Real-World Treatment Patterns and Outcomes in Hormone Receptor Positive HER2 Negative Early-Stage Breast Cancer in a Private Community Oncology Practice of Brazil

Real-World Treatment Patterns and Outcomes in Hormone Receptor Positive HER2 Negative Early-Stage Breast Cancer in a Private Community Oncology Practice of 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 Real-World Treatment Patterns and Outcomes in Hormone Receptor Positive HER2 Negative Early-Stage Breast Cancer in a Private Community Oncology Practice of Brazil Aline Goncalves, Tomas Reinert, Heloisa Cruz, Matheus Silva, Max Mano, and 11 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4952483/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 Purpose This study aims to assess the disease characteristics, practice patterns and real-world outcomes of patients (pts) with HR positive (+)/HER2 negative (-) early breast cancer (EBC) treated in Brazil's largest network of community oncology practices. Methods Retrospective study from the Oncoclínicas&CO real-world database from 2016 to 2021. We assessed risk profile distribution (high-risk [HR], intermediate-risk [IR] or low-risk [LR]) as per recent adjuvant trials in EBC, endocrine and chemotherapy (CT) prescriptions and 3-year invasive disease-free survival (iDFS). Results In total, 1,786 cases were selected for the study. Median age was 57 years, 566 (32%) were premenopausal, 1,179 (66%) were LR, 351 (20%) IR, and 256 (14%) HR. In post-menopausal pts, aromatase inhibitor (AI) was used by 74% with LR, 79% with IR and 83% with HR. In premenopausal pts, ovarian function suppression (OFS) – combined with tamoxifen or AI – was prescribed to 18% LR pts, 15% IR, and 48% HR. CT was offered to 32%, 38%, and 73% of postmenopausal pts in LR, IR, and HR groups. In premenopausal pts, 55%, 57%, and 78% received CT in LR, IR, and HR groups. The 3-year iDFS was 86% (95% CI 84%-89%) in LR population, 87% (82%-91%) in IR, and 72% (95% CI 65%-81%) in HR. Conclusions In this large real-world cohort of patients treated in a private setting in Brazil, most pts are diagnosed with low-risk EBC. We found that a significant proportion of premenopausal pts with high-risk EBC were not treated with OFS and did not receive CT. Early breast cancer Hormone receptor positive breast cancer real-world data Figures Figure 1 Figure 2 INTRODUCTION Breast cancer (BC) is a global health challenge, representing the most diagnosed cancer and the leading cause of cancer-related mortality among women worldwide ( 1 ). While substantial progress has been made in high-income countries (HICs) regarding early detection and treatment, low- and middle-income countries (LMICs) continue to bear a disproportionate burden of the disease ( 2 ). BC in LMICs presents unique challenges compared to HICs, including a higher proportion of younger patients and advanced disease at diagnosis ( 3 ). In Brazil, BC is the most common malignant neoplasm affecting women with estimated rate of 73.610 new cases annually for the period 2023–2025 ( 4 ). Among the molecular subtypes of BC, hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) disease represents the most prevalent subtype, accounting for approximately 70% of cases( 5 ). Adjuvant endocrine therapy (ET) plays a central role in the management of early-stage BC (EBC) HR+/HER2-, aimed at reducing the risk of recurrence and improving long-term outcomes( 6 ). Recent advancements in personalized medicine have revolutionized therapeutic strategies for this subtype, integrating risk stratification concepts and introducing agents such as cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) into clinical practice ( 7 ). In the era of personalized oncology, real-world evidence (RWE) studies play a crucial role in complementing findings from clinical trials and providing insights into treatment effectiveness and safety in routine clinical practice, including patient profiling underrepresented in randomized and controlled studies ( 8 ). RWE studies conducted in diverse patient populations, including those from LMICs, offer valuable perspectives on the utilization of healthcare resources and linked outcomes, informing evidence-based decision-making and improving patient care ( 9 ). This study aims to evaluate the proportion of HR+/HER2- EBC with high-risk or intermediate-risk profile and the clinical outcomes of patients receiving care within the Oncoclínicas&CO, the largest network of private oncology centers in Brazil. By generating robust real-world data, this study seeks to contribute to a deeper understanding of the disease characteristics, treatment patterns, and survival estimates with potential impact in guiding medical education efforts, clinical research initiatives, and developing guidelines and health policies. MATERIALS AND METHODS Retrospective cohort of patients with HR+/HER2- EBC with clinical and pathological data extracted from electronic medical files and pharmacy registries. The population of interest was selected from Oncoclínicas&CO institutional central database, which includes data from over 200,000 cancer patients treated in community oncology practices (23,233 breast cancer cases) representing 70 clinical sites located in 11 out of 27 federative units of Brazil. We combine longitudinal electronic health record (EHR) data from all sites in a cloud-based platform, which includes structured EHR data (patient demographics, disease stage, anti‐cancer drug prescriptions, and others) with elements from unstructured sources (such as physician notes and digitized histopathology reports) using technology‐based abstraction techniques. Trained data curators qualify the data using predefined ontology and actively search for critical outcomes in the patient disease trajectory, including treatment intent, relapse, and death events. External linkage of national death registries guarantees complete information of survival endpoints. After HR+/HER2- EBC patients diagnosed between 2016 and 2021 were identified, pre-curated data was exported from institutional database to an electronic case report form platform (REDCap) designed for this study to guide manual review of electronic charts and digitized reports. This second step involved the qualification of pre‐curated data (such as patient demographics, disease characteristics, treatment exposure and relapse or death events) and the complete manual abstraction of other variables that initially were not fully curated (such as histopathology reports and molecular and genetic test results). The study involved primary data collection with trained data curators. Although data are available from Oncoclínicas&CO institutional central database, manual data cleaning was performed to ensure validity and quality. Patients were eligible if treated in one of Oncoclínicas&CO units in the (neo)adjuvant setting with a minimal follow-up from EBC diagnosis to last patient visit of 6 months. Patients were excluded if they had metastatic disease at diagnosis, insufficient information to establish EBC risk based on clinical and pathological criteria (lack of documentation on TNM staging at diagnosis, histological grade and/or Ki67), undocumented status of HR and HER2, lacking minimal pharmacy registry according to data curators’ and researchers’ interpretation. The entire Oncoclínicas&CO institutional database was screened for the inclusion criteria of interest, and no sampling was performed to guarantee maximum representativeness. The primary objective of the study was to characterize the clinicopathological data of this cohort of patients with HR+/HER2- EBC and its stratification according to categories of low, intermediate, or high risk. Patients were classified according to risk strata with the following parameters based on the NATALEE trial ( 10 ): high-risk (HR) if 4 + axillary lymph nodes (LN), or 1–3 LN plus either tumor size ≥ 5 cm or grade 3 or Ki67 ≥ 20% or high-risk OncotypeDX/MammaPrint, or any T4 tumor; intermediate-risk (IR) if non-high-risk stage II or III, considering, at least, stage IIA with 1 to 3 lymph nodes (pN1) or pN0 grade 3 or pN0 grade 2 with either Ki67 ≥ 20% or high-risk OncotypeDX/MammaPrint; and low-risk (LR) if stages I or IIA, grade 1 or 2 disease and Ki76 < 20%. Secondary objectives include a detailed analysis of the characteristics of this cohort with clinicopathological data (age, menopausal status, staging); treatment patterns (use of chemotherapy, type of endocrine therapy, use of ovarian function suppression in premenopausal patients) and outcomes (invasive disease-free survival). Stage was defined as per TNM eight edition: clinical staging was adopted when patients received neoadjuvant therapy, while the pathological staging criteria was used when upfront surgery was performed. The definition of an invasive disease-free survival (iDFS) event included invasive local, regional, and distant recurrences, contralateral breast cancer, second non-breast primary cancer and death from any cause, as per STEEP criteria ( 11 ). Survival was estimated using the Kaplan–Meier method, and the log‐rank test was used for statistical