Socio-Demographic Factors and Time to Breast Cancer Treatment in a High-Complexity Hospital in Brazil

Socio-Demographic Factors and Time to Breast Cancer Treatment in a High-Complexity Hospital in Brazil | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Socio-Demographic Factors and Time to Breast Cancer Treatment in a High-Complexity Hospital in Brazil Pedro Marchiori Cacilhas, Daniela Dornelles Rosa, Gustavo Thomas¹, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5903519/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 5 You are reading this latest preprint version Abstract Objective the aim of this study is to identify the association between educational level and delays in the initiation of oncological treatment. Methods cross-sectional study that evaluated all female patients with BC between January 2022 and December 2023 registered in the Cancer Registry (CR) of Hospital de Clínicas de Porto Alegre (HCPA). Data collection of the sample was made through electronic medical record review and telephone questionnaires applied on the participants. Descriptive, univariable and multivariable analyses were performed to assess factors associated with the prevalence of delayed treatment initiation. A sample size of 178 subjects was calculated based on retrospective data. Results 307 participants had their data collected between June 1st 2023 until February 1st 2024. and were included in the analysis. In the multivariable analysis, initiation of treatment > 60 days after diagnosis was significantly associated with lower educational level, with an estimated relative risk (RR) of 1.48 (IC 95% = 1.064–2.062). The ethnicity “pardo”, which refers to mixed-race individuals, was correlated with a longer time to treatment when compared to white patients (RR = 1.63; IC 95% = 1.038–2.579). Conclusion This cross-sectional study provides evidence that educational level had a significant impact on time to oncological treatment in our cohort, demonstrated through a multivariable analysis. In addition, self-reported mixed-race ethnicity was also associated with delay. The study also demonstrated that although most participants had their treatment started within 60 days, the time between suspicion of cancer and diagnosis was larger than stipulated by law. Breast neoplasms Breast Cancer Time to Treatment Treatment Delay Door-to-Treatment Figures Figure 1 Figure 2 Figure 3 Contributions to the literature This is the first traversal study regarding access to breast cancer treatment in a population from the South of Brazil. This data provides an overview on socio-demographic factors that influence time to first oncological treatment, which represents a significant barrier to patients with cancer in Brazil. The study was also able to characterize the steps patients must take to have their disease diagnosed, which has not been described in previous trials. Therefore, we understand our trial as a landmark in public health access information in the south of Brazil, as it may provide valuable information on which patients should be monitored more closely to have their treatment began in an adequate time. Introduction Breast cancer (BC) is the most common neoplasm among women in Brazil and worldwide, excluding non-melanoma skin cancer ( 1 ). According to data from the Brazilian National Cancer Institute (INCA), 73.610 new cases of breast cancer were estimated in 2023, representing 30% of new cancer cases in women ( 1 ). The increase in incidence of this disease is not only due to longer life expectancy, but also to technologic advances in diagnosis and screening programs ( 2 ). In addition to the health impact, BC diagnosis brings economic consequences, specially those arising from work absences ( 3 ). It is essential to offer BC treatment in an adequate time since delays may decrease the chance of cure. A later diagnosis, with a more advanced disease, hinders the use of less aggressive treatments as less invasive axilla and breast surgeries, which may negatively impact the patients’ quality of life ( 4 ). In Brazil's public healthcare system (SUS), access to BC specialists is one of the first barriers found by patients to have their treatment initiated. The time considered ideal for patients to begin oncological treatment is variable in the literature ( 5 ). In Brazil, this period must not exceed 60 days from the biopsy-confirmed BC diagnosis. This time interval was established by Law No. 12.732, known as “60-Days Law”, created to optimize patient pathways to oncological treatment within the SUS ( 6 ). Despite being created in 2012, for several reasons, this law is difficult to follow by most Brazilian health institutes ( 7 ). Time to first consultation in specialized BC centers depends on several factors including the country region, proximity to cities with healthcare services ( 8 ), and more importantly, the patients' socio-demographic characteristics, such as ethnicity, educational level, and age ( 9 ). Retrospective studies have shown that patients over 50 years old, non-white and those with less than eight years of education are the most vulnerable to delays in BC treatment ( 10 ). Identifying factors associated with starting oncological treatment after 60 days is essential to develop public policies towards most vulnerable patients. These actions could reduce barriers that prevent patients from having timely diagnosis and treatment. Therefore, the primary objective of this study was to assess whether low educational level is associated with the initiation of oncological treatment after 60 days. Methods This was a cross-sectional study including all female patients with BC between 2022 and 2023 registered in the Cancer Registry (CR) of Hospital de Clínicas de Porto Alegre (HCPA). All study participants received care through the public health system (SUS). Inclusion criteria required a histopathological diagnosis of invasive breast cancer, with the first treatment occurring at HCPA in 2022–2023. Recurrence cases where the initial tumor was treated before 2022 and patients who did not receive antineoplastic treatment were excluded. A sample size of 178 subjects was calculated based on retrospective data ( 9 ) with an additional of 10% to account for potential losses and refusals, aiming to reach 198 subjects. It was considered an 80% power and 5% significance level ( 11 ). Although the sample size calculation indicated 178 participants, it was determined that all cases from the years 2022 and 2023 would be included to obtain a larger sample, allowing for a better exploration of the effects of socio-demographic characteristics. The project was approved by the Research Ethics Committee of the Hospital de Clínicas de Porto Alegre (CEP/HCPA) under registration number 71160423.7.0000.5327 (CAAE). The study followed current guidelines and regulations on research involving human subjects, respecting bioethical principles such as autonomy and non-maleficence. After identifying eligible patients, phone contact was made to invite them to participate in the study. Upon consent, the Consent Form (CF) was read via phone and a questionnaire regarding sociodemographic characteristics and the patient’s journey before the first consultation at HCPA was conducted. In addition, an individual review of electronic medical records was performed. The telephonic questionnaire was applied to all participants that answered the phone call from the research team. The questionnaire included questions regarding the date of suspicion and confirmation of breast cancer as well as information related to family structure, ethnicity, marital status, and whether the participant had a paid employment at the time of diagnosis. The collected data was used exclusively for the analyses of this study with precautions to minimize risks related to confidentiality as provided for in Resolution No. 466/2012 of the Brazilian National Health Council (CNS/MS). Pre-diagnosis data was obtained from the Health Department of the State of Rio Grande do Sul. Deceased participants, or those who did not answer the telephone call, as determined by the ethics committee, had their data obtained exclusively from electronic medical records. Quantitative variables were described based on measures of central tendency and dispersion. Qualitative variables were described according to frequency and proportion. The variable “time to first treatment” was obtained from medical records or through direct contact with the patient. Considering the 60-days law, time to first treatment was dichotomized into “up or equal to 60 days” or “more than 60 days” in order to establish associations with other variables. Prevalence ratio (PR), confidence intervals (CI) and significance values ( p -values) were calculated to verify the relationship between time to treatment and variables of interest. Relative risk (RR) was estimated through the PR. Univariate analyses were performed to correlate the time to first oncologic treatment with the participants' socio-demographic variables. Multivariable analysis was conducted using Poisson logistic regression, which is the most appropriate mathematical method for cross-sectional studies ( 12 ). In this model, variables were included if they modified the time to oncologic treatment by more than 10% and had an adequate number of participants. Results During the established period, 540 new patients were treated for BC at HCPA. Of these, 307 met the inclusion criteria and were included in the analysis (Image 1). Among the 307 study participants, 170 (55.37%) responded to the phone contact while the remaining participants had their information gathered exclusively through review of electronic medical records. Telephone calls were made from June 1st 2023 until February 1st 2024. Pre-diagnosis data were available from 284 participants (92.25%) and were collected through the electronic system responsible for municipal