2018) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], indicating that even though the value is high, the percentage found in this study was not higher than that in 2018.\u003c/p\u003e \u003cp\u003eStratifying the out-of-pocket costs surveyed, the transportation expenditure was the highest, approximately R\u003cspan\u003e$\u003c/span\u003e 100.00 (US\u003cspan\u003e$\u003c/span\u003e 17.39) per month, a finding similar to that in another Brazilian study and to that in a Canadian review that also found transportation among the top 4 highest expenses for patients with cancer [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. This finding indicates that transportation to treatment-related commitments (consultations, chemotherapy, radiotherapy, and laboratory tests, among others) is a critical part of out-of-pocket costs and, thus, where patients would benefit the most from receiving aid.\u003c/p\u003e \u003cp\u003eNo significant difference was found between the SUS and RP groups regarding the means of transportation, and the proportion of patients who used cars or public transportation was similar in each group; however, compared to previous studies conducted in Brazil, in this study, there was an increase in the proportion of patients who used their own car [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Despite the similarity in the use of means of transportation and the finding that SUS patients make more trips, the RP patients had a 46.25% higher mean transportation expenditure. Interestingly, the 2 groups spent more on transportation than did patients in a previous study [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e] but less on transportation than did patients in studies from other regions and countries, indicating perhaps greater difficulty in accessing health services in these locations [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. However, we cannot exclude the roles of inflation and our setting as causes of the differences in transportation costs between studies conducted at different times.\u003c/p\u003e \u003cp\u003eThe results of the multivariate analysis show that there was no significant difference between the SUS and RP groups. This may be due to the balance between some expenses among the evaluated costs. For example, while the RP group spent more on telephones, the SUS group had higher expenses related to the number of trips. Differently from another study conducted on the costs incurred by cancer patients that found that employed patients incurred higher costs, in this study, patient occupation was not significant in determining the difference between costs. In contrast, education level, type of cancer, sex, age and ethnicity were not significant either in our study or in another study conducted in Brazil [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBecause of the observational nature of our study, the limitations include the impossibility of establishing cause and effect relationships and include the possible presence of biases and confounding factors. Our questionnaires, especially those related to cost-time, required that patients remember various expenses and situations, potentially introducing recall bias. Additionally, the different proportion of patients from the SUS and RP may have influenced the results, but unfortunately, in the context of the COVID-19 pandemic, several patients were lost to follow-up, especially in the RP group. Last, our patient sample represents only a portion of patients undergoing cancer treatment, which includes patients from several other health centers that may have their own patient protocols and services.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eAlthough research protocols reduce the costs related to cancer treatment for the SUS and other paying sources, there was no impact on the out-of-pocket costs incurred by the patients. These out-of-pocket costs represent an important portion of the costs incurred by patients undergoing cancer treatment through the SUS and those enrolled in research protocols. The data reported here suggest that government aid in the form of a grant of approximately 1 minimum wage for patients diagnosed with cancer in our setting could mitigate these out-of-pocket costs.\u003c/p\u003e "},{"header":"Declarations","content":"\u003cp\u003e\u003cem\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors did not receive support from any organization for the submitted work.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAuthors Contribution\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eAll authors were part in the designing, data collection, data analysis and writing of this article, and all have approved the final version for publication.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConflicts of Interest\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe authors have no relevant financial or non-financial interests to disclose related to this work.