comparison. All patients had breast cancer surgery, and starting time point for iDFS calculation was date of surgery. Univariate Cox proportional hazard models were used to obtain hazard ratios (HRs) with 95% CIs. All data was processed in the R programming environment, version 4.0.5, along with Microsoft Office Excel and readxl package version 1.3.1 to load the data. The project was approved by local Ethics Committee with waiver of patient consent. We expected to identify at least 1,500 eligible patients, which would provide 2% absolute precision around the expected proportion of high-risk EBC of 8% with a 95% confidence interval. RESULTS In total, 1,786 cases were selected for the study based on predefined eligibility criteria and target sample size. The patient cohort primarily consisted of women, with only 19 (1.1%) men. Median age was 57 years (range 27–96). Regarding menopausal status, 566 (32%) patients were premenopausal, while 1,220 (68.3%) were postmenopausal. Disease staging revealed that 1,052 (59%) individuals had stage I disease, 372 (21%) were stage IIA, 165 (9%) stage IIB, and 197 (11%) stage III EBC. Gene expression profiling, OncotypeDX or MammaPrint assays, was conducted in a small subset of 50 (2.8%) patients. Germline BRCA1/2 status was available for 109 (6.1%) individuals, revealing pathogenic or likely pathogenic (P/LP) variants in 28 patients (25.7% of the patients tested). A summary of demographic and clinicopathological characteristics is presented in Table 1 . Table 1 Patient Demographic Characteristics and Tumor Staging Patients Characteristics Number % Gender Female 2 98.9 Male 19 1.1 Age (year) ≤ 30 20 1.1 31–40 203 11.4 41–50 413 23.1 51–60 391 21.9 61–70 425 23.8 71–80 253 14.2 ≥ 81 81 4.5 Elderly (≥ 65) 574 32.1 Median 57.1 Range 27–96 ECOG 0 771 43.2 1 978 54.8 2 5 0.3 Missing 32 1.8 Year of diagnosis 2016 279 15.6 2017 288 16.1 2018 254 14.2 2019 287 16.1 2020 267 14.9 2021 411 23.0 Menopausal status Premenopausal 566 31.7 Postmenopausal 1,220 68.3 Stage IA 606 33.9 IB 446 24.7 IIA 372 20.8 IIB 165 9.2 IIIA 128 7.2 IIIB 69 3.9 Brazil region Rio de Janeiro 945 52.9 Minas Gerais 401 22.5 Bahia 186 10.4 Pernambuco 129 7.2 São Paulo 125 7.0 As illustrated in Fig. 1 , overall, 1,179 (66%) were classified as LR, 351 (20%) as IR, and 256 (14%) as HR. Notably, high-risk stratification was enriched in premenopausal population. Among premenopausal women, 62.4% were categorized as LR, 19.4% as IR, and 18.2% as HR versus 67.7%, 19.8%, and 12.5%, respectively, for postmenopausal patients. As illustrated in Table 2 , among postmenopausal patients, an aromatase inhibitor (AI) therapy was the most used endocrine agent and was administered to 74% of LR, 79% of IR, and 83% of HR patients. In the premenopausal patients’ cohort, ovarian function suppression (OFS), either in combination with tamoxifen or AI, was prescribed to 18% of LR patients, 15% of IR patients, and 48% of HR patients, with the remaining patients having received tamoxifen only. Chemotherapy (CT) was offered to 32%, 38%, and 73% of postmenopausal patients in the LR, IR, and HR groups, respectively. Among premenopausal patients, CT prescription was 55%, 57%, and 78%, respectively, in the LR, IR, and HR groups. Table 2 Proportions of Patients by Treatment Class, Menopause Status, and Risk Category. Risk category Endocrine therapy Chemotherapy Tamoxifen Aromatase inhibitor Ovarian Function Suppression Premenopausal High (N = 103) 52% NA 48% 78% Intermediate (N = 110) 85% NA 15% 57% Low (N = 353) 82% NA 18% 55% Postmenopausal High (N = 153) 18% 83% NA 73% Intermediate (N = 241) 21% 79% NA 38% Low (N = 826) 26% 74% NA 32% With a median follow-up of 2 years, the median iDFS for the overall population was not reached, as shown in Fig. 2 A. Stratified analysis by risk assessment revealed a median iDFS of 67.9 months (95% CI 52.7-NA) for HR patients, while it was not reached for IR and LR groups. The 3-year iDFS rate in the general population was 85% (95% CI 81%-89%), 80% (76%-85%) in premenopausal patients, and 86% (84%-89%) in postmenopausal patients. For the HR population, 3-year iDFS rate was 72% (61%-84%). In the population with either HR or IR, 3-year iDFS rate was 83% (75%-92%). Among premenopausal patients, the 3-year iDFS rates were 81% for LR (75%-87%), 94% for IR (89%-99%), and 64% for HR (51%-80%), as shown in Fig. 2 B. In postmenopausal patients, the 3-year iDFS rates were 88% for LR (85%-92%), 84% for IR (78%-90%), and 78% for HR (68%-88%), as shown in Fig. 2 C. DISCUSSION Our work describes RWD from a large Brazilian cohort of patients with HR+/HER2- EBC treated in routine care in the private healthcare setting. We describe clinical characteristics, patterns of systemic therapy, and survival outcomes. Among the main findings are the distribution of patients into clinicopathological risk categories. These data are critical considering incorporating therapeutic agents, such as adjuvant abemaciclib for selected high-risk patients with HR+/HER2- EBC disease. Furthermore, systemic treatment patterns are described, and trends toward possible underuse of chemotherapy and OFS in premenopausal patients with intermediate or high-risk disease can be observed, which may negatively impact patients’ outcomes treated in routine practice. Real-world data (RWD) on patients with BC holds paramount importance in shaping evidence-based clinical decisions and optimizing patient outcomes. Unlike data from controlled clinical trials, RWD provides insights into the broader patient population encountered in routine clinical practice, offering a comprehensive understanding of treatment patterns, effectiveness, and gaps in access or utilization of therapies in diverse patient demographics and healthcare settings( 12 ). Additionally, RWD is a cornerstone for pharmacoeconomic studies, facilitating cost-effectiveness analyses, resource allocation decisions, and healthcare policy development in public and private settings( 13 ). The multidisciplinary management of HR+/HER2- EBC has seen significant advances with the incorporation of personalized systemic treatment strategies based on the classification of patients into low-, intermediate-, and high-recurrence risk groups. This classification is made according to clinicopathological risk factors, such as tumor size, lymph node involvement, and histological grade. Furthermore, biomarkers such as Ki67 expression and gene expression signatures such as OncotypeDX and MammaPrint are complementary. Patients with low-risk tumors, characterized by having a small, low-grade tumor and no lymph node involvement, can be treated with de-escalation strategies, especially if postmenopausal. On the other hand, patients with intermediate-risk and high-risk tumors should be considered for treatment escalation strategies with the use of chemotherapy, OFS in premenopausal women and combination endocrine therapy (ET) with CDK4/6i or PARP inhibitors (in patients with BRCA1/2 germline pathogenic variants). We acknowledge that the definitions for low, intermediate, and high-risk categories are relatively arbitrary and there is no consensus in the main guidelines for breast oncology. Nevertheless, it is important to highlight that we adopted the criteria used in the main phase III randomized clinical trials (RCTs) that evaluated the use of CDK4/6 inhibitors in the adjuvant setting, the monarchE study( 14 ) (which included only clinically high-risk patients) and the NATALEE study (with broader criteria for intermediate- and high-risk disease) ( 10 ). These recent RCTs have demonstrated a benefit in iDFS outcomes by incorporating abemaciclib and ribociclib into standard endocrine therapy. In the monarchE study, patients with high-risk clinicopathological characteristics were randomized to use ET with or without abemaciclib. The abemaciclib group had improved iDFS versus ET alone (HR 0.68, 95%CI 0.57–0.80, p < .0001). The 3-year iDFS rate in the experimental arm was 88.6% vs 82.9% in the control arm, translating into an absolute risk reduction of 5.7% with abemaciclib ( 14 ). Adjuvant ribociclib was evaluated in the phase III RCT NATALLEE, which randomized patients with intermediate and high-risk characteristics and demonstrated a gain in iDFS favoring the group that used ribociclib with an HR of 0.74 (95% CI 0.62–0.89, p = 0,0006) and 3-year iDFS of 90.7% in the ribociclib arm and 87.6% in the control arm( 10 ). The main findings of our RWD study can be divided into three themes. Firstly, we provide epidemiological data related to stratification into risk groups. This information has several potential implications, such as estimating potential patients eligible for systemic treatment (de)escalation strategies in our routine clinical practice. Second, we provide data on treatment patterns in routine clinical practice. Lastly, we describe the survival outcomes, primarily 3-year iDFS rates in cohorts grouped according to menopausal status and risk categorization. In our cohort, patterns of ET and CT use are described and call attention to the potential underuse of adjuvant systemic treatment strategies such as OFS and CT in