consultation scheduling (GERCON). The median age was 63 years (range: 27 to 91 years). Of the participants, 20.20% had up to 49 years, 50.49% were between 50 to 70 years and 29.31% were over 70 years. Data from one patient (0.32%) was missing. Regarding self-reported skin color, 80.46% identified as white, 10.75% as black and 8.47% as mixed-race (pardo). Information regarding one patient (0.32%) was not available. The self-reported skin color was obtained through phone contact in 170 participants and through electronic medical records in the remaining. Regarding educational level, 4.25% of the participants were illiterate, 38.23% had incomplete primary education, 13.73% had completed primary education, 5.23% had incomplete secondary education, 28.10% had completed secondary education and 10.46% had higher education (Table 1 ). Table 1. Clinical and sociodemographic characteristics of the participants. Table 1. Clinical and sociodemographic characteristics of the participants. Characteristic Participant (%) Age (median) 63 years Skin color / Ethnicity White Parda Black Non identified 247 (80.46) 26 (8.47) 33 (10.75) 1 (0.32) Education level* Illiterate Incomplete primary education Complete primary education Incomplete secondary education Complete secondary education Higher education *Missing Data from one patient 13 (4.25) 117 (38.23) 42 (13.73) 16 (5.23) 86 (28.10) 32 (10.46) City of origin Porto Alegre (capital) Other cities 115 (37.79) 192 (62.21) Tumor subtype* Luminal A Luminal B Luminal-HER2 Triple-negative HER-2+ *Missing Data from three patients 71 (23.36) 136 (44.74) 45 (14.80) 38 (12.5) 14 (4.6) Clinical staging* I II III IV *Missing Data from four patients 84 (27.72) 126 (41.58) 64 (21.12) 29 (9.6) Site of diagnosis* HCPA Other *Missing Data from one patient 231 (75) 75 (25) The median time to initiate oncologic treatment, measured from the date of the anatomopathological examination result, was 47 days (range 0–211 days). Ninety participants (29.9% of the sample) exceeded 60 days to start their treatment. To identify how educational level influences the time to first treatment, a Poisson log-linear model with robust variance for multivariable analysis was used ( 12 ). In this model, patients were divided into two groups according to their educational level. The first consisted of participants with lower educational level (illiterate or with incomplete/complete primary education), totaling 172 participants (56%); the second group consisted of participants with higher educational level (incomplete/complete secondary education or higher education), totaling 135 participants (44%). Based on this dichotomized educational level, an estimated relative risk (RR) = 1.24 (IC 95% = 0.872–1.781) was identified for starting treatment after 60 days in the lower education group. The multivariable model included all variables that modified the association effect by 10% or more. Among the variables tested, “biopsy location” was the only that met that criterion. Therefore, in the multivariable analysis model, “educational level” and “biopsy location” were included. In this model, lower educational level led to a statistically significant 48% increased risk (RR = 1.48; 95% CI: 1.064–2.062) of delayed initiation of oncologic treatment beyond 60 days compared to participants with higher educational levels (Image 2). As a secondary objective, univariable analyses were made evaluating the characteristics of participants that initiated their treatment within or after the established 60-days period (Table 2). Participants of skin color pardo had a statistically higher risk of starting their treatment after 60 days compared to other participants, with a RR = 1.63 (IC 95% = 1.038–2.579). The median time to treatment initiation was 58 days for the mixed-race group compared to 43 days for white participants. Black participants showed no significant differences when compared to white participants. There was a significantly higher risk of delayed treatment among those who underwent biopsy outside of HCPA compared to those who had the procedure performed inside the institution, with a RR = 2.64 (IC 95% = 1.918–3.633). Age, ethnicity, clinical stage, city of origin, modality of first oncological treatment and having a relationship at the time of diagnosis did not show significant differences. Regarding the modality of the first oncologic treatment, 168 participants started with surgery, with a median time of 44 days from diagnosis. In contrast, 101 participants began with chemotherapy with a median time of 51 days. For the subgroup of 32 participants who started with hormone therapy, the median time was 31.5 days. Five patients started treatment with radiotherapy and data from one patient could not be obtained. Table 2. Univariable analyses. Univariable analyses to identify factors associated with delayed start of treatment (> 60 days after diagnosis). For educational level, patients were divided into two groups: low (illiterate or with incomplete/complete primary education) or high (incomplete/complete secondary education or higher education). Percentage of patients that had their treatment begun after 60 days stratified by site of diagnostic biopsy and by educational level. The risk of delay in starting cancer treatment beyond 60 days associated with lower educational level was 1.48; (95% CI: 1.064–2.062). The risk remained for participants who were diagnosed at HCPA: RR = 2.019 (95% CI: 1.113–3.660). Because the referral time to the first cancer specialist consultation after diagnosis made at the primary health care level can be long, a sensitivity analysis was conducted including 231 participants (75% of the total sample) that underwent their tumor biopsy at HCPA. Of these, 79.2% (183 participants) had their treatment begin within 60 days from diagnosis, with a median time of 42 days and mean of 45.7 days (range: 0–150 days). The influence of sociodemographic factors in this sample was also evaluated, and lower educational level remained a risk factor for starting treatment after 60 days, with an RR = 2.019 (95% CI: 1.113–3.660). As a secondary objective, the questionnaire applied to participants was analyzed to describe their pre-diagnostic pathway to care at HCPA (Image 3). This analysis illustrates the steps participants, who were not yet diagnosed with breast cancer at that time, followed to reach HCPA. The median time between noticing a breast lump and seeking care at a primary health care unity (UBS) was 77 days. This median time was calculated based on the participants who reported detecting a lump before diagnosis (153 women). After the initial consultation at the UBS, a referral for specialized evaluation at HCPA is made. The waiting period for this referral is determined by the GERCON system, which organizes specialized consultation requests from primary care. Data from 278 participants were collected through the Rio Grande do Sul state health department. The median waiting time in GERCON was 17 days (range: 3–136 days). Therefore, the pre-diagnostic pathway to the first consultation at HCPA showed a median time of 94 days. Although the 60-days law determines that the anatomopathological (AP) result is the necessary exam to initiate oncological treatment, it is well established that the immunohistochemistry (IHC) test is currently essential to determine the most appropriate first-line treatment modality for breast cancer ( 13 ). This test guides the indication to begin therapy with surgery or chemotherapy, for example. In this sample, the median time for the release of the IHC result was 16 days (range: 0–95 days) from the date of the anatomopathological report. Among patients who underwent a biopsy at HCPA, this time was shorter, with a median of 7 days (range: 0–68 days). Discussion The treatment of early-stage BC is initially conducted through four main modalities: chemotherapy, surgery, hormone therapy or radiotherapy. The decision regarding the sequence of these treatments should be made within a multidisciplinary team involving specialists from different fields ( 13 ). According to a meta-analysis, initiating treatment within three months of diagnosis results in a 7% absolute risk reduction in cancer-related mortality, compared to patients whose treatment was initiated after three to six months ( 14 ). When surgery is the option as first treatment, the time between diagnosis and the procedure significantly impacts patient survival ( 15 , 16 ). There is a direct relationship between delays in breast surgery and decreased survival rates, with a 30-days delay increasing the risk of cancer-related death by 10% ( 16 ), while other studies demonstrated that patients undergoing surgery more than 90 days after diagnosis have lower survival rates compared to those treated within 30 days ( 16 , 17 ). In the present analysis, the median time to surgery was 44 days. Regarding time to initiation of chemotherapy, studies have indicated that starting this therapy within 45 days of diagnosis improves survival outcomes ( 18 ). In this sample, among the 101 patients who received chemotherapy as their first oncological treatment, the median time to treatment was 51 days. There is a lack of data in the literature concerning the time required to achieve a confirmed BC diagnosis. During the pre-diagnostic period, various barriers can delay patients from reaching diagnostic centers in a timely manner, resulting in late medical care. The diagnosis process begins when a woman notices a breast abnormality or through an abnormal screening mammography and seeks care at a nearby primary health center. According to Law No. 13,896, of October 30th, 2019, in cases where the primary diagnostic hypothesis is malignant neoplasm, the necessary diagnostic tests must be performed within a maximum period of thirty days ( 19 ). In the analyzed sample, composed of 54% participants with low educational