Survival implications of non-organized breast cancer screening in a Brazilian tertiary women’s health center: A retrospective cohort study of 1517 patients

Survival implications of non-organized breast cancer screening in a Brazilian tertiary women’s health center: A retrospective cohort study of 1517 patients | 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 Survival implications of non-organized breast cancer screening in a Brazilian tertiary women’s health center: A retrospective cohort study of 1517 patients Natalie Rios Almeida, Fabricio Palermo Brenelli, Maria Beatriz de Paula Leite Kraft, and 7 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8701531/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Breast cancer (BC) is the most prevalent malignancy among Brazilian women. Advanced-stage diagnosis remains frequent, largely due to limited access to screening and treatment. Despite national recommendations for organised screening, implementation remains opportunistic. This study compared prognostic outcomes between clinically detected and opportunistically screened breast cancers and estimated Years of Life Lost (YLL) and Years of Disease-Free Life Lost (YDFL) to quantify the impact of clinical stage on survival and disease-free survival expectancy. A retrospective cohort of 1,517 women with unilateral, invasive, non-metastatic BC who underwent surgery at a tertiary public hospital in Brazil between 2012 and 2016 was analysed. Patients were classified as symptomatic (diagnosed based on clinical signs and symptoms) or asymptomatic (diagnosed through screening). Clinicopathological features, treatments, and outcomes were compared using the Chi-square, Fisher’s exact, and Kruskal–Wallis tests. Survival was analysed using Kaplan–Meier estimates and Cox regression models. YLL and YDFL were derived from Weibull survival models, using stage I patients as the reference. Most patients (69.5%) were symptomatic at diagnosis, with palpable tumours in 94.3%. Compared with asymptomatic cases, symptomatic women were younger and presented with more advanced stages, and aggressive tumours. They more frequently underwent mastectomy and neoadjuvant chemotherapy (p < 0.001). Both YLL and YDFL increased progressively with advancing clinical stage, reaching over 15 years in stage III. The predominance of advanced-stage diagnoses reflects the limited effectiveness of non-systematic screening implementation. Advanced disease was associated with substantial loss of lifetime and disease-free years, reinforcing the prognostic value of early-stage detection. breast cancer clinical diagnosis screening imaging diagnosis survival mammography surgery life expectancy Figures Figure 1 Figure 2 Introduction Breast cancer (BC) is the most common malignancy among Brazilian women, with marked regional disparities in incidence, stage at diagnosis, and mortality. Although mortality has declined in some urban centers, late-stage diagnoses remain frequent in less privileged regions due to limited access to early detection and treatment [ 1 , 2 ]. The stage of disease at diagnosis remains the strongest determinant of survival, with five-year rates exceeding 90% for stage I and decreasing substantially with disease progression [ 3 ]. Regular participation in organized mammography screening can reduce breast cancer–specific mortality by up to 40% and substantially increase early-stage detection, with most tumours diagnosed as pT1 in countries with high screening coverage [ 4 , 5 ]. However, these benefits depend on structured, population-based programs with systematic invitations, quality control, and timely diagnostic follow-up [ 6 , 7 ]. In Brazil, despite national guidelines recommending biennial mammography for women aged 50–69 years, implementation remains predominantly opportunistic, resulting in low coverage and diagnostic delays [ 1 ]. Consequently, most women are still diagnosed after presenting signs and symptoms, often with more advanced disease, which reduces their life expectancy and quality of life [ 1 ]. The objective of this study was to compare prognostic outcomes between clinically detected and opportunistically screened breast cancers, and to quantify the loss of both total and disease-free life expectancy using Years of Life Lost (YLL) and Years of Disease-Free Life Lost (YDFL) according to clinical stage, in order to better understand the prognostic implications of late-stage diagnosis. Methods A retrospective analysis was conducted using data from consecutive women with BC who underwent oncological surgery at the Woman's Hospital Prof. Dr. José Aristodemo Pinotti, State University of Campinas (UNICAMP) between January 1, 2012, and December 31, 2016. A thorough review of the medical records was conducted, and the data were collected and managed using Research Electronic Data Capture (REDCap®) and Excel®. Recurrence events were categorized as local or distant, and all verified causes of death were recorded. This article was written according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines. The following patients were excluded from the study: those with stage IV disease, bilateral breast cancer, prior malignancy, pregnant or postpartum women, those who had undergone preoperative radiotherapy, ductal carcinoma in situ (DCIS) in both biopsy and surgical specimens, patients with incomplete data regarding adjuvant therapy, and those without follow-up records (due to continued care at other cancer centers). A total of 1517 female subjects were included in the study (Fig. 1 ), and follow-up data were recorded until March 2023. Women were classified as "symptomatic" if their diagnosis was prompted by signs or symptoms of breast cancer, such as a palpable lump, nipple discharge or retraction, or skin changes. Patients with no previous clinical abnormalities, whose biopsy was prompted by suspicious lesions initially detected by imaging, were classified as "asymptomatic". According to the institutional protocol, breast-conserving surgery (BCS) followed by WBI is considered the gold standard for breast cancer treatment and involves tumour resection with negative margins (no ink on tumour) [ 8 ]. Oncoplastic BCS + WBI is indicated for patients with larger tumours, those with a disproportionate tumour-to-breast ratio, or those who would benefit from a bilateral reduction. Mastectomy is indicated when oncological criteria are not met or conservative treatment is not feasible, preferably with immediate reconstruction. Borderline cases are discussed at a multidisciplinary tumour board. After completing local and systemic treatment, patients are followed twice a year with clinical examination and once a year with breast imaging (mammography with or without ultrasound). The study was approved by the Research Ethics Committee of the institution. Statistical analyses were performed using the SAS System for Windows (Statistical Analysis System), version 9.4, SAS Institute Inc, 2002–2012, Cary, NC, USA. The committee waived the need for informed consent because of the study’s retrospective nature. The clinicopathological characteristics of patients in the two groups were analyzed with the Chi-square test and Fisher’s exact test for categorical variables and the Kruskal–Wallis test followed by a post-hoc test for continuous variables. Overall and disease-specific survival were estimated using the Kaplan–Meier method. Cox regression models were applied for univariate and multivariate analyses, and results were expressed as hazard ratios (HR) with 95% confidence intervals (CI). Statistical significance was set at p < 0.05. Individual patient-level YLL and YDFL were estimated using Weibull parametric survival models for time to recurrence and time to death, including age at diagnosis and clinical stage as covariates. Restricted mean survival