premenopausal patients, which have robust evidence of clinical benefit in patients with intermediate and high-risk disease. Such findings have also been reported in other cohorts, such as the recent report by Heredia A et al. that showed that in a retrospective cohort of patients younger than 35 with EBC HR + from Chile, less than 20% received OFS ( 15 ). And even in the RxPONDER Trial that included 12.7% of premenopausal women, only 6.3% in the chemoendocrine group and 19.0% in the endocrine-only group had received OFS ( 16 ). This information impacts the development of medical education initiatives and the standardization of institutional pathways of care. We have also found a numeric difference in 3-year iDFS rates when indirectly comparing our real-world population to patients enrolled in the control arms of RCTs. For example, in our cohort’s high-risk group, the 3-year iDFS was 72% (versus 84% 3-year iDFS in the control arm of the monarchE trial)( 14 ). Also, the intermediate- and high-risk populations in our RWD study had 3-year iDFS of 83% (versus 87% 3-year iDFS in the control arm of the NATALEE trial)( 10 ). These observations underscore a concerning disparity between real-world outcomes and those observed in controlled trial settings. Several factors could contribute to this difference, including the definitions used for patient eligibility in the studies, variations in patient demographics, comorbidities, treatment adherence, and access to supportive care services ( 17 ). Additionally, the heterogeneity of patient populations in real-world settings, which often include individuals with more complex health profiles than those enrolled in clinical trials, may also play a significant role ( 18 ). For this reason, any formal comparison would have been biased, and inferences could be inaccurate. However, the implications of these findings are profound, suggesting the need for closer examination of real-world treatment outcomes and the development of strategies to address potential disparities to ensure that patients in clinical practice receive optimal care and support to improve their outcomes. Moreover, this information may be crucial in pharmacoeconomics, as incorporating new agents, such as CDK4/6 inhibitors in the adjuvant setting, may be associated with a higher absolute risk reduction given the worse prognosis observed in real-world settings. While our study provides valuable insights into the risk profile of patients with HR+/HER2- EBC attending tertiary oncology services, several limitations should be acknowledged. Firstly, the study's retrospective nature introduces inherent biases and limitations, including potential selection bias and incomplete data capture. Secondly, the reliance on electronic health records may result in inaccuracies or missing data, which could impact the validity of our findings. Unfortunately, we did not have access to important information related to adherence to treatment, causes of interruption or changes in treatment, and information about therapies and events after progression. Furthermore, our study was conducted within a single healthcare network that treats Brazilian women with access to the private health system, limiting the generalizability of our results to other populations or healthcare settings, especially the public health setting. However, our study has several strengths that confer robustness and clinical relevance to our findings. Firstly, we analyzed a large cohort of patients treated during a period of uniform perioperative standard-of-care, supporting the generalizability of our findings. Secondly, our detailed examination of clinicopathological characteristics and treatment strategies enables an in-depth analysis of factors affecting patient outcomes. Furthermore, our data underwent a rigorous analysis and review, incorporating specialized data curation to maximize data accuracy. CONCLUSION Our study represents a comprehensive examination of real-world clinical outcomes for Brazilian patients with early-stage HR+/HER2- breast cancer, focusing on their clinicopathological profiles, treatment modalities, and survival rates. It draws attention to the underutilization of certain therapies among specific risk groups and underscores discrepancies in outcomes when juxtaposing real-world data with controlled clinical trials. It also sheds light on the risk of recurrence within the high-risk patient group as defined by this analysis, advocating for developing novel strategies to mitigate it. In addition, we provide critical insights into the management and prognosis of HR+/HER2- EBC, offering meaningful contributions to clinical practice, medical education strategies, implementation of guidelines, as well as for planning research and health management initiatives. Declarations ACKNOWLEDGEMENTS Instituto Oncoclínicas for administrative and ethical support. FUNDING This project was funded by Novartis. CONFLICTS OF INTEREST AG declares advisory role for Roche, Novartis, Pfizer, Lilly, Daiichi-Sankyo received a speaker’s fee from Roche, Novartis, Pfizer, Lilly, Daiichi Sankyo, AstraZeneca, Gilead. RD declares advisory role for Roche, Foundation Medicine, AstraZeneca received a speaker’s fee from Roche, Ipsen, Amgen, Servier, Sanofi, Libbs, Merck Sharp & Dohme, Lilly, AstraZeneca, Janssen, Takeda, Bristol Myers Squibb, GlaxoSmithKline, Gilead, research grants from Merck, Novartis, Daiichi-Sankyo, GlaxoSmithKline and AstraZeneca, and is investor in Trialing Health, S.L. AUTHORS CONTRIBUTION Conception and design: Aline Coelho Goncalves, Tomas Reinert, Max S. Mano, Rodrigo Dienstmann Development of methodology: Rodrigo Dienstmann Acquisition of data: Rafael Duarte Paes, Heloisa Mussato Fernandes da Cruz, Rodrigo Dienstmann Analysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Matheus Costa e Silva, Rodrigo Dienstmann Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Fernanda Christtanini Koyama, Heloisa Mussato Fernandes da Cruz, Matheus Costa e Silva, Rodrigo Dienstmann Writing, review, and/or revision of the manuscript: Aline Coelho Goncalves, Tomas Reinert, Max S. Mano, Cristiano Augusto Andrade de Resende, Gustavo Bretas, Leandro Jonata de Carvalho Oliveira, Maria Cristina Figueroa, Carlos Barrios, Rodrigo Dienstmann Study supervision: Aline Coelho Goncalves, Rodrigo Dienstmann DATA AVAILABILITY Deidentified patient data from this study can be made available to qualified investigators who provide a methodologically sound research proposal and sign a data access agreement. Please email corresponding author for information. The study protocol and REDCap dictionary will also be made available upon request. ETHICS APPROVAL This study was conducted in accordance with local legislation and institution requirements. It was approved by the Ethics Committee protocol 59129322.9.0000.0227 on August 23, 2022. References Bray F, Laversanne M, Sung H et al Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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N Engl J Med 390(12):1080–1091 Tolaney SM, Garrett-Mayer E, White J et al (2021) Updated Standardized Definitions for Efficacy End Points (STEEP) in Adjuvant Breast Cancer Clinical Trials: STEEP Version 2.0. J Clin Oncol 39(24):2720–2731 Cottu P, Ramsey SD, Solà-Morales O, Spears PA, Taylor L (2022) The emerging role of real-world data in advanced breast cancer therapy: Recommendations for collaborative decision-making. Breast 61:118–122 Müller C, Kiver V, Solomayer EF et al (2023) CDK4/6 Inhibitors in Advanced HR+/HER2 - Breast Cancer: A Multicenter Real-World Data Analysis. Breast Care (Basel) 18(1):31–41 Johnston SRD, Harbeck N, Hegg R, Toi M, Martin M, Shao ZM et al (2020) Abemaciclib Combined With Endocrine Therapy for the Adjuvant Treatment of HR+, HER2-, Node-Positive, High-Risk, Early Breast Cancer (monarchE). J Clin Oncol 38(34):3987–3998 Ana Heredia CS (2024) Suboptimal use of ovarian function suppression in very young women with early breast cancer: a real-world data study. Breast Cancer Res Treat 203(1):173–179 Kalinsky K, Barlow WE, Gralow JR et al (2021) 21-Gene Assay to Inform Chemotherapy Benefit in Node-Positive Breast Cancer. N Engl J Med 385(25):2336–2347 Eloranta S, Smedby KE, Dickman PW, Andersson TM (2021) Cancer survival statistics for patients and healthcare professionals - a tutorial of real-world data analysis. J Intern Med 289(1):12–28 Taylor-Stokes G, Mitra D, Waller J, Gibson K, Milligan G, Iyer S (2019) Treatment patterns and clinical outcomes among patients receiving palbociclib in combination with an aromatase inhibitor or fulvestrant for HR+/HER2-negative advanced/metastatic breast cancer in real-world settings in the US: Results from the IRIS study. Breast 43:22–27 Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4952483","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":348447908,"identity":"50e15eb8-5fa1-4dba-9c47-58f039aa56c5","order_by":0,"name":"Aline