level, the median time between the onset of symptoms and the first specialized consultation at HCPA (where biopsies are performed in most cases) was 94 days, exceeding by approximately two months the period established by the recently enacted law. Among the reasons for this delay are gaps in knowledge and guidance for identifying signs and symptoms of breast cancer, as well as the fact that the coverage of screening mammography recommended in Brazilian guidelines is suboptimal, compounded by difficulties in accessing healthcare services ( 20 ). This phenomenon is not limited to Brazil; it is observed in many Latin American countries, where low education levels and limited access to healthcare are endemic issues that disproportionately affect disadvantaged populations ( 21 ). In the present study, both low educational level and skin color pardo had a significant impact in time to treatment initiation, leading to prolonged delays. This association remained significant even when analyzing only participants who received their diagnosis at HCPA indicating that social factors are determinants in the variable "time to treatment initiation" as previously described ( 21 ). Thus, individuals with characteristics of social vulnerability should receive differentiated attention to ensure that care is provided within an appropriate timeframe. On the other hand, older age, distance from the cancer treatment center and being single did not show to interfere in time to treatment, factors that have been described as related to late onset of oncological treatment ( 21 ). The lengthy pre-diagnostic journey partly explains the delays observed in patients who had their diagnosis confirmed at health facilities other than HCPA. In this sample, 25% of patients underwent breast biopsy before attending a UBS consultation and, therefore, many of them already had a BC diagnosis at the time they were consulting at a UBS. Even with a confirmed anatomopathological diagnosis in hand, these patients must follow the same process as those without a diagnosis, including waiting for a UBS consultation and referral to a hospital via the GERCON system. Therefore, these patients are at a higher risk of delayed treatment initiation because, under the 60-days law, the countdown starts once the diagnosis is confirmed. However, the referral system within the SUS does not prioritize these patients over those without a confirmed diagnosis, which the authors believe is a weakness in the referral process. Regarding the study's limitations, it is important to note that, as a cross-sectional study conducted at a single institution, caution should be taken when generalizing the reported findings, despite their alignment with the reviewed literature. While some variables showed an impact on the number of days to initiate oncological treatment, this difference did not reach statistical significance, which may reflect the limited sample size. Finally, it is worth emphasizing that, unlike studies based on cancer registry data from public institutions (which are often imprecise), the current study was conducted through an individual review of electronic medical records and, when possible, direct contact with the participants. This approach enhances the accuracy of the reported results. The study was capable of identifying a large proportion of patients (70.01%) that began treatment within 60 days from diagnosis. When considering only those who underwent biopsy at HCPA, the percentage increased to 79.2%, which is significantly higher than the national average. Between 2016 and 2018, only 55.1% of BC patients in Brazil started treatment within 60 days ( 9 ). This figure dropped to 45.5% in 2019 and 51.3% in 2020 ( 8 ). In the state of Piauí, for instance, only 28.4% of patients began treatment within the legally mandated period in 2018 ( 22 ). Based on the present study, it was possible to identify the population most vulnerable to treatment delays: patients with low educational level and skin color pardo . This population should therefore be monitored individually to address these disparities. One potential solution to reduce this inequity is the implementation of patient navigation programs to assist and guide patients and their families from the pre-diagnostic period until the initiation of oncological treatment. This approach is recommended by Law No. 14,758 as part of the National Cancer Prevention and Control Policy within the SUS as the use of patient navigators reduces both the time to breast cancer diagnosis ( 23 ) and the time to treatment initiation ( 24 ). Conclusion Currently, BC treatment is complex and requires synchronized efforts from various professionals and healthcare services to ensure timely initiation of therapy. The present study demonstrated that low educational level is a risk factor for delayed initiation of oncological treatment. Moreover, this association persists even among patients who underwent biopsy at the same institution where their initial treatment was established. Self-declared skin color pardo also emerged as a risk factor, although this finding should be further explored in specific studies due to the small number of participants. Regarding the 60-days law, it is essential to identify socially vulnerable populations to prevent delays in oncological treatment. Furthermore, this study was able to gather data regarding the pre-diagnostic period, a topic that is rarely discussed in Brazilian guidelines and scientific studies, highlighting that the median time of 94 days to establish a cancer diagnosis from the point of suspicion exceeds the time frame established by law. This period, during which the patient has not yet received a cancer diagnosis, should be minimized to increase the chances of diagnosing smaller tumors with a higher likelihood of cure. As previously mentioned, it is essential that government measures are specifically directed towards the most vulnerable populations. The use of nurse navigators, for example, has proven to be an effective strategy in reducing time to cancer treatment. Educational measures should also be encouraged to raise public awareness about signs and symptoms suggestive of cancer, thereby shortening the pre-diagnostic period. Declarations Ethics approval, consent to participate and consent for publication: The project was approved by the Research Ethics Committee of the Hospital de Clínicas de Porto Alegre (CEP/HCPA) under registration number 71160423.7.0000.5327 (CAAE). The study followed current guidelines and regulations on research involving human subjects, respecting bioethical principles such as autonomy and non-maleficence. The collected data was used exclusively for the analyses of this study with precautions to minimize risks related to confidentiality as provided for in Resolution No. 466/2012 of the Brazilian National Health Council (CNS/MS). All patients gave consent to participate and to publish data from this study. Competing interests: the authors have no conflict of interest regarding this publication. Funding: This research project received an award from the City Cancer Challenge, a non-governmental organization that promotes initiatives aimed at improving access to cancer treatment in developing countries. This support was essential for the successful completion of this study. Regarding the availability of data and materials, datasets used in the analysis are exclusively in possession of the first author (Pedro Cacilhas) to minimize risks related to confidentiality. Author 's contribution: Pedro Marchiori Cacilhas (PC), Alice de Medeiros Zelmanowicz (AZ) and Daniela Dornelles Rosa (DR) wrote and reviewed the main manuscript. PC, Gustavo Thomas (GT), Karine Lorenzen Molina (KM) and Pedhro Lennon Cezario de Freitas (PF) collected the data regarding the participants. PF was responsible for literature review. All authors read and approved the final manuscript. Acknowledgments: City Cancer Challenge, a non-governmental organization that supported this study. References MINISTÉRIO DA SAÚDE Instituto Nacional de Câncer (INCA). Estimativa | 2023 Incidência de Câncer no Brasil. Souza CB, Fustinoni SM, Amorim MHC, Zandonade E, Matos JC, Schirmer J. Estudo do tempo entre o diagnóstico e início do tratamento do câncer de mama em idosas de um hospital de referência em São Paulo, Brasil. Ciênc Saúde Colet Impr. 2015;20(12):3805–16. Costa JB, Lima MAGD, Neves RDF. O retorno ao trabalho de mulheres após a experiência do câncer de mama: uma metassíntese. Rev Bras Saúde Ocupacional. 2020;45:e19. Ng ET, Ang RZ, Tran BX, Ho CS, Zhang Z, Tan W, et al. Comparing Quality of Life in Breast Cancer Patients Who Underwent Mastectomy Versus Breast-Conserving Surgery: A Meta-Analysis. Int J Environ Res Public Health. 2019 Dec 6;16(24):4970. Abdel-Razeq H, Mansour A, Edaily S, Dayyat A. Delays in Initiating Anti-Cancer Therapy for Early-Stage Breast Cancer-How Slow Can We Go? J Clin Med. 2023 Jul 5;12(13):4502. LEI N o 12.732, DE 22 DE NOVEMBRO DE 2012. [Internet]. Available from: https://www.planalto.gov.br/ccivil_03/_ato2011-2014/2012/lei/l12732.htm Jomar RT, Velasco NS, Mendes GLQ, Guimarães RM, Fonseca VADO, Meira KC. Fatores associados ao tempo para submissão ao primeiro tratamento do câncer de mama. Ciênc Saúde Coletiva. 2023 Jul;28(7):2155–64. Nogueira MC, Atty AT de M, Tomazelli J, Jardim BC, Bustamante-Teixeira MT, Azevedo E Silva G. Frequency and factors associated with delay in breast cancer treatment in Brazil, according to data from the Oncology Panel, 2019-2020. Epidemiol E Serv Saude Rev Sist Unico Saude Bras. 2023;32(1):e2022563. Maschmann RM, De Jesus RG, Werutsky G, Rebelatto TF, Queiroz G, Simon SD, et al. Time interval between diagnosis to treatment of breast cancer and the impact of health insurance coverage: a sub analysis of the AMAZONA III Study (GBECAM 0115). Breast Cancer Res Treat. 