times (RMST) were predicted up to 100 years to approximate expected lifetime. In the absence of population life tables, an internal reference approach was adopted, using clinical stage I patients as the baseline. For each patient, YLL and YDFL were calculated as the difference between the mean RMST of stage I patients and the patient’s predicted lifetime or disease-free lifetime. Results were summarized by clinical stage using mean and standard deviations. Results A total of 1517 consecutive patients with breast cancer operated between 2012 and 2016 were included with a mean follow-up period of 5.94 years. Table 1 presents the clinicopathological characteristics of the entire cohort and the comparison between the two groups. Table 1. Patients and tumour characteristics by groups (n=1517) All patients (n=1517) Symptomatic (n=1054) Asymptomatic (n=463) p value Age at diagnosis (yr) Median 74 54 (22-91) 169 (11.1%) 371 (24.2%) 879 (57.9%) 98 (6.5%) 53 (22-91) 155 (14.7%) 274 (26%) 558 (53%) 67 (6.3%) 57 (29-86) 14 (3%) 97 (20.9%) 321 (69.3%) 31 (6.7%) <0.001 <0.001 <0.001 1 0.340 BMI (median) (kg/m²) 28.2 (14.2-61.2) 27.41 (14.2-61.2) 28.5 (18.6-50.3) 0.002 Menopausal status Premenopausal Postmenopausal 585 (38.6%) 932 (61.4%) 448 (42.5%) 606 (57.5%) 137 (29.6%) 326 (70.4%) 1 <0.001 Comorbidities No Yes 586 (38.6%) 931 (61.4%) 438 (41.6%) 616 (58.4%) 148 (32%) 315 (68%) 1 <0.001 Clinical stage 0* I IIa-IIb IIIa-IIIc 3 (2.4%) 561 (37%) 666 (43.9%) 255 (16.8%) 10 (0.9%) 264 (25%) 541 (51.3%) 239 (22.7%) 25 (5.3%) 297 (64.1%) 125 (27%) 16 (3.4%) 0.037 1 <0.001 <0.001 Median tumour size (cm) 2.3 (0-16) 2.7 (0-16) 1.5 (0-8) <0.001 Histology (biopsy) DCIS* Ductal Invasive Lobular Invasive Others 36 (2.4%) 1317 (86.8%) 72 (4.7%) 92 (6.1%) 11 (1%) 931 (88.3%) 44 (4.2%) 68 (6.4%) 25 (5.4%) 386 (83.4%) 28 (6%) 24 (5.2%) <0.001 1 0.086 0.511 Subtype (biopsy) Luminal A/B Luminal B HER2+ Non-luminal HER2+ Triple negative Unknown 887 (58.5%) 112 (7.4%) 71 (4.7%) 220 (14.5%) 227 (15%) 575 (54.6%) 87 (8.2%) 60 (5.7%) 185 (17.5%) 147 (13.9%) 312 (67.4%) 25 (5.4%) 11 (2.4%) 35 (7.6%) 80 (17.3%) 1 0.008 0.001 <0.001 0.985 Type of surgery Conservative Mastectomy 807 (53.2%) 710 (46.8%) 476 (45.2%) 578 (54.8%) 331 (71.5%) 132 (28.5%) 1 <0.001 Pathological T stage Median size (cm) pT0 pT1 pT2 pT3/T4 pCR 2.0 (0-17) 18 (1.2%) 647 (42.6%) 584 (38.5%) 175 (11.5%) 92 (6.1%) 2.5 (0-17) 13 (1.2%) 345 (32.7%) 456 (43.3%) 162 (15.4%) 78 (7.4%) 1.6 (0-8.3) 5 (1.1%) 302 (65.2%) 128 (27.7%) 13 (2.8%) 14 (3%) <0.001 0.122 1 <0.001 <0.001 <0.001 Pathological N stage pN0 pN1/1mi pN2/3 pNx ypN0 790 (52.1%) 454 (29.9%) 249 (16.4%) 5 (0.3%) 19 (1.3%) 500 (47.5%) 335 (31.8%) 201 (19.1%) 2 (0.2%) 16 (1.5%) 290 (62.6%) 119 (25.7%) 48 (10.4%) 3 (0.6%) 3 (0.6%) 1 <0.001 <0.001 0.300 0.075 Multifocal tumour No Yes 1227 (80.9%) 209 (13.8%) 840 (79.7%) 146 (13.8%) 387 (83.6%) 62 (13.4%) 1 0.589 Tumour grade I/II III pCR Unknown 892 (58.8%) 521 (34.3%) 92 (6.1%) 12 (0.8%) 568 (53.9%) 401 (38%) 78 (7.4%) 8 (0.7%) 324 (70%) 121 (26.1%) 14 (3%) 4 (0.9%) 1 <0.001 <0.001 0.831 Perivascular Invasion No Yes pCR/Unknown 864 (57%) 536 (35.3%) 117 (7.7%) 555 (52.7%) 404 (38.3%) 95 (9%) 309 (66.7%) 132 (28.5%) 22 (4.7%) 1 <0.001 <0.001 Removed breast tissue (g) 189 (5-2950) 350 (5-2950) 80 (8-1832) <0.001 Surgical Margins Negative Positive (invasive) 1423 (91.6%) 94 (6.2%) 995 (94.4%) 59 (5.6%) 428 (92.4%) 35 (7.6%) 1 0.146 Systemic therapy Neoadjuvant Adjuvant Endocrine therapy 533 (35.1%) 806 (53.1%) 1208 (79.6%) 477 (45.2%) 562 (53.3%) 766 (72.7%) 56 (12.1%) 244 (52.7%) 391 (84.5%) <0.001 0.823 <0.001 Radiotherapy No Yes 248 (16.3%) 1264 (83.3%) 173 (16.4%) 879 (83.4%) 75 (16.2%) 385 (83.1%) 1 0.946 Local recurrence 64 (4.2%) 49 (4.6%) 19 (4.1%) 0.211 Distant recurrence 221 (14.6%) 186 (17.6%) 35 (7.5%) <0.001 OR (Odds Ratio); BMI (Body Mass Index); DCIS (Ductal Carcinoma In Situ); pCR (pathological complete response); *In situ (biopsy) with invasive tumour in the specimen Most patients (1,054; 69.5%) were diagnosed after presenting clinical signs. Among them, palpable tumours were the most common, occurring in 994 patients (94.3%). Other clinical signs and symptoms included nipple discharge or retraction in 39 patients (3.7%), skin changes in 19 patients (1.8%) and pain in 2 patients (0.2%). In contrast, 463 tumours (30.5%) were detected through screening, without any reported clinical abnormalities. Mammography was the primary diagnostic method, used in 409 cases (88.3%), followed by ultrasound in 54 cases (11.7%). A comprehensive analysis of the clinical characteristics revealed significant disparities between the groups. Symptomatic patients exhibited a significantly higher prevalence of adverse tumour characteristics when compared to those diagnosed by screening: a greater number of advanced tumours (p < 0.001), more aggressive subtypes (p < 0.001), also grade III tumours (p < 0.001) and the presence of perivascular invasion were more prevalent (p < 0.001). Focality was the only variable without significant difference between the groups (p = 0.589) (Table 1). Mastectomy and neoadjuvant chemotherapy were more frequently performed in the group diagnosed by clinical signs and symptoms (p < 0.001), compared with the asymptomatic group. Instead of similarity between local recurrence rates (p = 0.21), the symptomatic group had a higher number of distant recurrence events (p < 0.001). As shown in Table 2 and Figure 2, both YLL and YDFL increased progressively with advancing clinical stage, ranging from nearly zero in stage I to more than 15 years in stage III. Table 2. Summary of Years of Life Lost and Years of Disease-Free Lost by Stage Clinical Stage N Mean YLL (y) SD YLL Mean YDFL (y) SD YDFL I 597 Ref. 1.45 Ref. 0.99 II 665 6.70 3.18 7.50 1.46 III 255 16.21 4.79 15.89 1.70 YLL (Years of Life Lost); YDFL (Years of Disease-Free Lost); SD (Standard Deviation) In the univariate analysis, the detection method was significantly associated with poorer disease-free survival (DFS), breast cancer-specific survival (BCSS), and overall survival (OS). Compared with the asymptomatic group, patients diagnosed based on clinical signs had a 5-year DFS of 77.8% versus 89.5% (HR 1.93; 95% CI, 1.48–2.51; p < 0.001), a 5-year BCSS of 86.1% versus 95.3% (HR 2.70; 95% CI, 1.86–3.92; p < 0.001), and a 5-year OS of 81.1% versus 92.1% (HR 2.13; 95% CI, 1.60–2.85; p < 0.001) (data not shown). However, in the multivariate analysis, the detection method was no longer an independent predictor of survival. Instead, older age, larger tumour size, advanced clinical stages (IIIa–IIIc), pathological axillary involvement, grade III tumours, perivascular invasion, as well as HER2-positive and triple-negative subtypes, emerged as the factors significantly associated with the survival outcomes (Supplementary Tables S1-S3). Discussion In this cohort study, unfavourable tumour characteristics were significantly more prevalent in patients whose biopsy was performed after the appearance of clinical signs and symptoms. Fewer than 40% of the entire cohort were diagnosed at clinical stage I. Survival rates were significantly affected by clinical and pathological stages, age, subtype, and perivascular invasion. It is well documented that countries with organized screening programmes have achieved reductions up to a 40% in fatal-breast cancer rates and an earlier stage of cancer diagnosis among screened women [ 4 , 9 ]. In contrast, the high proportion of symptomatic diagnoses in our study reflects the limited effectiveness of screening as currently implemented in Brazil, where most women undergo mammography on their own or opportunistically during routine consultations. In 2023, screening coverage in the public health system (Sistema Único de Saúde; SUS) remained below 35% nationwide [ 1 ]. Recent Brazilian studies have