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eAvailability of Data and Material\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eEvery available data and material is declared in the manuscript text.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eEthics Approval\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe study was conducted in accordance with the principles of the Declaration of Helsinki [10]. The study protocol was approved by the Research Ethics Committee of FMABC University Center (approval number: 30524420.3.0000.0082).\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent to Participate\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eWritten informed consent was obtained from all individual participants included in the study.\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eConsent for Publication\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. GLOBOCAN 2021. Cancer Today. Dispon\u0026iacute;vel em \u0026lt; Cancer Today (iarc.fr)\u0026gt;. Acesso em: 21 de maio de 2021.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Global health observatory data repository (2011) Number of deaths (World) by cause. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://apps.who.int/gho/data/node.main.CODWORLD?lang=en\u003c/span\u003e\u003c/span\u003e. Last accessed 30 January 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. Latest Global Cancer Data (2018) International Agency for Research on Cancer. Available from: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/cancer/PRGlobocanFinal.pdf\u003c/span\u003e\u003c/span\u003e. Last accessed 2 February 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLentz R, Benson AB, Kircher S (2019) Financial toxicity in cancer care: Prevalence, causes, consequences, and reduction strategies. J Surg Oncol 120(1):85\u0026ndash;92\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSetor Sa\u0026uacute;de. O custo de tratamento de c\u0026acirc;ncer no Brasil. 2018. Estat\u0026iacute;sticas e An\u0026aacute;lises. Dispon\u0026iacute;vel em: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://setorsaude.com.br/o-custo-do-tratamento-do-cancer-no-brasil/\u003c/span\u003e\u003c/span\u003e. Acessado em: 2 de fevereiro de 2020\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eARAUJO, Jos\u0026eacute; Klerton Luz et al. Assessment of costs related to cancer treatment. Rev. Assoc. Med. Bras., S\u0026atilde;o Paulo, v. 66, n. 10, p.\u0026nbsp;1423\u0026ndash;1430, Oct. 2020. Available from \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e\u0026lt; http://www.scielo.br/scielo.php?script=sci_arttext\u0026amp;pid=S0104\u003c/span\u003e\u003c/span\u003e-42302020001001423\u0026amp;lng=en\u0026amp;nrm=iso\u0026gt;. access on 21 May 2021. Epub Nov 06, 2020. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1590/1806-9282.66.10.1423\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003ePaim J, Travassos C, Almeida C, Bahia L, Macinko J (2011) The Brazilian health system: history, advances, and challenges. Lancet. May 21;377(9779):1778\u0026ndash;97\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSatibi S, Andayani TM, Endarti D, Suwantara IPT, Agustini NPD (2019) Comparison of real cost versus the Indonesian case base groups (INA-CBGs) tariff rates among patients of high-incidence cancers under the national health insurance scheme. Asian Pac J Cancer Prev 20(1):117\u0026ndash;122\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZaremba G et al (2016) Out-of-pocket costs for cancer patients treated at the Brazil- ian public health system (SUS) and for their caregivers: A pilot study. Clinical Oncology Letters 2(1):23\u0026ndash;30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Medical Association (2013) World Medical Association Declaration of Helsinki. JAMA 310(20):2191\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003evon Elm E, Altman DG, Egger M et al (2007) The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) statement: guidelines for reporting observational studies. Lancet 370(9596):1453\u0026ndash;1457\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKoskinen J-P, F\u0026auml;rkkil\u0026auml; N, Sintonen H, Saarto T, Taari K, Roine RP (2019 Jul) The association of financial difficulties and out-of-pocket payments with health-related quality of life among breast, prostate and colorectal cancer patients. Acta Oncol 3(7):1062\u0026ndash;1068 58(\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDehghan M, Jazinizade M, Malakoutikhah A, Madadimahani A, Iranmanesh MH, Oghabian S et al (2020) Stress and Quality of Life of Patients with Cancer: The Mediating Role of Mindfulness. J Oncol 2020:3289521\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eChauhan AS, Prinja S, Ghoshal S, Verma R (2019 Feb) Economic Burden of Head and Neck Cancer Treatment in North India. Asian Pac J Cancer Prev 26(2):403\u0026ndash;409 20(\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCallahan C, Brintzenhofeszoc K (2015) Financial Quality of Life for Patients With Cancer: An Exploratory Study. J Psychosoc Oncol 