2023 Feb;198(1):123–30. Cabral ALLV, Giatti L, Casale C, Cherchiglia ML. Vulnerabilidade social e câncer de mama: diferenciais no intervalo entre o diagnóstico e o tratamento em mulheres de diferentes perfis sociodemográficos. Ciênc Saúde Colet Impr. 2019;613–22. Borges RB, Mancuso ACB, Camey SA, Leotti VB, Hirakata VN, Azambuja GS, et al. Power and Sample Size for Health Researchers: uma ferramenta para cálculo de tamanho amostral e poder do teste voltado a pesquisadores da área da saúde. Clin Biomed Res [Internet]. 2021 Apr 13 [cited 2024 Nov 20]; Barros AJ, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol. 2003 Oct 20;3(1):21. Waks AG, Winer EP. Breast Cancer Treatment: A Review. JAMA. 2019 Jan 22;321(3):288. Richards, MA et al. Influence of delay on survival in patients with breast cancer: a systematic review. Volume 353(Issue 9159, 1119-1126). Abdel-Razeq H, Mansour A, Edaily S, Dayyat A. Delays in Initiating Anti-Cancer Therapy for Early-Stage Breast Cancer—How Slow Can We Go? J Clin Med [Internet]. 2023;12(13). An D, Choi J, Lee J, Kim JY, Kwon S, Kim J, et al. Time to surgery and survival in breast cancer. BMC Surg. 2022 Nov 11;22(1):388. Ho PJ, Cook AR, Binte Mohamed Ri Nur Khaliesah and Liu J, Li J, Hartman M. Impact of delayed treatment in women diagnosed with breast cancer: A population-based study. Cancer Med. 2020 Feb;9(7):2435–44. Flores-Balcázar CH, Flores-Luna ML, Villarreal-Garza CM, Bargalló-Rocha JE. Provider delay in treatment initiation and its influence on survival outcomes in women with operable breast cancer. Rep Pract Oncol Radiother. 2020;25(2):271–5. LEI N o 13.896, DE 30 DE OUTUBRO DE 2019 [Internet]. Sect. Seção 1. Available from: https://www2.camara.leg.br/legin/fed/lei/2019/lei-13896-30-outubro-2019-789326-publicacaooriginal-159304-pl.html Barros ÂF, Murta-Nascimento C, Abdon CH de, Nogueira DN, Lopes ELC, Dias A. Factors associated with time interval between the onset of symptoms and first medical visit in women with breast cancer. Cad Saude Publica. 2020;36(2):e00011919. Rivera-Franco MM, Leon-Rodriguez E. Delays in Breast Cancer Detection and Treatment in Developing Countries. Breast Cancer Basic Clin Res. 2018 Jan 1;12:1178223417752677. Sousa SMMT, Carvalho MDGFDM, Santos Júnior LA, Mariano SBC. Acesso ao tratamento da mulher com câncer de mama. Saúde Em Debate. 2019 Sep;43(122):727–41. Palmieri FM, Deperi ER, Mincey BA, Smith JA, Wen LK, Chewar DM, et al. Comprehensive Diagnostic Program for Medically Underserved Women With Abnormal Breast Screening Evaluations in an Urban Population. Mayo Clin Proc. 2009 Apr;84(4):317–22. Zibrik K, Laskin J, Ho C. Integration of a Nurse Navigator into the Triage Process for Patients with Non-Small-Cell Lung Cancer: Creating Systematic Improvements in Patient Care. Curr Oncol. 2016 Jun 1;23(3):280–3. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 29 Apr, 2025 Reviewers agreed at journal 26 Apr, 2025 Reviewers invited by journal 22 Apr, 2025 Submission checks completed at journal 21 Apr, 2025 First submitted to journal 12 Apr, 2025 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-5903519","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":446217681,"identity":"cd1d12bb-ec0e-4750-94e3-38e7392de55a","order_by":0,"name":"Pedro Marchiori Cacilhas","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9klEQVRIiWNgGAWjYHACAwjFzNwGJG2AmLHxAJFaGEFa0kBaGojUwgDWchjMxKvFnL1524ePOXby/O2MbQ9+/Dlvt7b9MNCWGptoXFose44Vz5y5LdlwxmHGdsPettvJ284kArUcS8ttwOWqGznGzLzbDjBuAPpFgrfhdrLZAaAWxobDuLXcfwPWYg/SIvnnz7lks/MPCWi5wQPWkgjSIs3DdsDO7AYBWyx70ooZgX5JBvqlTVq2LTnB7AbQlgQ8fjFnP7yZ4eM2O9v+/sPHJN/8sbM3O5/+8MGHGhvcDkMXSASrTMChHKsWezyKR8EoGAWjYIQCAGKhYwK7XKddAAAAAElFTkSuQmCC","orcid":"","institution":"Universidade Federal do Rio Grande do Sul","correspondingAuthor":true,"prefix":"","firstName":"Pedro","middleName":"Marchiori","lastName":"Cacilhas","suffix":""},{"id":446217683,"identity":"53a7e2e9-a3b1-48d4-b581-c90fc9b43290","order_by":1,"name":"Daniela Dornelles Rosa","email":"","orcid":"","institution":"Universidade Federal do Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Daniela","middleName":"Dornelles","lastName":"Rosa","suffix":""},{"id":446217685,"identity":"ba592e84-184b-4662-97bb-fadbc023ea2f","order_by":2,"name":"Gustavo Thomas¹","email":"","orcid":"","institution":"Hospital de Clínicas de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Gustavo","middleName":"","lastName":"Thomas¹","suffix":""},{"id":446217687,"identity":"5ee46357-a9b6-4bd8-a94c-bad3cc7f1265","order_by":3,"name":"Karine Lorenzen Molina¹","email":"","orcid":"","institution":"Hospital de Clínicas de Porto Alegre","correspondingAuthor":false,"prefix":"","firstName":"Karine","middleName":"Lorenzen","lastName":"Molina¹","suffix":""},{"id":446217689,"identity":"f2b6200c-74f9-4582-bdb9-3f8b420182fb","order_by":4,"name":"Pedhro Lennon Cezario de Freitas","email":"","orcid":"","institution":"Universidade Federal do Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Pedhro","middleName":"Lennon Cezario","lastName":"de Freitas","suffix":""},{"id":446217691,"identity":"b2d1880e-e4e6-4e71-af95-a64e6af0678b","order_by":5,"name":"Alice de Medeiros Zelmanowicz","email":"","orcid":"","institution":"Universidade Federal do Rio Grande do Sul","correspondingAuthor":false,"prefix":"","firstName":"Alice","middleName":"de Medeiros","lastName":"Zelmanowicz","suffix":""}],"badges":[],"createdAt":"2025-01-25 20:23:07","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-5903519/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-5903519/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81542243,"identity":"baf252fe-8caf-43ee-bbb1-e4bfc61c2283","added_by":"auto","created_at":"2025-04-28 11:17:52","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":40208,"visible":true,"origin":"","legend":"\u003cp\u003eImage 1. Inclusion of participants.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5903519/v1/c22b8e7c3231f6fbcb0894a8.jpg"},{"id":81542245,"identity":"212998b9-19e7-4d4f-a525-dc975921753f","added_by":"auto","created_at":"2025-04-28 11:17:52","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":29678,"visible":true,"origin":"","legend":"\u003cp\u003eImage 2. Multivariable analyses regarding site of diagnostic biopsy and educational level.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5903519/v1/ea4f55c7b99ed2fa5af5b67c.jpg"},{"id":81542244,"identity":"d6ec6403-6ef0-42b5-b2fe-1b50975f1bc2","added_by":"auto","created_at":"2025-04-28 11:17:52","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":30071,"visible":true,"origin":"","legend":"\u003cp\u003eImage 3. Diagnostic Pathway of Participants.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-5903519/v1/4bd00ad61b44f8a6a76a9782.jpg"},{"id":81544796,"identity":"4afff86f-882c-4b01-af6e-e9aca73645b5","added_by":"auto","created_at":"2025-04-28 11:33:57","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":657606,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5903519/v1/40ed1024-c44c-4249-a60e-033634f868a7.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Socio-Demographic Factors and Time to Breast Cancer Treatment in a High-Complexity Hospital in Brazil","fulltext":[{"header":"Contributions to the literature","content":"\u003cp\u003eThis is the first traversal study regarding access to breast cancer treatment in a population from the South of Brazil. This data provides an overview on socio-demographic factors that influence time to first oncological treatment, which represents a significant barrier to patients with cancer in Brazil.\u003c/p\u003e\n\u003cp\u003eThe study was also able to characterize the steps patients must take to have their disease diagnosed, which has not been described in previous trials. Therefore, we understand our trial as a landmark in public health access information in the south of Brazil, as it may provide valuable information on which patients should be monitored more closely to have their treatment began in an adequate time.\u003c/p\u003e"},{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) is the most common neoplasm among women in Brazil and worldwide, excluding non-melanoma skin cancer (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). According to data from the Brazilian National Cancer Institute (INCA), 73.610 new cases of breast cancer were estimated in 2023, representing 30% of new cancer cases in women (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). The increase in incidence of this disease is not only due to longer life expectancy, but also to technologic advances in diagnosis and screening programs (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). In addition to the health impact, BC diagnosis brings economic consequences, specially those arising from work absences (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIt is essential to offer BC treatment in an adequate time since delays may decrease the chance of cure. A later diagnosis, with a more advanced disease, hinders the use of less aggressive treatments as less invasive axilla and breast surgeries, which may negatively impact the patients\u0026rsquo; quality of life (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). In Brazil's public healthcare system (SUS), access to BC specialists is one of the first barriers found by patients to have their treatment initiated. The time considered ideal for patients to begin oncological treatment is variable in the literature (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). In Brazil, this period must not exceed 60 days from the biopsy-confirmed BC diagnosis. This time interval was established by Law No. 12.732, known as \u0026ldquo;60-Days Law\u0026rdquo;, created to optimize patient pathways to oncological treatment within the SUS (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Despite being created in 2012, for several reasons, this law is difficult to follow by most Brazilian health institutes (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTime to first consultation in specialized BC centers depends on several factors including the country region, proximity to cities with healthcare services (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e), and more importantly, the patients' socio-demographic characteristics, such as ethnicity, educational level, and age (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Retrospective studies have shown that patients over 50 years old, non-white and those with less than eight years of education are the most vulnerable to delays in BC treatment (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIdentifying factors associated with starting oncological treatment after 60 days is essential to develop public policies towards most vulnerable patients. These actions could reduce barriers that prevent patients from having timely diagnosis and treatment. Therefore, the primary objective of this study was to assess whether low educational level is associated with the initiation of oncological treatment after 60 days.