reinforced the association between opportunistic screening and advanced presentation at diagnosis. At the Instituto do Câncer do Estado de São Paulo (ICESP), tumours detected by mammography were smaller and less likely to present nodal involvement than those clinically detected [ 10 ]. The multicenter AMAZONA III study reported similar findings, showing that 76.9% of public-sector patients were diagnosed after symptoms onset versus 47% in the private sector, and that stage II and III disease predominated among public patients [ 11 ]. Together, these findings confirm that, in Brazil, most breast cancers are still detected symptomatically and at later stages. International evidence highlights the benefits of population-based programmes. The Dutch national screening programme achieves about 70% coverage among women aged 50–75 years. In 2023, 67% of tumours detected were stage pT1, only 1.1% were pT3/pT4, and the fatal-breast cancer rate decreased by around 40% compared with the pre-implementation period [ 5 ]. Moreover, in the Netherlands, treating one advanced breast cancer case costs over €50,000, while each screening mammogram costs around €65, illustrating that even a small reduction in late-stage cases offsets the full cost of screening [ 13 ]. In Brazil, despite national recommendations, the absence of organized invitations, quality assurance, and structured diagnostic pathways contributes to delayed diagnosis and high proportions of advanced disease. This scenario not only limits survival gains but also imposes a substantial and avoidable financial burden on the public health system. Strengthening population coverage, training professionals, and improving referral networks are essential steps toward implementing an affective national programme. In our cohort, both YLL and YDFL increased progressively with advancing clinical stage, exceeding 15 years in stage III. Similar patterns have been reported in population-based studies, showing a marked reduction in expected lifetime with late-stage diagnosis [ 14 – 17 ]. Brazilian studies have also demonstrated that advanced-stage presentation remains a major contributor to premature mortality and YLL due to breast cancer [ 14 , 18 ]. Such findings emphasize how delays in diagnosis translate into substantial loss of potential life-years, reinforcing the need for effective, organized screening programmes and timely access to treatment. Evidence indicates that detection method alone is not an independent prognostic factor when tumour stage and biology are considered [ 19 , 20 ]. The apparent survival benefit of screen-detected tumours arises mainly from earlier diagnosis and less aggressive disease. Classic screening biases, such as lead-time and length-time effects, may further amplify this effect if not adjusted analytically [ 6 , 21 ]. Symptomatic patients were more likely to undergo mastectomy (54.8%) than those whose tumours were detected by screening (45.2%) (p < 0.001). Mactier et al. similarly reported higher rates of breast-conserving surgery and superior overall and cancer-specific survival among screen-detected cases, even after multivariate adjustment [ 21 ]. These observations reinforce that the benefit of screening derives from earlier detection, enabling less extensive surgery and improved outcomes. Evidence from other countries confirms that a structured, equitable screening system can substantially reduce mortality. Long-term follow-up from Norway, Finland, and Sweden demonstrates reductions of 30–40% in breast cancer–specific deaths, corresponding to approximately 20–30 life-years gained per 1000 women screened [ 4 , 5 , 9 ]. Achieving comparable results in Brazil will require not only greater coverage but also improvements in diagnostic access, education, and treatment pathways. In summary, the predominance of advanced-stage disease in our cohort reflects systemic limitations in early detection rather than intrinsic lack of prognostic value in screening. Implementing a truly organized screening programme, integrated with timely diagnostic confirmation and treatment access, is essential to reduce avoidable morbidity, improve survival outcomes, and optimise public resource allocation. This study included a large number of patients representing all invasive non metastatic stages and molecular subtypes of breast cancer, and provides comprehensive real-world data on diagnosis, treatment, and long-term outcomes in a public tertiary centre. The findings should, however, be interpreted considering the study’s limitations, particularly its single-center and retrospective design. Conducting prospective, randomized trials in this context would be unethical. Conclusion In this cohort, breast cancers detected after the onset of symptoms presented more advanced stages and higher mastectomy rates. Despite national guidelines recommendations for screening, the predominance of advanced-stage diagnoses reflects the limited effectiveness of non-systematic screening implementation. Advanced disease was associated with substantial loss of life-years and disease-free years, reinforcing the prognostic benefit of early-stage breast cancer detection. Declarations Declaration of Interest Statement Funding: None Conflicts of interest: None declared Ethical approval: We confirm that the study complies with ethical standards, including approval by the Research Ethics Committee of UNICAMP (CAAE 84450518.9.0000.5404) Consent to Participate declarations: The clinical data of the patients included in the study were obtained from the medical records only by the research team and recorded in an electronic file. No samples of biological material were obtained from the patients, no interviews were conducted, and the study did not interfere with the follow-up of the patients included in the study. The application of the Consent to Participate declaration was waived by the Research Ethics Committee of UNICAMP. Author contribution: N.A. wrote the original draft, designed the study;F. B. wrote the original draft, designed the study, contributed to the interpretation of results; M.B.K. performed the data collection and analysis; N.S. performed the data collection and analysis; C.C. wrote the original draft, contributed to the interpretation of results; R.T. wrote the original draft, contributed to the interpretation of results; C.C-F. contributed to the interpretation of results; G.D. contributed to the interpretation of results; J.S. contributed to the interpretation of results; L.C.Z. designed the study, contributed to the interpretation of results, reviewed and wrote the original draft. All authors contributed to the final manuscript and approved it. References Ministério da Saúde. Instituto Nacional de Câncer José Alencar Gomes da Silva (INCA). Estimativa 2020: incidência de câncer no Brasil. Rio de Janeiro: INCA; 2019. https://www.inca.gov.br/publicacoes/livros/estimativa-2020-incidencia-de-cancer-no-brasil . Disponível em. Ferreira MC, Vale DB, Barros MBA. 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Br J Cancer. 2009;101(8):1338–44. 10.1038/sj.bjc.6605298 . Schumann L, Hadwiger M, Eisemann N, Katalinic A. Lead-time corrected effect on breast cancer survival in Germany by mode of detection. Cancers (Basel). 2024;16(7):1326. 10.3390/cancers16071326 . Mactier M, Mansell J, Arthur L, et al. Survival after standard or oncoplastic breast-conserving surgery versus mastectomy for breast cancer. BJS Open. 2025;9(2):zraf002. 10.1093/bjsopen/zraf002 . 