Goncalves","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAABCElEQVRIie3PsWrDMBCAYQmBvDT1esYheYWYDKXg9lkkDJ4cL4YuDUQgUBZDV+ctOnl2ENhb546ZOjubhxYqh3QoxMRjofqH06D7EELIZvuLOViczltA+NAixH4u2OV9EzkTCogExThyPg2h/s0Y4kqiDu06nFFfVv6DekxdR+D2mKD0TlwmoPE2KOp4Sac1W65UlHl5RbxdibJpNfCMxsqfCM0VJItopQh/fWeUTErEiwEx78mX0Jue6Hu1uU4WPcFCMwpJILHS10lgiJfXcaAgjnD+1vBdvpfmL5DBAJk12w/o1uHchajpuqdn/uLIfXssw3SI/A7T0xRmjAOmz7GLNpvN9p/6BgxnVqqfWzcMAAAAAElFTkSuQmCC","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":true,"prefix":"","firstName":"Aline","middleName":"","lastName":"Goncalves","suffix":""},{"id":348447909,"identity":"45a203ea-022c-41c1-8a7d-46a983f81a62","order_by":1,"name":"Tomas Reinert","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Tomas","middleName":"","lastName":"Reinert","suffix":""},{"id":348447910,"identity":"2c853159-8474-4cb2-b884-1b1833dba59d","order_by":2,"name":"Heloisa Cruz","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Heloisa","middleName":"","lastName":"Cruz","suffix":""},{"id":348447911,"identity":"ddb8e01a-49ac-4cfd-92a1-fede664b2d36","order_by":3,"name":"Matheus Silva","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Matheus","middleName":"","lastName":"Silva","suffix":""},{"id":348447912,"identity":"00c222a3-811c-4fcd-bdd2-058f2bc9eec8","order_by":4,"name":"Max Mano","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Max","middleName":"","lastName":"Mano","suffix":""},{"id":348447913,"identity":"14d8a7aa-7028-4cb6-b38a-4570d03820c7","order_by":5,"name":"Cristiano Resende","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Cristiano","middleName":"","lastName":"Resende","suffix":""},{"id":348447914,"identity":"e4e1f3cc-507e-447a-9199-9a85bdb97909","order_by":6,"name":"Gustavo Bretas","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Gustavo","middleName":"","lastName":"Bretas","suffix":""},{"id":348447915,"identity":"6f8bfc20-791e-451a-a1ae-c10f6c96df68","order_by":7,"name":"Leandro Oliveira","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Leandro","middleName":"","lastName":"Oliveira","suffix":""},{"id":348447917,"identity":"d2b0374b-08fe-416e-ba87-3ce89e342c5d","order_by":8,"name":"Maria Cristina Figueroa","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Cristina","lastName":"Figueroa","suffix":""},{"id":348447918,"identity":"7f6f88e9-858f-4fb7-8e1a-da7f707c1ba6","order_by":9,"name":"Rafael Paes","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Rafael","middleName":"","lastName":"Paes","suffix":""},{"id":348447921,"identity":"ba879e59-daf8-439d-9ce1-f5fb6a9557a2","order_by":10,"name":"Jorge Canedo","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Canedo","suffix":""},{"id":348447930,"identity":"dca16e7e-1c65-4f47-8f02-932c9d280cdf","order_by":11,"name":"Fernanda Koyama","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Fernanda","middleName":"","lastName":"Koyama","suffix":""},{"id":348447934,"identity":"299a4dd7-dd8d-49f9-b939-9a312bf774f1","order_by":12,"name":"Carolina Bueno","email":"","orcid":"","institution":"Novartis (Brazil)","correspondingAuthor":false,"prefix":"","firstName":"Carolina","middleName":"","lastName":"Bueno","suffix":""},{"id":348447943,"identity":"2e6d61b8-a29f-4218-99e1-48c274595a05","order_by":13,"name":"Erica Ferreira","email":"","orcid":"","institution":"Novartis (Brazil)","correspondingAuthor":false,"prefix":"","firstName":"Erica","middleName":"","lastName":"Ferreira","suffix":""},{"id":348447945,"identity":"877db018-a6e5-40b8-9e26-b05f70312967","order_by":14,"name":"Carlos Barrios","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Carlos","middleName":"","lastName":"Barrios","suffix":""},{"id":348447947,"identity":"5dabae81-fd27-4dfb-a271-2f3646c83022","order_by":15,"name":"Rodrigo Dienstmann","email":"","orcid":"","institution":"1.\tOncoclinicas\u0026CO – Medica Scientia Innovation Research (MedSir), São Paulo, Brazil.","correspondingAuthor":false,"prefix":"","firstName":"Rodrigo","middleName":"","lastName":"Dienstmann","suffix":""}],"badges":[],"createdAt":"2024-08-21 14:56:36","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4952483/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4952483/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":66742729,"identity":"b689b80a-c144-4a65-b3ae-dff575448d06","added_by":"auto","created_at":"2024-10-16 06:07:06","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":137874,"visible":true,"origin":"","legend":"\u003cp\u003eRisk profile distribution of the overall population as per initial therapy, with detailed classification of intermediate and high-risk subsets.\u003c/p\u003e","description":"","filename":"Figure110.png","url":"https://assets-eu.researchsquare.com/files/rs-4952483/v1/0e75c194e0dab204c91d0a7c.png"},{"id":66742728,"identity":"ddfaf2ba-3508-4b24-9c4b-eaf48404b0d9","added_by":"auto","created_at":"2024-10-16 06:07:06","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":158456,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curve of invasive disease-free survival stratified by risk category in the overall population (A), on premenopausal patients (B), and on postmenopausal patients (C).\u003c/p\u003e","description":"","filename":"Figure28.png","url":"https://assets-eu.researchsquare.com/files/rs-4952483/v1/bcbcb0aad612d22420650b54.png"},{"id":68471735,"identity":"6e35e5bd-496b-4cee-bbb8-0ccae8f048a2","added_by":"auto","created_at":"2024-11-07 15:09:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":783431,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4952483/v1/b92b4132-2e31-4b6a-9f12-6fabf2c58c20.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Real-World Treatment Patterns and Outcomes in Hormone Receptor Positive HER2 Negative Early-Stage Breast Cancer in a Private Community Oncology Practice of Brazil","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer (BC) is a global health challenge, representing the most diagnosed cancer and the leading cause of cancer-related mortality among women worldwide (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e). While substantial progress has been made in high-income countries (HICs) regarding early detection and treatment, low- and middle-income countries (LMICs) continue to bear a disproportionate burden of the disease (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). BC in LMICs presents unique challenges compared to HICs, including a higher proportion of younger patients and advanced disease at diagnosis (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). In Brazil, BC is the most common malignant neoplasm affecting women with estimated rate of 73.610 new cases annually for the period 2023\u0026ndash;2025 (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAmong the molecular subtypes of BC, hormone receptor-positive (HR+)/human epidermal growth factor receptor 2-negative (HER2-) disease represents the most prevalent subtype, accounting for approximately 70% of cases(\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Adjuvant endocrine therapy (ET) plays a central role in the management of early-stage BC (EBC) HR+/HER2-, aimed at reducing the risk of recurrence and improving long-term outcomes(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Recent advancements in personalized medicine have revolutionized therapeutic strategies for this subtype, integrating risk stratification concepts and introducing agents such as cyclin-dependent kinase 4/6 inhibitors (CDK4/6i) into clinical practice (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eIn the era of personalized oncology, real-world evidence (RWE) studies play a crucial role in complementing findings from clinical trials and providing insights into treatment effectiveness and safety in routine clinical practice, including patient profiling underrepresented in randomized and controlled studies (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e). RWE studies conducted in diverse patient populations, including those from LMICs, offer valuable perspectives on the utilization of healthcare resources and linked outcomes, informing evidence-based decision-making and improving patient care (\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThis study aims to evaluate the proportion of HR+/HER2- EBC with high-risk or intermediate-risk profile and the clinical outcomes of patients receiving care within the Oncocl\u0026iacute;nicas\u0026amp;CO, the largest network of private oncology centers in Brazil. By generating robust real-world data, this study seeks to contribute to a deeper understanding of the disease characteristics, treatment patterns, and survival estimates with potential impact in guiding medical education efforts, clinical research initiatives, and developing guidelines and health policies.