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eThis was a cross-sectional study including all female patients with BC between 2022 and 2023 registered in the Cancer Registry (CR) of Hospital de Cl\u0026iacute;nicas de Porto Alegre (HCPA). All study participants received care through the public health system (SUS). Inclusion criteria required a histopathological diagnosis of invasive breast cancer, with the first treatment occurring at HCPA in 2022\u0026ndash;2023. Recurrence cases where the initial tumor was treated before 2022 and patients who did not receive antineoplastic treatment were excluded.\u003c/p\u003e \u003cp\u003eA sample size of 178 subjects was calculated based on retrospective data (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e) with an additional of 10% to account for potential losses and refusals, aiming to reach 198 subjects. It was considered an 80% power and 5% significance level (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Although the sample size calculation indicated 178 participants, it was determined that all cases from the years 2022 and 2023 would be included to obtain a larger sample, allowing for a better exploration of the effects of socio-demographic characteristics.\u003c/p\u003e \u003cp\u003e The project was approved by the Research Ethics Committee of the Hospital de Cl\u0026iacute;nicas de Porto Alegre (CEP/HCPA) under registration number 71160423.7.0000.5327 (CAAE). The study followed current guidelines and regulations on research involving human subjects, respecting bioethical principles such as autonomy and non-maleficence.\u003c/p\u003e \u003cp\u003e After identifying eligible patients, phone contact was made to invite them to participate in the study. Upon consent, the Consent Form (CF) was read via phone and a questionnaire regarding sociodemographic characteristics and the patient\u0026rsquo;s journey before the first consultation at HCPA was conducted. In addition, an individual review of electronic medical records was performed.\u003c/p\u003e \u003cp\u003e The telephonic questionnaire was applied to all participants that answered the phone call from the research team. The questionnaire included questions regarding the date of suspicion and confirmation of breast cancer as well as information related to family structure, ethnicity, marital status, and whether the participant had a paid employment at the time of diagnosis. The collected data was used exclusively for the analyses of this study with precautions to minimize risks related to confidentiality as provided for in Resolution No. 466/2012 of the Brazilian National Health Council (CNS/MS). Pre-diagnosis data was obtained from the Health Department of the State of Rio Grande do Sul. Deceased participants, or those who did not answer the telephone call, as determined by the ethics committee, had their data obtained exclusively from electronic medical records.\u003c/p\u003e \u003cp\u003eQuantitative variables were described based on measures of central tendency and dispersion. Qualitative variables were described according to frequency and proportion. The variable \u0026ldquo;time to first treatment\u0026rdquo; was obtained from medical records or through direct contact with the patient. Considering the 60-days law, time to first treatment was dichotomized into \u0026ldquo;up or equal to 60 days\u0026rdquo; or \u0026ldquo;more than 60 days\u0026rdquo; in order to establish associations with other variables. Prevalence ratio (PR), confidence intervals (CI) and significance values (\u003cem\u003ep\u003c/em\u003e-values) were calculated to verify the relationship between time to treatment and variables of interest. Relative risk (RR) was estimated through the PR.\u003c/p\u003e \u003cp\u003eUnivariate analyses were performed to correlate the time to first oncologic treatment with the participants' socio-demographic variables. Multivariable analysis was conducted using Poisson logistic regression, which is the most appropriate mathematical method for cross-sectional studies (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In this model, variables were included if they modified the time to oncologic treatment by more than 10% and had an adequate number of participants.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eDuring the established period, 540 new patients were treated for BC at HCPA. Of these, 307 met the inclusion criteria and were included in the analysis (Image 1). Among the 307 study participants, 170 (55.37%) responded to the phone contact while the remaining participants had their information gathered exclusively through review of electronic medical records. Telephone calls were made from June 1st 2023 until February 1st 2024. Pre-diagnosis data were available from 284 participants (92.25%) and were collected through the electronic system responsible for municipal consultation scheduling (GERCON).\u003c/p\u003e \u003cp\u003eThe median age was 63 years (range: 27 to 91 years). Of the participants, 20.20% had up to 49 years, 50.49% were between 50 to 70 years and 29.31% were over 70 years. Data from one patient (0.32%) was missing. Regarding self-reported skin color, 80.46% identified as white, 10.75% as black and 8.47% as mixed-race (pardo). Information regarding one patient (0.32%) was not available. The self-reported skin color was obtained through phone contact in 170 participants and through electronic medical records in the remaining.\u003c/p\u003e \u003cp\u003eRegarding educational level, 4.25% of the participants were illiterate, 38.23% had incomplete primary education, 13.73% had completed primary education, 5.23% had incomplete secondary education, 28.10% had completed secondary education and 10.46% had higher education (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eTable 1. Clinical and sociodemographic characteristics of the participants.\u003c/p\u003e\u003cp\u003eTable 1. Clinical and sociodemographic characteristics of the participants.\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" align=\"\" width=\"509\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eCharacteristic\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003eParticipant (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003eAge (median)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp; \u0026nbsp;63 years\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSkin color / Ethnicity\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eWhite\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eParda\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eBlack\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNon identified\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e247 (80.46)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e26 (8.47)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e33 (10.75)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1 (0.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eEducation level*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIlliterate\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIncomplete primary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eComplete primary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIncomplete secondary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eComplete secondary education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHigher education\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e*Missing Data from one patient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e13 (4.25)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e117 (38.23)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e42 (13.73)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e16 (5.23)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e86 (28.10)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e32 (10.46)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCity of origin\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003ePorto Alegre (capital)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOther cities\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e115 (37.79)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e192 (62.21)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor subtype*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLuminal B\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eLuminal-HER2\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eTriple-negative\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHER-2+\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e*Missing Data from three patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e71 (23.36)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e136 (44.74)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e45 (14.80)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e38 (12.5)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e14 (4.