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-8701531","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":589826849,"identity":"f18a0d0b-ae9a-4bdc-8956-f71d321072da","order_by":0,"name":"Natalie Rios Almeida","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA7klEQVRIiWNgGAWjYFACxgYgYcHAwMxgwPAByGRjJ06LBFgL4wyQFmbirJIAEQbMPCCKkBZz6cOND3/USETzszNv/Gzza5s8HzMD44ePObi1WPYlNhvzHJPIndnMViyd23fbsI2ZgVly5jbcWgzOMLZJM7BJ5G44zGMgndtzmxGohY2Zl4AWyR//JHL3H+Yx/m3Zc9ueKC0SvG1AW5h5zKQZftxOJEZLszFvn0TujMNsZZa9DbeT25gZmwn4hf3hwx/fbHL7+w9vvvHjz23b+e3NBz98xKMFFTC2gckGYtWDwB9SFI+CUTAKRsFIAQB+70wDuwjbhQAAAABJRU5ErkJggg==","orcid":"","institution":"State University of Campinas","correspondingAuthor":true,"prefix":"","firstName":"Natalie","middleName":"Rios","lastName":"Almeida","suffix":""},{"id":589826850,"identity":"a480274b-5b9a-40c3-82af-3449c0353d86","order_by":1,"name":"Fabricio Palermo Brenelli","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Fabricio","middleName":"Palermo","lastName":"Brenelli","suffix":""},{"id":589826851,"identity":"5d36e0fa-cb79-4328-8660-a4f387a76d30","order_by":2,"name":"Maria Beatriz de Paula Leite Kraft","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Maria","middleName":"Beatriz de Paula Leite","lastName":"Kraft","suffix":""},{"id":589826852,"identity":"3abdd192-fc41-4691-89de-1afa0300ac1a","order_by":3,"name":"Nicoli Serquiz de Azevedo","email":"","orcid":"","institution":"Federal University of Rio Grande do Norte","correspondingAuthor":false,"prefix":"","firstName":"Nicoli","middleName":"Serquiz","lastName":"de Azevedo","suffix":""},{"id":589826853,"identity":"c9e73079-6c49-4d08-82d5-10657f1da7bf","order_by":4,"name":"Cesar Cabello","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Cesar","middleName":"","lastName":"Cabello","suffix":""},{"id":589826854,"identity":"2e2ab50b-9077-4002-9f98-555621401cf7","order_by":5,"name":"Renato Zocchio Torresan","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Renato","middleName":"Zocchio","lastName":"Torresan","suffix":""},{"id":589826855,"identity":"0060fa3a-a779-4a37-856d-ba62abc47b49","order_by":6,"name":"Cassio Cardoso-Filho","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Cassio","middleName":"","lastName":"Cardoso-Filho","suffix":""},{"id":589826856,"identity":"d7b09886-2be2-4ce2-b220-13ed21f68e36","order_by":7,"name":"Giuliano Mendes Duarte","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Giuliano","middleName":"Mendes","lastName":"Duarte","suffix":""},{"id":589826857,"identity":"ab742d1a-80a1-4aee-84b9-b8e461ab67d4","order_by":8,"name":"Julia Yoriko Shinzato","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Julia","middleName":"Yoriko","lastName":"Shinzato","suffix":""},{"id":589826858,"identity":"1a53481e-93d9-41e0-9edd-ed222852d18c","order_by":9,"name":"Luiz Carlos Zeferino","email":"","orcid":"","institution":"State University of Campinas","correspondingAuthor":false,"prefix":"","firstName":"Luiz","middleName":"Carlos","lastName":"Zeferino","suffix":""}],"badges":[],"createdAt":"2026-01-26 14:53:59","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8701531/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8701531/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":102517459,"identity":"35a54494-d632-4d1b-84a1-9c980d265cee","added_by":"auto","created_at":"2026-02-12 13:57:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":54216,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of patient selection (n=1517)\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8701531/v1/e2e18ae15d15519fa077d541.png"},{"id":102517456,"identity":"3d1cc1bb-a695-4327-b700-68a45bf263a6","added_by":"auto","created_at":"2026-02-12 13:57:20","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":81817,"visible":true,"origin":"","legend":"\u003cp\u003eYLL and Disease-Free YLL by Stage with Individual Patient Values\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-8701531/v1/58afa8510802256dd9865272.png"},{"id":102517609,"identity":"06dddb52-cca4-4df9-ad26-bf5b486b6133","added_by":"auto","created_at":"2026-02-12 13:57:50","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":700496,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8701531/v1/e0d8ea92-9a63-4115-81d3-e9bbff89ebaa.pdf"},{"id":102517434,"identity":"83a960f3-b5a0-4c56-9a8b-015fe6a0650e","added_by":"auto","created_at":"2026-02-12 13:57:05","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":30821,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesS1S2S3.docx","url":"https://assets-eu.researchsquare.com/files/rs-8701531/v1/7578d1e7d8a6b455de16d67f.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Survival implications of non-organized breast cancer screening in a Brazilian tertiary women’s health center: A retrospective cohort study of 1517 patients","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) is the most common malignancy among Brazilian women, with marked regional disparities in incidence, stage at diagnosis, and mortality. Although mortality has declined in some urban centers, late-stage diagnoses remain frequent in less privileged regions due to limited access to early detection and treatment [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe stage of disease at diagnosis remains the strongest determinant of survival, with five-year rates exceeding 90% for stage I and decreasing substantially with disease progression [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Regular participation in organized mammography screening can reduce breast cancer\u0026ndash;specific mortality by up to 40% and substantially increase early-stage detection, with most tumours diagnosed as pT1 in countries with high screening coverage [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, these benefits depend on structured, population-based programs with systematic invitations, quality control, and timely diagnostic follow-up [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Brazil, despite national guidelines recommending biennial mammography for women aged 50\u0026ndash;69 years, implementation remains predominantly opportunistic, resulting in low coverage and diagnostic delays [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. Consequently, most women are still diagnosed after presenting signs and symptoms, often with more advanced disease, which reduces their life expectancy and quality of life [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe objective of this study was to compare prognostic outcomes between clinically detected and opportunistically screened breast cancers, and to quantify the loss of both total and disease-free life expectancy using Years of Life Lost (YLL) and Years of Disease-Free Life Lost (YDFL) according to clinical stage, in order to better understand the prognostic implications of late-stage diagnosis.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003eA retrospective analysis was conducted using data from consecutive women with BC who underwent oncological surgery at the Woman's Hospital Prof. Dr. Jos\u0026eacute; Aristodemo Pinotti, State University of Campinas (UNICAMP) between January 1, 2012, and December 31, 2016. A thorough review of the medical records was conducted, and the data were collected and managed using Research Electronic Data Capture (REDCap\u0026reg;) and Excel\u0026reg;. Recurrence events were categorized as local or distant, and all verified causes of death were recorded. This article was written according to the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) guidelines.\u003c/p\u003e \u003cp\u003eThe following patients were excluded from the study: those with stage IV disease, bilateral breast cancer, prior malignancy, pregnant or postpartum women, those who had undergone preoperative radiotherapy, ductal carcinoma in situ (DCIS) in both biopsy and surgical specimens, patients with incomplete data regarding adjuvant therapy, and those without follow-up records (due to continued care at other cancer centers). A total of 1517 female subjects were included in the study (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e), and follow-up data were recorded until March 2023.