\u003c/p\u003e"},{"header":"MATERIALS AND METHODS","content":"\u003cp\u003eRetrospective cohort of patients with HR+/HER2- EBC with clinical and pathological data extracted from electronic medical files and pharmacy registries. The population of interest was selected from Oncocl\u0026iacute;nicas\u0026amp;CO institutional central database, which includes data from over 200,000 cancer patients treated in community oncology practices (23,233 breast cancer cases) representing 70 clinical sites located in 11 out of 27 federative units of Brazil. We combine longitudinal electronic health record (EHR) data from all sites in a cloud-based platform, which includes structured EHR data (patient demographics, disease stage, anti‐cancer drug prescriptions, and others) with elements from unstructured sources (such as physician notes and digitized histopathology reports) using technology‐based abstraction techniques. Trained data curators qualify the data using predefined ontology and actively search for critical outcomes in the patient disease trajectory, including treatment intent, relapse, and death events. External linkage of national death registries guarantees complete information of survival endpoints.\u003c/p\u003e \u003cp\u003e After HR+/HER2- EBC patients diagnosed between 2016 and 2021 were identified, pre-curated data was exported from institutional database to an electronic case report form platform (REDCap) designed for this study to guide manual review of electronic charts and digitized reports. This second step involved the qualification of pre‐curated data (such as patient demographics, disease characteristics, treatment exposure and relapse or death events) and the complete manual abstraction of other variables that initially were not fully curated (such as histopathology reports and molecular and genetic test results). The study involved primary data collection with trained data curators. Although data are available from Oncocl\u0026iacute;nicas\u0026amp;CO institutional central database, manual data cleaning was performed to ensure validity and quality.\u003c/p\u003e \u003cp\u003ePatients were eligible if treated in one of Oncocl\u0026iacute;nicas\u0026amp;CO units in the (neo)adjuvant setting with a minimal follow-up from EBC diagnosis to last patient visit of 6 months. Patients were excluded if they had metastatic disease at diagnosis, insufficient information to establish EBC risk based on clinical and pathological criteria (lack of documentation on TNM staging at diagnosis, histological grade and/or Ki67), undocumented status of HR and HER2, lacking minimal pharmacy registry according to data curators\u0026rsquo; and researchers\u0026rsquo; interpretation. The entire Oncocl\u0026iacute;nicas\u0026amp;CO institutional database was screened for the inclusion criteria of interest, and no sampling was performed to guarantee maximum representativeness.\u003c/p\u003e \u003cp\u003eThe primary objective of the study was to characterize the clinicopathological data of this cohort of patients with HR+/HER2- EBC and its stratification according to categories of low, intermediate, or high risk. Patients were classified according to risk strata with the following parameters based on the NATALEE trial (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e): high-risk (HR) if 4\u0026thinsp;+\u0026thinsp;axillary lymph nodes (LN), or 1\u0026ndash;3 LN plus either tumor size\u0026thinsp;\u0026ge;\u0026thinsp;5 cm or grade 3 or Ki67\u0026thinsp;\u0026ge;\u0026thinsp;20% or high-risk OncotypeDX/MammaPrint, or any T4 tumor; intermediate-risk (IR) if non-high-risk stage II or III, considering, at least, stage IIA with 1 to 3 lymph nodes (pN1) or pN0 grade 3 or pN0 grade 2 with either Ki67\u0026thinsp;\u0026ge;\u0026thinsp;20% or high-risk OncotypeDX/MammaPrint; and low-risk (LR) if stages I or IIA, grade 1 or 2 disease and Ki76\u0026thinsp;\u0026lt;\u0026thinsp;20%. Secondary objectives include a detailed analysis of the characteristics of this cohort with clinicopathological data (age, menopausal status, staging); treatment patterns (use of chemotherapy, type of endocrine therapy, use of ovarian function suppression in premenopausal patients) and outcomes (invasive disease-free survival). Stage was defined as per TNM eight edition: clinical staging was adopted when patients received neoadjuvant therapy, while the pathological staging criteria was used when upfront surgery was performed. The definition of an invasive disease-free survival (iDFS) event included invasive local, regional, and distant recurrences, contralateral breast cancer, second non-breast primary cancer and death from any cause, as per STEEP criteria (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). Survival was estimated using the Kaplan\u0026ndash;Meier method, and the log‐rank test was used for statistical comparison. All patients had breast cancer surgery, and starting time point for iDFS calculation was date of surgery. Univariate Cox proportional hazard models were used to obtain hazard ratios (HRs) with 95% CIs. All data was processed in the R programming environment, version 4.0.5, along with Microsoft Office Excel and readxl package version 1.3.1 to load the data.\u003c/p\u003e \u003cp\u003e The project was approved by local Ethics Committee with waiver of patient consent. We expected to identify at least 1,500 eligible patients, which would provide 2% absolute precision around the expected proportion of high-risk EBC of 8% with a 95% confidence interval.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003eIn total, 1,786 cases were selected for the study based on predefined eligibility criteria and target sample size. The patient cohort primarily consisted of women, with only 19 (1.1%) men. Median age was 57 years (range 27\u0026ndash;96). Regarding menopausal status, 566 (32%) patients were premenopausal, while 1,220 (68.3%) were postmenopausal. Disease staging revealed that 1,052 (59%) individuals had stage I disease, 372 (21%) were stage IIA, 165 (9%) stage IIB, and 197 (11%) stage III EBC. Gene expression profiling, OncotypeDX or MammaPrint assays, was conducted in a small subset of 50 (2.8%) patients. Germline BRCA1/2 status was available for 109 (6.1%) individuals, revealing pathogenic or likely pathogenic (P/LP) variants in 28 patients (25.7% of the patients tested). A summary of demographic and clinicopathological characteristics is presented in Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003ePatient Demographic Characteristics and Tumor Staging\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePatients Characteristics\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNumber\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e%\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eGender\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eFemale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMale\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"9\" rowspan=\"10\"\u003e \u003cp\u003e\u003cb\u003eAge (year)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026le;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e20\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e31\u0026ndash;40\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e203\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e11.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e41\u0026ndash;50\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e413\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e51\u0026ndash;60\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e391\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e21.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e61\u0026ndash;70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e425\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e71\u0026ndash;80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e253\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e4.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eElderly (\u0026ge;\u0026thinsp;65)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e574\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMedian\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e57.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRange\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c4\" namest=\"c3\"\u003e \u003cp\u003e27\u0026ndash;96\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u003cb\u003eECOG\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e771\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e43.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e978\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMissing\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e32\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eYear of diagnosis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2016\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e279\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e15.6\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2017\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e288\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2018\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e254\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2019\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e287\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e16.1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2020\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e267\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e14.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e2021\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e411\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e23.