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eClinical staging*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIV\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e*Missing Data from four patients\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e84 (27.72)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e126 (41.58)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e64 (21.12)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e29 (9.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 287px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSite of diagnosis*\u003c/strong\u003e\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eHCPA\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eOther\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e*Missing Data from one patient\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 222px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e231 (75)\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e75 (25)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e \u003cp\u003eThe median time to initiate oncologic treatment, measured from the date of the anatomopathological examination result, was 47 days (range 0\u0026ndash;211 days). Ninety participants (29.9% of the sample) exceeded 60 days to start their treatment.\u003c/p\u003e \u003cp\u003eTo identify how educational level influences the time to first treatment, a Poisson log-linear model with robust variance for multivariable analysis was used (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). In this model, patients were divided into two groups according to their educational level. The first consisted of participants with lower educational level (illiterate or with incomplete/complete primary education), totaling 172 participants (56%); the second group consisted of participants with higher educational level (incomplete/complete secondary education or higher education), totaling 135 participants (44%). Based on this dichotomized educational level, an estimated relative risk (RR)\u0026thinsp;=\u0026thinsp;1.24 (IC 95% = 0.872\u0026ndash;1.781) was identified for starting treatment after 60 days in the lower education group. The multivariable model included all variables that modified the association effect by 10% or more. Among the variables tested, \u0026ldquo;biopsy location\u0026rdquo; was the only that met that criterion. Therefore, in the multivariable analysis model, \u0026ldquo;educational level\u0026rdquo; and \u0026ldquo;biopsy location\u0026rdquo; were included. In this model, lower educational level led to a statistically significant 48% increased risk (RR\u0026thinsp;=\u0026thinsp;1.48; 95% CI: 1.064\u0026ndash;2.062) of delayed initiation of oncologic treatment beyond 60 days compared to participants with higher educational levels (Image 2).\u003c/p\u003e \u003cp\u003eAs a secondary objective, univariable analyses were made evaluating the characteristics of participants that initiated their treatment within or after the established 60-days period (Table\u0026nbsp;2). Participants of skin color \u003cem\u003epardo\u003c/em\u003e had a statistically higher risk of starting their treatment after 60 days compared to other participants, with a RR\u0026thinsp;=\u0026thinsp;1.63 (IC 95% = 1.038\u0026ndash;2.579). The median time to treatment initiation was 58 days for the mixed-race group compared to 43 days for white participants. Black participants showed no significant differences when compared to white participants. There was a significantly higher risk of delayed treatment among those who underwent biopsy outside of HCPA compared to those who had the procedure performed inside the institution, with a RR\u0026thinsp;=\u0026thinsp;2.64 (IC 95% = 1.918\u0026ndash;3.633). Age, ethnicity, clinical stage, city of origin, modality of first oncological treatment and having a relationship at the time of diagnosis did not show significant differences.\u003c/p\u003e \u003cp\u003eRegarding the modality of the first oncologic treatment, 168 participants started with surgery, with a median time of 44 days from diagnosis. In contrast, 101 participants began with chemotherapy with a median time of 51 days. For the subgroup of 32 participants who started with hormone therapy, the median time was 31.5 days. Five patients started treatment with radiotherapy and data from one patient could not be obtained.\u003c/p\u003e \u003cp\u003eTable\u0026nbsp;2. Univariable analyses.\u003c/p\u003e \u003cp\u003e\u003cimg src=\"data:image/png;base64,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\" width=\"654\" height=\"506\"\u003e\u003c/p\u003e\u003cp\u003eUnivariable analyses to identify factors associated with delayed start of treatment (\u0026gt;\u0026thinsp;60 days after diagnosis). For educational level, patients were divided into two groups: low (illiterate or with incomplete/complete primary education) or high (incomplete/complete secondary education or higher education).\u003c/p\u003e \u003cp\u003ePercentage of patients that had their treatment begun after 60 days stratified by site of diagnostic biopsy and by educational level. The risk of delay in starting cancer treatment beyond 60 days associated with lower educational level was 1.48; (95% CI: 1.064\u0026ndash;2.062). The risk remained for participants who were diagnosed at HCPA: RR\u0026thinsp;=\u0026thinsp;2.019 (95% CI: 1.113\u0026ndash;3.660).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eBecause the referral time to the first cancer specialist consultation after diagnosis made at the primary health care level can be long, a sensitivity analysis was conducted including 231 participants (75% of the total sample) that underwent their tumor biopsy at HCPA. Of these, 79.2% (183 participants) had their treatment begin within 60 days from diagnosis, with a median time of 42 days and mean of 45.7 days (range: 0\u0026ndash;150 days). The influence of sociodemographic factors in this sample was also evaluated, and lower educational level remained a risk factor for starting treatment after 60 days, with an RR\u0026thinsp;=\u0026thinsp;2.019 (95% CI: 1.113\u0026ndash;3.660).\u003c/p\u003e \u003cp\u003eAs a secondary objective, the questionnaire applied to participants was analyzed to describe their pre-diagnostic pathway to care at HCPA (Image 3). This analysis illustrates the steps participants, who were not yet diagnosed with breast cancer at that time, followed to reach HCPA. The median time between noticing a breast lump and seeking care at a primary health care unity (UBS) was 77 days. This median time was calculated based on the participants who reported detecting a lump before diagnosis (153 women). After the initial consultation at the UBS, a referral for specialized evaluation at HCPA is made. The waiting period for this referral is determined by the GERCON system, which organizes specialized consultation requests from primary care. Data from 278 participants were collected through the Rio Grande do Sul state health department. The median waiting time in GERCON was 17 days (range: 3\u0026ndash;136 days). Therefore, the pre-diagnostic pathway to the first consultation at HCPA showed a median time of 94 days.\u003c/p\u003e \u003cp\u003eAlthough the 60-days law determines that the anatomopathological (AP) result is the necessary exam to initiate oncological treatment, it is well established that the immunohistochemistry (IHC) test is currently essential to determine the most appropriate first-line treatment modality for breast cancer (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). This test guides the indication to begin therapy with surgery or chemotherapy, for example.\u003c/p\u003e \u003cp\u003eIn this sample, the median time for the release of the IHC result was 16 days (range: 0\u0026ndash;95 days) from the date of the anatomopathological report. Among patients who underwent a biopsy at HCPA, this time was shorter, with a median of 7 days (range: 0\u0026ndash;68 days).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe treatment of early-stage BC is initially conducted through four main modalities: chemotherapy, surgery, hormone therapy or radiotherapy. The decision regarding the sequence of these treatments should be made within a multidisciplinary team involving specialists from different fields (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). According to a meta-analysis, initiating treatment within three months of diagnosis results in a 7% absolute risk reduction in cancer-related mortality, compared to patients whose treatment was initiated after three to six months (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eWhen surgery is the option as first treatment, the time between diagnosis and the procedure significantly impacts patient survival (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). There is a direct relationship between delays in breast surgery and decreased survival rates, with a 30-days delay increasing the risk of cancer-related death by 10% (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e), while other studies demonstrated that patients undergoing surgery more than 90 days after diagnosis have lower survival rates compared to those treated within 30 days (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). In the present analysis, the median time to surgery was 44 days.\u003c/p\u003e \u003cp\u003eRegarding time to initiation of chemotherapy, studies have indicated that starting this therapy within 45 days of diagnosis improves survival outcomes (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). In this sample, among the 101 patients who received chemotherapy as their first oncological treatment, the median time to treatment was 51 days.