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eWomen were classified as \"symptomatic\" if their diagnosis was prompted by signs or symptoms of breast cancer, such as a palpable lump, nipple discharge or retraction, or skin changes. Patients with no previous clinical abnormalities, whose biopsy was prompted by suspicious lesions initially detected by imaging, were classified as \"asymptomatic\".\u003c/p\u003e \u003cp\u003eAccording to the institutional protocol, breast-conserving surgery (BCS) followed by WBI is considered the gold standard for breast cancer treatment and involves tumour resection with negative margins (no ink on tumour) [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Oncoplastic BCS\u0026thinsp;+\u0026thinsp;WBI is indicated for patients with larger tumours, those with a disproportionate tumour-to-breast ratio, or those who would benefit from a bilateral reduction. Mastectomy is indicated when oncological criteria are not met or conservative treatment is not feasible, preferably with immediate reconstruction. Borderline cases are discussed at a multidisciplinary tumour board. After completing local and systemic treatment, patients are followed twice a year with clinical examination and once a year with breast imaging (mammography with or without ultrasound).\u003c/p\u003e \u003cp\u003e The study was approved by the Research Ethics Committee of the institution. Statistical analyses were performed using the SAS System for Windows (Statistical Analysis System), version 9.4, SAS Institute Inc, 2002\u0026ndash;2012, Cary, NC, USA. The committee waived the need for informed consent because of the study\u0026rsquo;s retrospective nature.\u003c/p\u003e \u003cp\u003eThe clinicopathological characteristics of patients in the two groups were analyzed with the Chi-square test and Fisher\u0026rsquo;s exact test for categorical variables and the Kruskal\u0026ndash;Wallis test followed by a post-hoc test for continuous variables. Overall and disease-specific survival were estimated using the Kaplan\u0026ndash;Meier method. Cox regression models were applied for univariate and multivariate analyses, and results were expressed as hazard ratios (HR) with 95% confidence intervals (CI). Statistical significance was set at p\u0026thinsp;\u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003cp\u003eIndividual patient-level YLL and YDFL were estimated using Weibull parametric survival models for time to recurrence and time to death, including age at diagnosis and clinical stage as covariates. Restricted mean survival times (RMST) were predicted up to 100 years to approximate expected lifetime. In the absence of population life tables, an internal reference approach was adopted, using clinical stage I patients as the baseline. For each patient, YLL and YDFL were calculated as the difference between the mean RMST of stage I patients and the patient\u0026rsquo;s predicted lifetime or disease-free lifetime. Results were summarized by clinical stage using mean and standard deviations.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eA total of 1517 consecutive patients with breast cancer operated between 2012 and 2016 were included with a mean follow-up period of 5.94 years. Table 1 presents the clinicopathological characteristics of the entire cohort and the comparison between the two groups.\u003c/p\u003e\n\u003cp\u003eTable 1. Patients and tumour characteristics by groups (n=1517)\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAll patients \u0026nbsp;(n=1517)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSymptomatic (n=1054)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAsymptomatic (n=463)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u003cstrong\u003e\u003cem\u003ep\u003c/em\u003e\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eAge at diagnosis (yr)\u003c/p\u003e\n \u003cp\u003eMedian\u003c/p\u003e\n \u003cp\u003e\u0026lt; 40\u003c/p\u003e\n \u003cp\u003e40-49\u003c/p\u003e\n \u003cp\u003e50-74\u003c/p\u003e\n \u003cp\u003e\u0026gt;74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e54 (22-91)\u003c/p\u003e\n \u003cp\u003e169 (11.1%)\u003c/p\u003e\n \u003cp\u003e371 (24.2%)\u003c/p\u003e\n \u003cp\u003e879 (57.9%)\u003c/p\u003e\n \u003cp\u003e98 (6.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e53 (22-91)\u003c/p\u003e\n \u003cp\u003e155 (14.7%)\u003c/p\u003e\n \u003cp\u003e274 (26%)\u003c/p\u003e\n \u003cp\u003e558 (53%)\u003c/p\u003e\n \u003cp\u003e67 (6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e57 (29-86)\u003c/p\u003e\n \u003cp\u003e14 (3%)\u003c/p\u003e\n \u003cp\u003e97 (20.9%)\u003c/p\u003e\n \u003cp\u003e321 (69.3%)\u003c/p\u003e\n \u003cp\u003e31 (6.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0.340\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eBMI (median) (kg/m\u0026sup2;)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e28.2 (14.2-61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e27.41 (14.2-61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e28.5 (18.6-50.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMenopausal status\u003c/p\u003e\n \u003cp\u003ePremenopausal\u003c/p\u003e\n \u003cp\u003ePostmenopausal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e585 (38.6%)\u003c/p\u003e\n \u003cp\u003e932 (61.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e448 (42.5%)\u003c/p\u003e\n \u003cp\u003e606 (57.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e137 (29.6%)\u003c/p\u003e\n \u003cp\u003e326 (70.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eComorbidities\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e586 (38.6%)\u003c/p\u003e\n \u003cp\u003e931 (61.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e438 (41.6%)\u003c/p\u003e\n \u003cp\u003e616 (58.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e148 (32%)\u003c/p\u003e\n \u003cp\u003e315 (68%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eClinical stage\u003c/p\u003e\n \u003cp\u003e0*\u003c/p\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003cp\u003eIIa-IIb\u003c/p\u003e\n \u003cp\u003eIIIa-IIIc\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e3 (2.4%)\u003c/p\u003e\n \u003cp\u003e561 (37%)\u003c/p\u003e\n \u003cp\u003e666 (43.9%)\u003c/p\u003e\n \u003cp\u003e255 (16.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e10 (0.9%)\u003c/p\u003e\n \u003cp\u003e264 (25%)\u003c/p\u003e\n \u003cp\u003e541 (51.3%)\u003c/p\u003e\n \u003cp\u003e239 (22.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (5.3%)\u003c/p\u003e\n \u003cp\u003e297 (64.1%)\u003c/p\u003e\n \u003cp\u003e125 (27%)\u003c/p\u003e\n \u003cp\u003e16 (3.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.037\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMedian tumour size (cm)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.3 (0-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e2.7 (0-16)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e1.5 (0-8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eHistology (biopsy)\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eDCIS*\u003c/p\u003e\n \u003cp\u003eDuctal Invasive\u003c/p\u003e\n \u003cp\u003eLobular Invasive\u003c/p\u003e\n \u003cp\u003eOthers\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e36 (2.4%)\u003c/p\u003e\n \u003cp\u003e1317 (86.8%)\u003c/p\u003e\n \u003cp\u003e72 (4.7%)\u003c/p\u003e\n \u003cp\u003e92 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e11 (1%)\u003c/p\u003e\n \u003cp\u003e931 (88.3%)\u003c/p\u003e\n \u003cp\u003e44 (4.2%)\u003c/p\u003e\n \u003cp\u003e68 (6.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e25 (5.4%)\u003c/p\u003e\n \u003cp\u003e386 (83.4%)\u003c/p\u003e\n \u003cp\u003e28 (6%)\u003c/p\u003e\n \u003cp\u003e24 (5.