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cb\u003eMenopausal status\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePremenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e566\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePostmenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1,220\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e68.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eStage\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e606\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e446\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e24.7\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e372\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e20.8\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e165\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e9.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIIIA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eIIIB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e\u003cb\u003eBrazil region\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eRio de Janeiro\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e945\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e52.9\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eMinas Gerais\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e401\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e22.5\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBahia\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e186\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e10.4\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePernambuco\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eS\u0026atilde;o Paulo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e125\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e7.0\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAs illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, overall, 1,179 (66%) were classified as LR, 351 (20%) as IR, and 256 (14%) as HR. Notably, high-risk stratification was enriched in premenopausal population. Among premenopausal women, 62.4% were categorized as LR, 19.4% as IR, and 18.2% as HR versus 67.7%, 19.8%, and 12.5%, respectively, for postmenopausal patients.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eAs illustrated in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, among postmenopausal patients, an aromatase inhibitor (AI) therapy was the most used endocrine agent and was administered to 74% of LR, 79% of IR, and 83% of HR patients. In the premenopausal patients\u0026rsquo; cohort, ovarian function suppression (OFS), either in combination with tamoxifen or AI, was prescribed to 18% of LR patients, 15% of IR patients, and 48% of HR patients, with the remaining patients having received tamoxifen only. Chemotherapy (CT) was offered to 32%, 38%, and 73% of postmenopausal patients in the LR, IR, and HR groups, respectively. Among premenopausal patients, CT prescription was 55%, 57%, and 78%, respectively, in the LR, IR, and HR groups.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eProportions of Patients by Treatment Class, Menopause Status, and Risk Category.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"6\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eRisk category\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eEndocrine therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eChemotherapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eTamoxifen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAromatase inhibitor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eOvarian Function Suppression\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePremenopausal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHigh (N\u0026thinsp;=\u0026thinsp;103)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e48%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e78%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIntermediate (N\u0026thinsp;=\u0026thinsp;110)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e85%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e15%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e57%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLow (N\u0026thinsp;=\u0026thinsp;353)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e82%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e55%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u003cb\u003ePostmenopausal\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eHigh (N\u0026thinsp;=\u0026thinsp;153)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e18%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e73%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eIntermediate (N\u0026thinsp;=\u0026thinsp;241)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e21%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e79%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e38%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eLow (N\u0026thinsp;=\u0026thinsp;826)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e26%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e74%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003eNA\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e32%\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWith a median follow-up of 2 years, the median iDFS for the overall population was not reached, as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eA. Stratified analysis by risk assessment revealed a median iDFS of 67.9 months (95% CI 52.7-NA) for HR patients, while it was not reached for IR and LR groups. The 3-year iDFS rate in the general population was 85% (95% CI 81%-89%), 80% (76%-85%) in premenopausal patients, and 86% (84%-89%) in postmenopausal patients. For the HR population, 3-year iDFS rate was 72% (61%-84%). In the population with either HR or IR, 3-year iDFS rate was 83% (75%-92%). Among premenopausal patients, the 3-year iDFS rates were 81% for LR (75%-87%), 94% for IR (89%-99%), and 64% for HR (51%-80%), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eB. In postmenopausal patients, the 3-year iDFS rates were 88% for LR (85%-92%), 84% for IR (78%-90%), and 78% for HR (68%-88%), as shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eC.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eOur work describes RWD from a large Brazilian cohort of patients with HR+/HER2- EBC treated in routine care in the private healthcare setting. We describe clinical characteristics, patterns of systemic therapy, and survival outcomes. Among the main findings are the distribution of patients into clinicopathological risk categories. These data are critical considering incorporating therapeutic agents, such as adjuvant abemaciclib for selected high-risk patients with HR+/HER2- EBC disease. Furthermore, systemic treatment patterns are described, and trends toward possible underuse of chemotherapy and OFS in premenopausal patients with intermediate or high-risk disease can be observed, which may negatively impact patients\u0026rsquo; outcomes treated in routine practice.\u003c/p\u003e \u003cp\u003eReal-world data (RWD) on patients with BC holds paramount importance in shaping evidence-based clinical decisions and optimizing patient outcomes. Unlike data from controlled clinical trials, RWD provides insights into the broader patient population encountered in routine clinical practice, offering a comprehensive understanding of treatment patterns, effectiveness, and gaps in access or utilization of therapies in diverse patient demographics and healthcare settings(\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Additionally, RWD is a cornerstone for pharmacoeconomic studies, facilitating cost-effectiveness analyses, resource allocation decisions, and healthcare policy development in public and private settings(\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe multidisciplinary management of HR+/HER2- EBC has seen significant advances with the incorporation of personalized systemic treatment strategies based on the classification of patients into low-, intermediate-, and high-recurrence risk groups. This classification is made according to clinicopathological risk factors, such as tumor size, lymph node involvement, and histological grade. Furthermore, biomarkers such as Ki67 expression and gene expression signatures such as OncotypeDX and MammaPrint are complementary. Patients with low-risk tumors, characterized by having a small, low-grade tumor and no lymph node involvement, can be treated with de-escalation strategies, especially if postmenopausal. On the other hand, patients with intermediate-risk and high-risk tumors should be considered for treatment escalation strategies with the use of chemotherapy, OFS in premenopausal women and combination endocrine therapy (ET) with CDK4/6i or PARP inhibitors (in patients with BRCA1/2 germline pathogenic variants).