\u003c/p\u003e \u003cp\u003eThere is a lack of data in the literature concerning the time required to achieve a confirmed BC diagnosis. During the pre-diagnostic period, various barriers can delay patients from reaching diagnostic centers in a timely manner, resulting in late medical care. The diagnosis process begins when a woman notices a breast abnormality or through an abnormal screening mammography and seeks care at a nearby primary health center. According to Law No. 13,896, of October 30th, 2019, in cases where the primary diagnostic hypothesis is malignant neoplasm, the necessary diagnostic tests must be performed within a maximum period of thirty days (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). In the analyzed sample, composed of 54% participants with low educational level, the median time between the onset of symptoms and the first specialized consultation at HCPA (where biopsies are performed in most cases) was 94 days, exceeding by approximately two months the period established by the recently enacted law. Among the reasons for this delay are gaps in knowledge and guidance for identifying signs and symptoms of breast cancer, as well as the fact that the coverage of screening mammography recommended in Brazilian guidelines is suboptimal, compounded by difficulties in accessing healthcare services (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). This phenomenon is not limited to Brazil; it is observed in many Latin American countries, where low education levels and limited access to healthcare are endemic issues that disproportionately affect disadvantaged populations (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the present study, both low educational level and skin color \u003cem\u003epardo\u003c/em\u003e had a significant impact in time to treatment initiation, leading to prolonged delays. This association remained significant even when analyzing only participants who received their diagnosis at HCPA indicating that social factors are determinants in the variable \"time to treatment initiation\" as previously described (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). Thus, individuals with characteristics of social vulnerability should receive differentiated attention to ensure that care is provided within an appropriate timeframe. On the other hand, older age, distance from the cancer treatment center and being single did not show to interfere in time to treatment, factors that have been described as related to late onset of oncological treatment (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe lengthy pre-diagnostic journey partly explains the delays observed in patients who had their diagnosis confirmed at health facilities other than HCPA. In this sample, 25% of patients underwent breast biopsy before attending a UBS consultation and, therefore, many of them already had a BC diagnosis at the time they were consulting at a UBS. Even with a confirmed anatomopathological diagnosis in hand, these patients must follow the same process as those without a diagnosis, including waiting for a UBS consultation and referral to a hospital via the GERCON system. Therefore, these patients are at a higher risk of delayed treatment initiation because, under the 60-days law, the countdown starts once the diagnosis is confirmed. However, the referral system within the SUS does not prioritize these patients over those without a confirmed diagnosis, which the authors believe is a weakness in the referral process.\u003c/p\u003e \u003cp\u003eRegarding the study's limitations, it is important to note that, as a cross-sectional study conducted at a single institution, caution should be taken when generalizing the reported findings, despite their alignment with the reviewed literature. While some variables showed an impact on the number of days to initiate oncological treatment, this difference did not reach statistical significance, which may reflect the limited sample size. Finally, it is worth emphasizing that, unlike studies based on cancer registry data from public institutions (which are often imprecise), the current study was conducted through an individual review of electronic medical records and, when possible, direct contact with the participants. This approach enhances the accuracy of the reported results.\u003c/p\u003e \u003cp\u003eThe study was capable of identifying a large proportion of patients (70.01%) that began treatment within 60 days from diagnosis. When considering only those who underwent biopsy at HCPA, the percentage increased to 79.2%, which is significantly higher than the national average. Between 2016 and 2018, only 55.1% of BC patients in Brazil started treatment within 60 days (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). This figure dropped to 45.5% in 2019 and 51.3% in 2020 (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). In the state of Piau\u0026iacute;, for instance, only 28.4% of patients began treatment within the legally mandated period in 2018 (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eBased on the present study, it was possible to identify the population most vulnerable to treatment delays: patients with low educational level and skin color \u003cem\u003epardo\u003c/em\u003e. This population should therefore be monitored individually to address these disparities. One potential solution to reduce this inequity is the implementation of patient navigation programs to assist and guide patients and their families from the pre-diagnostic period until the initiation of oncological treatment. This approach is recommended by Law No. 14,758 as part of the National Cancer Prevention and Control Policy within the SUS as the use of patient navigators reduces both the time to breast cancer diagnosis (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e) and the time to treatment initiation (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e).\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eCurrently, BC treatment is complex and requires synchronized efforts from various professionals and healthcare services to ensure timely initiation of therapy. The present study demonstrated that low educational level is a risk factor for delayed initiation of oncological treatment. Moreover, this association persists even among patients who underwent biopsy at the same institution where their initial treatment was established. Self-declared skin color \u003cem\u003epardo\u003c/em\u003e also emerged as a risk factor, although this finding should be further explored in specific studies due to the small number of participants. Regarding the 60-days law, it is essential to identify socially vulnerable populations to prevent delays in oncological treatment. Furthermore, this study was able to gather data regarding the pre-diagnostic period, a topic that is rarely discussed in Brazilian guidelines and scientific studies, highlighting that the median time of 94 days to establish a cancer diagnosis from the point of suspicion exceeds the time frame established by law. This period, during which the patient has not yet received a cancer diagnosis, should be minimized to increase the chances of diagnosing smaller tumors with a higher likelihood of cure.\u003c/p\u003e \u003cp\u003eAs previously mentioned, it is essential that government measures are specifically directed towards the most vulnerable populations. The use of nurse navigators, for example, has proven to be an effective strategy in reducing time to cancer treatment. Educational measures should also be encouraged to raise public awareness about signs and symptoms suggestive of cancer, thereby shortening the pre-diagnostic period.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eEthics approval, consent to participate and consent for publication: The project was approved by the Research Ethics Committee of the Hospital de Cl\u0026iacute;nicas de Porto Alegre (CEP/HCPA) under registration number 71160423.7.0000.5327 (CAAE). The study followed current guidelines and regulations on research involving human subjects, respecting bioethical principles such as autonomy and non-maleficence. The collected data was used exclusively for the analyses of this study with precautions to minimize risks related to confidentiality as provided for in Resolution No. 466/2012 of the Brazilian National Health Council (CNS/MS). All patients gave consent to participate and to publish data from this study.\u003c/p\u003e\n\u003cp\u003eCompeting interests: the authors have no conflict of interest regarding this publication.\u003c/p\u003e\n\u003cp\u003eFunding: This research project received an award from the City Cancer Challenge, a non-governmental organization that promotes initiatives aimed at improving access to cancer treatment in developing countries. This support was essential for the successful completion of this study.\u003c/p\u003e\n\u003cp\u003eRegarding the availability of data and materials, datasets used in the analysis are exclusively in possession of the first author (Pedro Cacilhas) to minimize risks related to confidentiality.\u003c/p\u003e\n\u003cp\u003eAuthor \u0026apos;s contribution: Pedro Marchiori Cacilhas (PC), Alice de Medeiros Zelmanowicz (AZ) and Daniela Dornelles Rosa (DR) wrote and reviewed the main manuscript. PC, Gustavo Thomas (GT), Karine Lorenzen Molina (KM) and Pedhro Lennon Cezario de Freitas (PF) collected the data regarding the participants. PF was responsible for literature review. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003eAcknowledgments: City Cancer Challenge, a non-governmental organization that supported this study.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eMINIST\u0026Eacute;RIO DA SA\u0026Uacute;DE Instituto Nacional de C\u0026acirc;ncer (INCA). Estimativa | 2023 Incid\u0026ecirc;ncia de C\u0026acirc;ncer no Brasil.