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0.086\u003c/p\u003e\n \u003cp\u003e0.511\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSubtype (biopsy)\u003c/p\u003e\n \u003cp\u003eLuminal A/B\u003c/p\u003e\n \u003cp\u003eLuminal B HER2+\u003c/p\u003e\n \u003cp\u003eNon-luminal HER2+\u003c/p\u003e\n \u003cp\u003eTriple negative\u003c/p\u003e\n \u003cp\u003eUnknown\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e887 (58.5%)\u003c/p\u003e\n \u003cp\u003e112 (7.4%)\u003c/p\u003e\n \u003cp\u003e71 (4.7%)\u003c/p\u003e\n \u003cp\u003e220 (14.5%)\u003c/p\u003e\n \u003cp\u003e227 (15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e575 (54.6%)\u003c/p\u003e\n \u003cp\u003e87 (8.2%)\u003c/p\u003e\n \u003cp\u003e60 (5.7%)\u003c/p\u003e\n \u003cp\u003e185 (17.5%)\u003c/p\u003e\n \u003cp\u003e147 (13.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e312 (67.4%)\u003c/p\u003e\n \u003cp\u003e25 (5.4%)\u003c/p\u003e\n \u003cp\u003e11 (2.4%)\u003c/p\u003e\n \u003cp\u003e35 (7.6%)\u003c/p\u003e\n \u003cp\u003e80 (17.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.985\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eType of surgery\u003c/p\u003e\n \u003cp\u003eConservative\u003c/p\u003e\n \u003cp\u003eMastectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e807 (53.2%)\u003c/p\u003e\n \u003cp\u003e710 (46.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e476 (45.2%)\u003c/p\u003e\n \u003cp\u003e578 (54.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e331 (71.5%)\u003c/p\u003e\n \u003cp\u003e132 (28.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePathological T stage\u003c/p\u003e\n \u003cp\u003eMedian size (cm)\u003c/p\u003e\n \u003cp\u003epT0\u003c/p\u003e\n \u003cp\u003epT1\u003c/p\u003e\n \u003cp\u003epT2\u003c/p\u003e\n \u003cp\u003epT3/T4\u003c/p\u003e\n \u003cp\u003epCR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.0 (0-17)\u003c/p\u003e\n \u003cp\u003e18 (1.2%)\u003c/p\u003e\n \u003cp\u003e647 (42.6%)\u003c/p\u003e\n \u003cp\u003e584 (38.5%)\u003c/p\u003e\n \u003cp\u003e175 (11.5%)\u003c/p\u003e\n \u003cp\u003e92 (6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e2.5 (0-17)\u003c/p\u003e\n \u003cp\u003e13 (1.2%)\u003c/p\u003e\n \u003cp\u003e345 (32.7%)\u003c/p\u003e\n \u003cp\u003e456 (43.3%)\u003c/p\u003e\n \u003cp\u003e162 (15.4%)\u003c/p\u003e\n \u003cp\u003e78 (7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1.6 (0-8.3)\u003c/p\u003e\n \u003cp\u003e5 (1.1%)\u003c/p\u003e\n \u003cp\u003e302 (65.2%)\u003c/p\u003e\n \u003cp\u003e128 (27.7%)\u003c/p\u003e\n \u003cp\u003e13 (2.8%)\u003c/p\u003e\n \u003cp\u003e14 (3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.122\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePathological N stage\u0026nbsp;\u003c/p\u003e\n \u003cp\u003epN0\u003c/p\u003e\n \u003cp\u003epN1/1mi\u003c/p\u003e\n \u003cp\u003epN2/3\u003c/p\u003e\n \u003cp\u003epNx\u003c/p\u003e\n \u003cp\u003eypN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e790 (52.1%)\u003c/p\u003e\n \u003cp\u003e454 (29.9%)\u003c/p\u003e\n \u003cp\u003e249 (16.4%)\u003c/p\u003e\n \u003cp\u003e5 (0.3%)\u003c/p\u003e\n \u003cp\u003e19 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e500 (47.5%)\u003c/p\u003e\n \u003cp\u003e335 (31.8%)\u003c/p\u003e\n \u003cp\u003e201 (19.1%)\u003c/p\u003e\n \u003cp\u003e2 (0.2%)\u003c/p\u003e\n \u003cp\u003e16 (1.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e290 (62.6%)\u003c/p\u003e\n \u003cp\u003e119 (25.7%)\u003c/p\u003e\n \u003cp\u003e48 (10.4%)\u003c/p\u003e\n \u003cp\u003e3 (0.6%)\u003c/p\u003e\n \u003cp\u003e3 (0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.300\u003c/p\u003e\n \u003cp\u003e0.075\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eMultifocal tumour\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1227 (80.9%)\u003c/p\u003e\n \u003cp\u003e209 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e840 (79.7%)\u003c/p\u003e\n \u003cp\u003e146 (13.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e387 (83.6%)\u003c/p\u003e\n \u003cp\u003e62 (13.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0.589\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eTumour grade\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eI/II\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003cp\u003epCR\u003c/p\u003e\n \u003cp\u003eUnknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e892 (58.8%)\u003c/p\u003e\n \u003cp\u003e521 (34.3%)\u003c/p\u003e\n \u003cp\u003e92 (6.1%)\u003c/p\u003e\n \u003cp\u003e12 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e568 (53.9%)\u003c/p\u003e\n \u003cp\u003e401 (38%)\u003c/p\u003e\n \u003cp\u003e78 (7.4%)\u003c/p\u003e\n \u003cp\u003e8 (0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e324 (70%)\u003c/p\u003e\n \u003cp\u003e121 (26.1%)\u003c/p\u003e\n \u003cp\u003e14 (3%)\u003c/p\u003e\n \u003cp\u003e4 (0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003ePerivascular Invasion\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003cp\u003epCR/Unknown\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e864 (57%)\u003c/p\u003e\n \u003cp\u003e536 (35.3%)\u003c/p\u003e\n \u003cp\u003e117 (7.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e555 (52.7%)\u003c/p\u003e\n \u003cp\u003e404 (38.3%)\u003c/p\u003e\n \u003cp\u003e95 (9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e309 (66.7%)\u003c/p\u003e\n \u003cp\u003e132 (28.5%)\u003c/p\u003e\n \u003cp\u003e22 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRemoved breast tissue (g)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e189 (5-2950)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e350 (5-2950)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e80 (8-1832)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSurgical Margins\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;Negative\u0026nbsp;\u003c/p\u003e\n \u003cp\u003ePositive (invasive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1423 (91.6%)\u003c/p\u003e\n \u003cp\u003e94 (6.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e995 (94.4%)\u003c/p\u003e\n \u003cp\u003e59 (5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e428 (92.4%)\u003c/p\u003e\n \u003cp\u003e35 (7.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0.146\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eSystemic therapy\u003c/p\u003e\n \u003cp\u003eNeoadjuvant\u003c/p\u003e\n \u003cp\u003eAdjuvant\u003c/p\u003e\n \u003cp\u003eEndocrine therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e533 (35.1%)\u003c/p\u003e\n \u003cp\u003e806 (53.1%)\u003c/p\u003e\n \u003cp\u003e1208 (79.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e477 (45.2%)\u003c/p\u003e\n \u003cp\u003e562 (53.3%)\u003c/p\u003e\n \u003cp\u003e766 (72.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e56 (12.1%)\u003c/p\u003e\n \u003cp\u003e244 (52.7%)\u003c/p\u003e\n \u003cp\u003e391 (84.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eRadiotherapy\u003c/p\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e248 (16.3%)\u003c/p\u003e\n \u003cp\u003e1264 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e173 (16.4%)\u003c/p\u003e\n \u003cp\u003e879 (83.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e75 (16.2%)\u003c/p\u003e\n \u003cp\u003e385 (83.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003cp\u003e0.946\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eLocal recurrence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e64 (4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e49 (4.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e19 (4.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 142px;\"\u003e\n \u003cp\u003eDistant recurrence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e221 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 113px;\"\u003e\n \u003cp\u003e186 (17.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 94px;\"\u003e\n \u003cp\u003e35 (7.