\u003c/p\u003e \u003cp\u003e We acknowledge that the definitions for low, intermediate, and high-risk categories are relatively arbitrary and there is no consensus in the main guidelines for breast oncology. Nevertheless, it is important to highlight that we adopted the criteria used in the main phase III randomized clinical trials (RCTs) that evaluated the use of CDK4/6 inhibitors in the adjuvant setting, the monarchE study(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e) (which included only clinically high-risk patients) and the NATALEE study (with broader criteria for intermediate- and high-risk disease) (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). These recent RCTs have demonstrated a benefit in iDFS outcomes by incorporating abemaciclib and ribociclib into standard endocrine therapy. In the monarchE study, patients with high-risk clinicopathological characteristics were randomized to use ET with or without abemaciclib. The abemaciclib group had improved iDFS versus ET alone (HR 0.68, 95%CI 0.57\u0026ndash;0.80, p\u0026thinsp;\u0026lt;\u0026thinsp;.0001). The 3-year iDFS rate in the experimental arm was 88.6% vs 82.9% in the control arm, translating into an absolute risk reduction of 5.7% with abemaciclib (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Adjuvant ribociclib was evaluated in the phase III RCT NATALLEE, which randomized patients with intermediate and high-risk characteristics and demonstrated a gain in iDFS favoring the group that used ribociclib with an HR of 0.74 (95% CI 0.62\u0026ndash;0.89, p\u0026thinsp;=\u0026thinsp;0,0006) and 3-year iDFS of 90.7% in the ribociclib arm and 87.6% in the control arm(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe main findings of our RWD study can be divided into three themes. Firstly, we provide epidemiological data related to stratification into risk groups. This information has several potential implications, such as estimating potential patients eligible for systemic treatment (de)escalation strategies in our routine clinical practice. Second, we provide data on treatment patterns in routine clinical practice. Lastly, we describe the survival outcomes, primarily 3-year iDFS rates in cohorts grouped according to menopausal status and risk categorization. In our cohort, patterns of ET and CT use are described and call attention to the potential underuse of adjuvant systemic treatment strategies such as OFS and CT in premenopausal patients, which have robust evidence of clinical benefit in patients with intermediate and high-risk disease. Such findings have also been reported in other cohorts, such as the recent report by Heredia A et al. that showed that in a retrospective cohort of patients younger than 35 with EBC HR\u0026thinsp;+\u0026thinsp;from Chile, less than 20% received OFS (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). And even in the RxPONDER Trial that included 12.7% of premenopausal women, only 6.3% in the chemoendocrine group and 19.0% in the endocrine-only group had received OFS (\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e). This information impacts the development of medical education initiatives and the standardization of institutional pathways of care.\u003c/p\u003e \u003cp\u003eWe have also found a numeric difference in 3-year iDFS rates when indirectly comparing our real-world population to patients enrolled in the control arms of RCTs. For example, in our cohort\u0026rsquo;s high-risk group, the 3-year iDFS was 72% (versus 84% 3-year iDFS in the control arm of the monarchE trial)(\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e). Also, the intermediate- and high-risk populations in our RWD study had 3-year iDFS of 83% (versus 87% 3-year iDFS in the control arm of the NATALEE trial)(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). These observations underscore a concerning disparity between real-world outcomes and those observed in controlled trial settings. Several factors could contribute to this difference, including the definitions used for patient eligibility in the studies, variations in patient demographics, comorbidities, treatment adherence, and access to supportive care services (\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Additionally, the heterogeneity of patient populations in real-world settings, which often include individuals with more complex health profiles than those enrolled in clinical trials, may also play a significant role (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). For this reason, any formal comparison would have been biased, and inferences could be inaccurate.\u003c/p\u003e \u003cp\u003eHowever, the implications of these findings are profound, suggesting the need for closer examination of real-world treatment outcomes and the development of strategies to address potential disparities to ensure that patients in clinical practice receive optimal care and support to improve their outcomes. Moreover, this information may be crucial in pharmacoeconomics, as incorporating new agents, such as CDK4/6 inhibitors in the adjuvant setting, may be associated with a higher absolute risk reduction given the worse prognosis observed in real-world settings.\u003c/p\u003e \u003cp\u003eWhile our study provides valuable insights into the risk profile of patients with HR+/HER2- EBC attending tertiary oncology services, several limitations should be acknowledged. Firstly, the study's retrospective nature introduces inherent biases and limitations, including potential selection bias and incomplete data capture. Secondly, the reliance on electronic health records may result in inaccuracies or missing data, which could impact the validity of our findings. Unfortunately, we did not have access to important information related to adherence to treatment, causes of interruption or changes in treatment, and information about therapies and events after progression. Furthermore, our study was conducted within a single healthcare network that treats Brazilian women with access to the private health system, limiting the generalizability of our results to other populations or healthcare settings, especially the public health setting.\u003c/p\u003e \u003cp\u003eHowever, our study has several strengths that confer robustness and clinical relevance to our findings. Firstly, we analyzed a large cohort of patients treated during a period of uniform perioperative standard-of-care, supporting the generalizability of our findings. Secondly, our detailed examination of clinicopathological characteristics and treatment strategies enables an in-depth analysis of factors affecting patient outcomes. Furthermore, our data underwent a rigorous analysis and review, incorporating specialized data curation to maximize data accuracy.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eOur study represents a comprehensive examination of real-world clinical outcomes for Brazilian patients with early-stage HR+/HER2- breast cancer, focusing on their clinicopathological profiles, treatment modalities, and survival rates. It draws attention to the underutilization of certain therapies among specific risk groups and underscores discrepancies in outcomes when juxtaposing real-world data with controlled clinical trials. It also sheds light on the risk of recurrence within the high-risk patient group as defined by this analysis, advocating for developing novel strategies to mitigate it. In addition, we provide critical insights into the management and prognosis of HR+/HER2- EBC, offering meaningful contributions to clinical practice, medical education strategies, implementation of guidelines, as well as for planning research and health management initiatives.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003e\u003cu\u003eACKNOWLEDGEMENTS\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eInstituto Oncocl\u0026iacute;nicas for administrative and ethical support.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eFUNDING\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project was funded by Novartis.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eCONFLICTS OF INTEREST\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAG declares advisory role for Roche, Novartis, Pfizer, Lilly, Daiichi-Sankyo received a speaker\u0026rsquo;s fee from Roche, Novartis, Pfizer, Lilly, Daiichi Sankyo, AstraZeneca, Gilead.\u003c/p\u003e\n\u003cp\u003eRD declares advisory role for Roche, Foundation Medicine, AstraZeneca received a speaker\u0026rsquo;s fee from Roche, Ipsen, Amgen, Servier, Sanofi, Libbs, Merck Sharp \u0026amp; Dohme, Lilly, AstraZeneca, Janssen, Takeda, Bristol Myers Squibb, GlaxoSmithKline, Gilead, research grants from Merck, Novartis, Daiichi-Sankyo, GlaxoSmithKline and AstraZeneca, and is investor in Trialing Health, S.L.