33(4):377\u0026ndash;394\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSmith GL, Lopez-Olivo MA, Advani PG, Ning MS, Geng Y, Giordano SH et al (2019) Financial Burdens of Cancer Treatment: A Systematic Review of Risk Factors and Outcomes. J Natl Compr Canc Netw. Oct 1;17(10):1184\u0026ndash;92\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003edel Giglio A et al (2016) Out-of-pocket costs for cancer patients treated at the Brazilian public health system (SUS) and for their caregivers: A pilot study. Clin Onc Let 2(1):23\u0026ndash;30\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eGordon LG, Merollini KMD, Lowe A, Chan RJ (2017 Jun) A Systematic Review of Financial Toxicity Among Cancer Survivors: We Can\u0026rsquo;t Pay the Co-Pay. Patient 10(3):295\u0026ndash;309\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZafar SY, Peppercorn JM, Schrag D, Taylor DH, Goetzinger AM, Zhong X et al (2013) The financial toxicity of cancer treatment: a pilot study assessing out-of-pocket expenses and the insured cancer patient\u0026rsquo;s experience. Oncologist 18(4):381\u0026ndash;390\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIBGE EDUCA. Conhe\u0026ccedil;a o Brasil \u0026ndash; Popula\u0026ccedil;\u0026atilde;o \u0026ndash; Cor ou Ra\u0026ccedil;a. Dispon\u0026iacute;vel em: \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://educa.ibge.gov.br/jovens/conheca-o-brasil/populacao/18319-cor-ou-raca.html\u003c/span\u003e\u003c/span\u003e. Acesso em: 21 jun. 2021\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoumoundouros C, Ould Brahim L, Lambert SD, McCusker J (2019 Sep) The direct and indirect financial costs of informal cancer care: A scoping review. Health Soc Care Community 27(5):e622\u0026ndash;e636\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Neoplasms, Costs, SUS, Research protocols, Chemotherapy.","lastPublishedDoi":"10.21203/rs.3.rs-807102/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-807102/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eIntroduction:\u003c/h2\u003e \u003cp\u003eEconomic burden of cancer treatment does not fall only on the Brazilian National Health System (\u0026ldquo;SUS\u0026rdquo;) but also on patients. Nonreimbursed indirect costs include noncovered oral medications, food, transportation, and others. Our study compares out-of-pocket costs of cancer treatment between patients from the SUS and patients enrolled in research protocols.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eObservational, cross-sectional and analytical study conducted in 2021. Patients undergoing chemotherapy were divided into 2 groups: patients from a tertiary hospital affiliated with the SUS and patients enrolled in research protocols at a research center. The primary outcome was the evaluation of out-of-pocket costs using a socioeconomic questionnaire to identify the cost and time spent by patients during treatment. This study was approved by the Research Ethics Committee.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003e195 patients were included, of whom 165 (84.6%) were treated by the SUS and 30 (15.4%) by research protocols. Of the total, 61% were female, and the mean age of the patients was 57 years. The median total out-of-pocket costs of SUS patients was Brazilian reais (R\u003cspan\u003e$\u003c/span\u003e) 453.80 (US\u003cspan\u003e$\u003c/span\u003e 78.92), and that of patients who were enrolled in research protocols was R\u003cspan\u003e$\u003c/span\u003e 448.00 (US\u003cspan\u003e$\u003c/span\u003e 77.91) (P\u0026thinsp;=\u0026thinsp;0.317). A comparison of the groups by multivariate analysis showed that only the time spent by patients on chemotherapy and radiotherapy was significantly different, being higher in the SUS group (OR 2.58, 95% CI 1.03\u0026ndash;6.50).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eTotal out-of-pocket spending by SUS patients is similar in magnitude to that by patients in research protocols, although the reasons for the spending are different.\u003c/p\u003e","manuscriptTitle":"Is There a Difference in The “Out-Of-Pocket” Costs of Cancer Treatment When Comparing Patients From The Brazilian National Health System With Patients Enrolled in Clinical Research Protocols?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2021-09-02 14:12:30","doi":"10.21203/rs.3.rs-807102/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":"4570e7ee-6ec9-4f21-8d73-2817f41350b8","owner":[],"postedDate":"September 2nd, 2021","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":6895287,"name":"Critical Care \u0026 Emergency Medicine"},{"id":6895288,"name":"Cancer Biology"},{"id":6895289,"name":"Oncology"}],"tags":[],"updatedAt":"2021-12-14T14:55:05+00:00","versionOfRecord":[],"versionCreatedAt":"2021-09-02 14:12:30","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-807102","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-807102","identity":"rs-807102","version":["v1"]},"buildId":"WrCJVZZCHTDjtuVLN7oU0","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}