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 96px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\" valign=\"top\" style=\"width: 559px;\"\u003e\n \u003cp\u003eOR (Odds Ratio); BMI (Body Mass Index); DCIS (Ductal Carcinoma In Situ); pCR (pathological complete response); *In situ (biopsy) with invasive tumour in the specimen\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eMost patients (1,054; 69.5%) were diagnosed after presenting clinical signs. Among them, palpable tumours were the most common, occurring in 994 patients (94.3%). Other clinical signs and symptoms included nipple discharge or retraction in 39 patients (3.7%), skin changes in 19 patients (1.8%) and pain in 2 patients (0.2%). In contrast, 463 tumours (30.5%) were detected through screening, without any reported clinical abnormalities. Mammography was the primary diagnostic method, used in 409 cases (88.3%), followed by ultrasound in 54 cases (11.7%).\u003c/p\u003e\n\u003cp\u003eA comprehensive analysis of the clinical characteristics revealed significant disparities between the groups. Symptomatic patients exhibited a significantly higher prevalence of adverse tumour characteristics when compared to those diagnosed by screening: a greater number of advanced tumours (p \u0026lt; 0.001), more aggressive subtypes (p \u0026lt; 0.001), also grade III tumours (p \u0026lt; 0.001) and the presence of perivascular invasion were more prevalent (p \u0026lt; 0.001). Focality was the only variable without significant difference between the groups (p = 0.589)\u0026nbsp;(Table 1).\u003c/p\u003e\n\u003cp\u003eMastectomy and neoadjuvant chemotherapy were more frequently performed in the group diagnosed by clinical signs and symptoms (p \u0026lt; 0.001), compared with the asymptomatic group. Instead of similarity between local recurrence rates (p = 0.21), the symptomatic group had a higher number of distant recurrence events (p \u0026lt; 0.001).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs shown in Table 2 and Figure 2, both YLL and YDFL increased progressively with advancing clinical stage, ranging from nearly zero in stage I to more than 15 years in stage III.\u003c/p\u003e\n\u003cp\u003eTable 2. Summary of Years of Life Lost and Years of Disease-Free Lost by Stage\u003c/p\u003e\n\u003ctable border=\"0\" cellspacing=\"0\" cellpadding=\"0\" width=\"81%\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eClinical Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eMean YLL (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eSD YLL\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003eMean YDFL (y)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003eSD YDFL\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e597\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e1.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003eRef.\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e665\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e6.70\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e3.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e7.50\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1.46\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003eIII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 8px;\"\u003e\n \u003cp\u003e255\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 22px;\"\u003e\n \u003cp\u003e16.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 14px;\"\u003e\n \u003cp\u003e4.79\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 24px;\"\u003e\n \u003cp\u003e15.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 16px;\"\u003e\n \u003cp\u003e1.70\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eYLL (Years of Life Lost); YDFL (Years of Disease-Free Lost); SD (Standard Deviation)\u003c/p\u003e\n\u003cp\u003eIn the univariate analysis, the detection method was significantly associated with poorer disease-free survival (DFS), breast cancer-specific survival (BCSS), and overall survival (OS). Compared with the asymptomatic group, patients diagnosed based on clinical signs had a 5-year DFS of 77.8% versus 89.5% (HR 1.93; 95% CI, 1.48\u0026ndash;2.51; p \u0026lt; 0.001), a 5-year BCSS of 86.1% versus 95.3% (HR 2.70; 95% CI, 1.86\u0026ndash;3.92; p \u0026lt; 0.001), and a 5-year OS of 81.1% versus 92.1% (HR 2.13; 95% CI, 1.60\u0026ndash;2.85; p \u0026lt; 0.001) (data not shown).\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;However, in the multivariate analysis, the detection method was no longer an independent predictor of survival. Instead, older age, larger tumour size, advanced clinical stages (IIIa\u0026ndash;IIIc), pathological axillary involvement, grade III tumours, perivascular invasion, as well as HER2-positive and triple-negative subtypes, emerged as the factors significantly associated with the survival outcomes (Supplementary Tables S1-S3).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eIn this cohort study, unfavourable tumour characteristics were significantly more prevalent in patients whose biopsy was performed after the appearance of clinical signs and symptoms. Fewer than 40% of the entire cohort were diagnosed at clinical stage I. Survival rates were significantly affected by clinical and pathological stages, age, subtype, and perivascular invasion.\u003c/p\u003e \u003cp\u003eIt is well documented that countries with organized screening programmes have achieved reductions up to a 40% in fatal-breast cancer rates and an earlier stage of cancer diagnosis among screened women [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. In contrast, the high proportion of symptomatic diagnoses in our study reflects the limited effectiveness of screening as currently implemented in Brazil, where most women undergo mammography on their own or opportunistically during routine consultations. In 2023, screening coverage in the public health system (Sistema \u0026Uacute;nico de Sa\u0026uacute;de; SUS) remained below 35% nationwide [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent Brazilian studies have reinforced the association between opportunistic screening and advanced presentation at diagnosis. At the Instituto do C\u0026acirc;ncer do Estado de S\u0026atilde;o Paulo (ICESP), tumours detected by mammography were smaller and less likely to present nodal involvement than those clinically detected [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. The multicenter AMAZONA III study reported similar findings, showing that 76.9% of public-sector patients were diagnosed after symptoms onset versus 47% in the private sector, and that stage II and III disease predominated among public patients [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e]. Together, these findings confirm that, in Brazil, most breast cancers are still detected symptomatically and at later stages.\u003c/p\u003e \u003cp\u003eInternational evidence highlights the benefits of population-based programmes. The Dutch national screening programme achieves about 70% coverage among women aged 50\u0026ndash;75 years. In 2023, 67% of tumours detected were stage pT1, only 1.1% were pT3/pT4, and the fatal-breast cancer rate decreased by around 40% compared with the pre-implementation period [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Moreover, in the Netherlands, treating one advanced breast cancer case costs over \u0026euro;50,000, while each screening mammogram costs around \u0026euro;65, illustrating that even a small reduction in late-stage cases offsets the full cost of screening [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eIn Brazil, despite national recommendations, the absence of organized invitations, quality assurance, and structured diagnostic pathways contributes to delayed diagnosis and high proportions of advanced disease. This scenario not only limits survival gains but also imposes a substantial and avoidable financial burden on the public health system. Strengthening population coverage, training professionals, and improving referral networks are essential steps toward implementing an affective national programme.