\u003c/li\u003e\n\u003cli\u003eSouza CB, Fustinoni SM, Amorim MHC, Zandonade E, Matos JC, Schirmer J. Estudo do tempo entre o diagn\u0026oacute;stico e in\u0026iacute;cio do tratamento do c\u0026acirc;ncer de mama em idosas de um hospital de refer\u0026ecirc;ncia em S\u0026atilde;o Paulo, Brasil. Ci\u0026ecirc;nc Sa\u0026uacute;de Colet Impr. 2015;20(12):3805\u0026ndash;16.\u003c/li\u003e\n\u003cli\u003eCosta JB, Lima MAGD, Neves RDF. O retorno ao trabalho de mulheres ap\u0026oacute;s a experi\u0026ecirc;ncia do c\u0026acirc;ncer de mama: uma metass\u0026iacute;ntese. Rev Bras Sa\u0026uacute;de Ocupacional. 2020;45:e19.\u003c/li\u003e\n\u003cli\u003eNg ET, Ang RZ, Tran BX, Ho CS, Zhang Z, Tan W, et al. Comparing Quality of Life in Breast Cancer Patients Who Underwent Mastectomy Versus Breast-Conserving Surgery: A Meta-Analysis. Int J Environ Res Public Health. 2019 Dec 6;16(24):4970.\u003c/li\u003e\n\u003cli\u003eAbdel-Razeq H, Mansour A, Edaily S, Dayyat A. Delays in Initiating Anti-Cancer Therapy for Early-Stage Breast Cancer-How Slow Can We Go? J Clin Med. 2023 Jul 5;12(13):4502.\u003c/li\u003e\n\u003cli\u003eLEI N\u003csup\u003eo\u003c/sup\u003e 12.732, DE 22 DE NOVEMBRO DE 2012. [Internet]. Available from: https://www.planalto.gov.br/ccivil_03/_ato2011-2014/2012/lei/l12732.htm\u003c/li\u003e\n\u003cli\u003eJomar RT, Velasco NS, Mendes GLQ, Guimar\u0026atilde;es RM, Fonseca VADO, Meira KC. Fatores associados ao tempo para submiss\u0026atilde;o ao primeiro tratamento do c\u0026acirc;ncer de mama. Ci\u0026ecirc;nc Sa\u0026uacute;de Coletiva. 2023 Jul;28(7):2155\u0026ndash;64.\u003c/li\u003e\n\u003cli\u003eNogueira MC, Atty AT de M, Tomazelli J, Jardim BC, Bustamante-Teixeira MT, Azevedo E Silva G. Frequency and factors associated with delay in breast cancer treatment in Brazil, according to data from the Oncology Panel, 2019-2020. Epidemiol E Serv Saude Rev Sist Unico Saude Bras. 2023;32(1):e2022563.\u003c/li\u003e\n\u003cli\u003eMaschmann RM, De Jesus RG, Werutsky G, Rebelatto TF, Queiroz G, Simon SD, et al. Time interval between diagnosis to treatment of breast cancer and the impact of health insurance coverage: a sub analysis of the AMAZONA III Study (GBECAM 0115). Breast Cancer Res Treat. 2023 Feb;198(1):123\u0026ndash;30.\u003c/li\u003e\n\u003cli\u003eCabral ALLV, Giatti L, Casale C, Cherchiglia ML. Vulnerabilidade social e c\u0026acirc;ncer de mama: diferenciais no intervalo entre o diagn\u0026oacute;stico e o tratamento em mulheres de diferentes perfis sociodemogr\u0026aacute;ficos. Ci\u0026ecirc;nc Sa\u0026uacute;de Colet Impr. 2019;613\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eBorges RB, Mancuso ACB, Camey SA, Leotti VB, Hirakata VN, Azambuja GS, et al. Power and Sample Size for Health Researchers: uma ferramenta para c\u0026aacute;lculo de tamanho amostral e poder do teste voltado a pesquisadores da \u0026aacute;rea da sa\u0026uacute;de. Clin Biomed Res [Internet]. 2021 Apr 13 [cited 2024 Nov 20];\u003c/li\u003e\n\u003cli\u003eBarros AJ, Hirakata VN. Alternatives for logistic regression in cross-sectional studies: an empirical comparison of models that directly estimate the prevalence ratio. BMC Med Res Methodol. 2003 Oct 20;3(1):21.\u003c/li\u003e\n\u003cli\u003eWaks AG, Winer EP. Breast Cancer Treatment: A Review. JAMA. 2019 Jan 22;321(3):288.\u003c/li\u003e\n\u003cli\u003eRichards, MA et al. Influence of delay on survival in patients with breast cancer: a systematic review. Volume 353(Issue 9159, 1119-1126).\u003c/li\u003e\n\u003cli\u003eAbdel-Razeq H, Mansour A, Edaily S, Dayyat A. Delays in Initiating Anti-Cancer Therapy for Early-Stage Breast Cancer\u0026mdash;How Slow Can We Go? J Clin Med [Internet]. 2023;12(13). \u003c/li\u003e\n\u003cli\u003eAn D, Choi J, Lee J, Kim JY, Kwon S, Kim J, et al. Time to surgery and survival in breast cancer. BMC Surg. 2022 Nov 11;22(1):388.\u003c/li\u003e\n\u003cli\u003eHo PJ, Cook AR, Binte Mohamed Ri Nur Khaliesah and Liu J, Li J, Hartman M. Impact of delayed treatment in women diagnosed with breast cancer: A population-based study. Cancer Med. 2020 Feb;9(7):2435\u0026ndash;44.\u003c/li\u003e\n\u003cli\u003eFlores-Balc\u0026aacute;zar CH, Flores-Luna ML, Villarreal-Garza CM, Bargall\u0026oacute;-Rocha JE. Provider delay in treatment initiation and its influence on survival outcomes in women with operable breast cancer. Rep Pract Oncol Radiother. 2020;25(2):271\u0026ndash;5.\u003c/li\u003e\n\u003cli\u003eLEI N\u003csup\u003eo\u003c/sup\u003e 13.896, DE 30 DE OUTUBRO DE 2019 [Internet]. Sect. Se\u0026ccedil;\u0026atilde;o 1. Available from: https://www2.camara.leg.br/legin/fed/lei/2019/lei-13896-30-outubro-2019-789326-publicacaooriginal-159304-pl.html\u003c/li\u003e\n\u003cli\u003eBarros \u0026Acirc;F, Murta-Nascimento C, Abdon CH de, Nogueira DN, Lopes ELC, Dias A. Factors associated with time interval between the onset of symptoms and first medical visit in women with breast cancer. Cad Saude Publica. 2020;36(2):e00011919.\u003c/li\u003e\n\u003cli\u003eRivera-Franco MM, Leon-Rodriguez E. Delays in Breast Cancer Detection and Treatment in Developing Countries. Breast Cancer Basic Clin Res. 2018 Jan 1;12:1178223417752677.\u003c/li\u003e\n\u003cli\u003eSousa SMMT, Carvalho MDGFDM, Santos J\u0026uacute;nior LA, Mariano SBC. Acesso ao tratamento da mulher com c\u0026acirc;ncer de mama. Sa\u0026uacute;de Em Debate. 2019 Sep;43(122):727\u0026ndash;41.\u003c/li\u003e\n\u003cli\u003ePalmieri FM, Deperi ER, Mincey BA, Smith JA, Wen LK, Chewar DM, et al. Comprehensive Diagnostic Program for Medically Underserved Women With Abnormal Breast Screening Evaluations in an Urban Population. Mayo Clin Proc. 2009 Apr;84(4):317\u0026ndash;22.\u003c/li\u003e\n\u003cli\u003eZibrik K, Laskin J, Ho C. Integration of a Nurse Navigator into the Triage Process for Patients with Non-Small-Cell Lung Cancer: Creating Systematic Improvements in Patient Care. Curr Oncol. 2016 Jun 1;23(3):280\u0026ndash;3.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":true,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Breast neoplasms, Breast Cancer, Time to Treatment, Treatment Delay, Door-to-Treatment","lastPublishedDoi":"10.21203/rs.3.rs-5903519/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5903519/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cb\u003eObjective\u003c/b\u003e\u003c/p\u003e \u003cp\u003ethe aim of this study is to identify the association between educational level and delays in the initiation of oncological treatment.\u003c/p\u003e\u003cp\u003e\u003cb\u003eMethods\u003c/b\u003e\u003c/p\u003e \u003cp\u003ecross-sectional study that evaluated all female patients with BC between January 2022 and December 2023 registered in the Cancer Registry (CR) of Hospital de Cl\u0026iacute;nicas de Porto Alegre (HCPA). Data collection of the sample was made through electronic medical record review and telephone questionnaires applied on the participants. Descriptive, univariable and multivariable analyses were performed to assess factors associated with the prevalence of delayed treatment initiation. A sample size of 178 subjects was calculated based on retrospective data.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResults\u003c/b\u003e\u003c/p\u003e \u003cp\u003e307 participants had their data collected between June 1st 2023 until February 1st 2024. and were included in the analysis. In the multivariable analysis, initiation of treatment\u0026thinsp;\u0026gt;\u0026thinsp;60 days after diagnosis was significantly associated with lower educational level, with an estimated relative risk (RR) of 1.48 (IC 95% = 1.064\u0026ndash;2.062). The ethnicity \u0026ldquo;pardo\u0026rdquo;, which refers to mixed-race individuals, was correlated with a longer time to treatment when compared to white patients (RR\u0026thinsp;=\u0026thinsp;1.63; IC 95% = 1.038\u0026ndash;2.579).\u003c/p\u003e\u003cp\u003e\u003cb\u003eConclusion\u003c/b\u003e\u003c/p\u003e \u003cp\u003eThis cross-sectional study provides evidence that educational level had a significant impact on time to oncological treatment in our cohort, demonstrated through a multivariable analysis. In addition, self-reported mixed-race ethnicity was also associated with delay. The study also demonstrated that although most participants had their treatment started within 60 days, the time between suspicion of cancer and diagnosis was larger than stipulated by law.\u003c/p\u003e","manuscriptTitle":"Socio-Demographic Factors and Time to Breast Cancer Treatment in a High-Complexity Hospital in Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-28 11:17:47","doi":"10.21203/rs.3.rs-5903519/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2025-04-29T13:43:33+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"54181849544595954188363573532682178790","date":"2025-04-26T04:10:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-04-22T09:01:29+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-04-21T06:37:09+00:00","index":"","fulltext":""},{"type":"submitted","content":"Archives of Public Health","date":"2025-04-12T15:06:05+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"archives-of-public-health","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"aoph","sideBox":"Learn more about [Archives of Public Health](http://archpublichealth.biomedcentral.com/)","snPcode":"13690","submissionUrl":"https://submission.nature.com/new-submission/13690/3","title":"Archives of Public Health","twitterHandle":"@Archpubhealth","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"em","reportingPortfolio":"BMC/SO AJ","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"09936551-7931-46e8-b48f-e215b5e6d553","owner":[],"postedDate":"April 28th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2025-04-30T05:23:17+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-28 11:17:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5903519","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5903519","identity":"rs-5903519","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}