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eAUTHORS CONTRIBUTION\u0026nbsp;\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eConception and design: \u0026nbsp;Aline Coelho Goncalves, Tomas Reinert, Max S. Mano, Rodrigo Dienstmann\u003c/p\u003e\n\u003cp\u003eDevelopment of methodology: Rodrigo Dienstmann\u003c/p\u003e\n\u003cp\u003eAcquisition of data: Rafael Duarte Paes, Heloisa Mussato Fernandes da Cruz, Rodrigo Dienstmann\u003c/p\u003e\n\u003cp\u003eAnalysis and interpretation of data (e.g., statistical analysis, biostatistics, computational analysis): Matheus Costa e Silva, Rodrigo Dienstmann\u003cbr\u003e\u0026nbsp;\u003cbr\u003e\u0026nbsp;Administrative, technical, or material support (i.e., reporting or organizing data, constructing databases): Fernanda Christtanini Koyama, Heloisa Mussato Fernandes da Cruz, Matheus Costa e Silva, Rodrigo Dienstmann\u003c/p\u003e\n\u003cp\u003eWriting, review, and/or revision of the manuscript: Aline Coelho Goncalves, Tomas Reinert, Max S. Mano, Cristiano Augusto Andrade de Resende, Gustavo Bretas, Leandro Jonata de Carvalho Oliveira, Maria Cristina Figueroa, Carlos Barrios, Rodrigo Dienstmann\u003c/p\u003e\n\u003cp\u003eStudy supervision: Aline Coelho Goncalves, Rodrigo Dienstmann\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eDATA AVAILABILITY\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDeidentified patient data from this study can be made available to qualified investigators who provide a methodologically sound research proposal and sign a data access agreement. Please email corresponding author for information. The study protocol and REDCap dictionary will also be made available upon request.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cu\u003eETHICS APPROVAL\u003c/u\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study was conducted in accordance with local legislation and institution requirements. It was approved by the Ethics Committee protocol 59129322.9.0000.0227 on August 23,\u0026nbsp;2022.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H et al Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin 74(3):229\u0026ndash;263\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAllemani C, Matsuda T, Di Carlo V et al (2018) Global surveillance of trends in cancer survival 2000-14 (CONCORD-3): analysis of individual records for 37 513 025 patients diagnosed with one of 18 cancers from 322 population-based registries in 71 countries. Lancet 391(10125):1023\u0026ndash;7105\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFranzoi MA, Rosa DD, Zaffaroni F et al (2019) Advanced Stage at Diagnosis and Worse Clinicopathologic Features in Young Women with Breast Cancer in Brazil: A Subanalysis of the AMAZONA III Study (GBECAM 0115). J Glob Oncol 5:1\u0026ndash;10\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEstimativa de Incid\u0026ecirc;ncia de C\u0026acirc;ncer no Brasil 2023\u0026ndash;2025 | Revista Brasileira de Cancerologia [Internet]. [cited 2024 Apr 12]. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://rbc.inca.gov.br/index.php/revista/article/view/3700\u003c/span\u003e\u003cspan address=\"https://rbc.inca.gov.br/index.php/revista/article/view/3700\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAdes F, Zardavas D, Bozovic-Spasojevic I et al (2014) Luminal B breast cancer: molecular characterization, clinical management, and future perspectives. J Clin Oncol 32(25):2794\u0026ndash;2803\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurstein HJ, Curigliano G, Th\u0026uuml;rlimann B et al (2021) Customizing local and systemic therapies for women with early breast cancer: the St. Gallen International Consensus Guidelines for treatment of early breast cancer 2021. Ann Oncol 32(10):1216\u0026ndash;1235\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBurstein HJ, Escalation (2023) De-escalation, Adaptation, Speciation, Customization: The New Approaches to Breast Cancer. Hematol Oncol Clin North Am 37(1):xiii\u0026ndash;xvi\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSherman RE, Anderson SA, Dal Pan GJ, Gray GW, Gross T, Hunter NL et al (2016) Real-World Evidence - What Is It and What Can It Tell Us? N Engl J Med 375(23):2293\u0026ndash;2297\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eRaphael MJ, Gyawali B, Booth CM (2020) Real-world evidence and regulatory drug approval. Nat Rev Clin Oncol 17(5):271\u0026ndash;272\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSlamon Dennis L, Oleg N, Zbigniew et al (2024) Ribociclib plus Endocrine Therapy in Early Breast Cancer. N Engl J Med 390(12):1080\u0026ndash;1091\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTolaney SM, Garrett-Mayer E, White J et al (2021) Updated Standardized Definitions for Efficacy End Points (STEEP) in Adjuvant Breast Cancer Clinical Trials: STEEP Version 2.0. J Clin Oncol 39(24):2720\u0026ndash;2731\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCottu P, Ramsey SD, Sol\u0026agrave;-Morales O, Spears PA, Taylor L (2022) The emerging role of real-world data in advanced breast cancer therapy: Recommendations for collaborative decision-making. Breast 61:118\u0026ndash;122\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eM\u0026uuml;ller C, Kiver V, Solomayer EF et al (2023) CDK4/6 Inhibitors in Advanced HR+/HER2 - Breast Cancer: A Multicenter Real-World Data Analysis. Breast Care (Basel) 18(1):31\u0026ndash;41\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eJohnston SRD, Harbeck N, Hegg R, Toi M, Martin M, Shao ZM et al (2020) Abemaciclib Combined With Endocrine Therapy for the Adjuvant Treatment of HR+, HER2-, Node-Positive, High-Risk, Early Breast Cancer (monarchE). J Clin Oncol 38(34):3987\u0026ndash;3998\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAna Heredia CS (2024) Suboptimal use of ovarian function suppression in very young women with early breast cancer: a real-world data study. Breast Cancer Res Treat 203(1):173\u0026ndash;179\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKalinsky K, Barlow WE, Gralow JR et al (2021) 21-Gene Assay to Inform Chemotherapy Benefit in Node-Positive Breast Cancer. N Engl J Med 385(25):2336\u0026ndash;2347\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEloranta S, Smedby KE, Dickman PW, Andersson TM (2021) Cancer survival statistics for patients and healthcare professionals - a tutorial of real-world data analysis. J Intern Med 289(1):12\u0026ndash;28\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eTaylor-Stokes G, Mitra D, Waller J, Gibson K, Milligan G, Iyer S (2019) Treatment patterns and clinical outcomes among patients receiving palbociclib in combination with an aromatase inhibitor or fulvestrant for HR+/HER2-negative advanced/metastatic breast cancer in real-world settings in the US: Results from the IRIS study. Breast 43:22\u0026ndash;27\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":"Early breast cancer, Hormone receptor positive breast cancer, real-world data","lastPublishedDoi":"10.21203/rs.3.rs-4952483/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4952483/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003ePurpose\u003c/h2\u003e \u003cp\u003eThis study aims to assess the disease characteristics, practice patterns and real-world outcomes of patients (pts) with HR positive (+)/HER2 negative (-) early breast cancer (EBC) treated in Brazil's largest network of community oncology practices.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eRetrospective study from the Oncocl\u0026iacute;nicas\u0026amp;CO real-world database from 2016 to 2021. We assessed risk profile distribution (high-risk [HR], intermediate-risk [IR] or low-risk [LR]) as per recent adjuvant trials in EBC, endocrine and chemotherapy (CT) prescriptions and 3-year invasive disease-free survival (iDFS).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn total, 1,786 cases were selected for the study. Median age was 57 years, 566 (32%) were premenopausal, 1,179 (66%) were LR, 351 (20%) IR, and 256 (14%) HR. In post-menopausal pts, aromatase inhibitor (AI) was used by 74% with LR, 79% with IR and 83% with HR. In premenopausal pts, ovarian function suppression (OFS) \u0026ndash; combined with tamoxifen or AI \u0026ndash; was prescribed to 18% LR pts, 15% IR, and 48% HR. CT was offered to 32%, 38%, and 73% of postmenopausal pts in LR, IR, and HR groups. In premenopausal pts, 55%, 57%, and 78% received CT in LR, IR, and HR groups. The 3-year iDFS was 86% (95% CI 84%-89%) in LR population, 87% (82%-91%) in IR, and 72% (95% CI 65%-81%) in HR.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eIn this large real-world cohort of patients treated in a private setting in Brazil, most pts are diagnosed with low-risk EBC. We found that a significant proportion of premenopausal pts with high-risk EBC were not treated with OFS and did not receive CT.\u003c/p\u003e","manuscriptTitle":"Real-World Treatment Patterns and Outcomes in Hormone Receptor Positive HER2 Negative Early-Stage Breast Cancer in a Private Community Oncology Practice of Brazil","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-10-16 06:07:00","doi":"10.21203/rs.3.rs-4952483/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":"bf6484ac-913d-410b-af5f-201781fcc75f","owner":[],"postedDate":"October 16th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-11-07T15:08:51+00:00","versionOfRecord":[],"versionCreatedAt":"2024-10-16 06:07:00","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4952483","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4952483","identity":"rs-4952483","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}