\u003c/p\u003e \u003cp\u003eIn our cohort, both YLL and YDFL increased progressively with advancing clinical stage, exceeding 15 years in stage III. Similar patterns have been reported in population-based studies, showing a marked reduction in expected lifetime with late-stage diagnosis [\u003cspan additionalcitationids=\"CR15 CR16\" citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e]. Brazilian studies have also demonstrated that advanced-stage presentation remains a major contributor to premature mortality and YLL due to breast cancer [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Such findings emphasize how delays in diagnosis translate into substantial loss of potential life-years, reinforcing the need for effective, organized screening programmes and timely access to treatment.\u003c/p\u003e \u003cp\u003eEvidence indicates that detection method alone is not an independent prognostic factor when tumour stage and biology are considered [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. The apparent survival benefit of screen-detected tumours arises mainly from earlier diagnosis and less aggressive disease. Classic screening biases, such as lead-time and length-time effects, may further amplify this effect if not adjusted analytically [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eSymptomatic patients were more likely to undergo mastectomy (54.8%) than those whose tumours were detected by screening (45.2%) (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mactier et al. similarly reported higher rates of breast-conserving surgery and superior overall and cancer-specific survival among screen-detected cases, even after multivariate adjustment [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]. These observations reinforce that the benefit of screening derives from earlier detection, enabling less extensive surgery and improved outcomes.\u003c/p\u003e \u003cp\u003eEvidence from other countries confirms that a structured, equitable screening system can substantially reduce mortality. Long-term follow-up from Norway, Finland, and Sweden demonstrates reductions of 30\u0026ndash;40% in breast cancer\u0026ndash;specific deaths, corresponding to approximately 20\u0026ndash;30 life-years gained per 1000 women screened [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e]. Achieving comparable results in Brazil will require not only greater coverage but also improvements in diagnostic access, education, and treatment pathways.\u003c/p\u003e \u003cp\u003eIn summary, the predominance of advanced-stage disease in our cohort reflects systemic limitations in early detection rather than intrinsic lack of prognostic value in screening. Implementing a truly organized screening programme, integrated with timely diagnostic confirmation and treatment access, is essential to reduce avoidable morbidity, improve survival outcomes, and optimise public resource allocation.\u003c/p\u003e \u003cp\u003eThis study included a large number of patients representing all invasive non metastatic stages and molecular subtypes of breast cancer, and provides comprehensive real-world data on diagnosis, treatment, and long-term outcomes in a public tertiary centre. The findings should, however, be interpreted considering the study\u0026rsquo;s limitations, particularly its single-center and retrospective design. Conducting prospective, randomized trials in this context would be unethical.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIn this cohort, breast cancers detected after the onset of symptoms presented more advanced stages and higher mastectomy rates. Despite national guidelines recommendations for screening, the predominance of advanced-stage diagnoses reflects the limited effectiveness of non-systematic screening implementation. Advanced disease was associated with substantial loss of life-years and disease-free years, reinforcing the prognostic benefit of early-stage breast cancer detection.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eDeclaration of Interest Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFunding: None\u003cbr\u003e\u0026nbsp;Conflicts of interest: None declared\u003cbr\u003e\u0026nbsp;Ethical approval: We confirm that the study complies with ethical standards, including approval by the Research Ethics Committee of UNICAMP (CAAE 84450518.9.0000.5404)\u003c/p\u003e\n\u003cp\u003eConsent to Participate declarations: The clinical data of the patients included in the study were obtained from the medical records only by the research team and recorded in an electronic file. No samples of biological material were obtained from the patients, no interviews were conducted, and the study did not interfere with the follow-up of the patients included in the study. The application of the Consent to Participate declaration was waived by the Research Ethics Committee of UNICAMP.\u003c/p\u003e\n\u003cp\u003eAuthor contribution: N.A. wrote the original draft, designed the study;F. B. wrote the original draft, designed the study, contributed to the interpretation of results; M.B.K. performed the data collection and analysis; N.S. performed the data collection and analysis; C.C. wrote the original draft, contributed to the interpretation of results; R.T. wrote the original draft, contributed to the interpretation of results; C.C-F. contributed to the interpretation of results; G.D. contributed to the interpretation of results; J.S. contributed to the interpretation of results; L.C.Z. designed the study, contributed to the interpretation of results, reviewed and wrote the original draft. All authors contributed to the final manuscript and approved it.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eMinist\u0026eacute;rio da Sa\u0026uacute;de. Instituto Nacional de C\u0026acirc;ncer Jos\u0026eacute; Alencar Gomes da Silva (INCA). Estimativa 2020: incid\u0026ecirc;ncia de c\u0026acirc;ncer no Brasil. 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Survival after standard or oncoplastic breast-conserving surgery versus mastectomy for breast cancer. BJS Open. 2025;9(2):zraf002. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/bjsopen/zraf002\u003c/span\u003e\u003cspan address=\"10.1093/bjsopen/zraf002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"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":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"breast cancer, clinical diagnosis, screening, imaging diagnosis, survival, mammography, surgery, life expectancy","lastPublishedDoi":"10.21203/rs.3.rs-8701531/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8701531/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eBreast cancer (BC) is the most prevalent malignancy among Brazilian women. Advanced-stage diagnosis remains frequent, largely due to limited access to screening and treatment. Despite national recommendations for organised screening, implementation remains opportunistic. This study compared prognostic outcomes between clinically detected and opportunistically screened breast cancers and estimated Years of Life Lost (YLL) and Years of Disease-Free Life Lost (YDFL) to quantify the impact of clinical stage on survival and disease-free survival expectancy. A retrospective cohort of 1,517 women with unilateral, invasive, non-metastatic BC who underwent surgery at a tertiary public hospital in Brazil between 2012 and 2016 was analysed. Patients were classified as symptomatic (diagnosed based on clinical signs and symptoms) or asymptomatic (diagnosed through screening). Clinicopathological features, treatments, and outcomes were compared using the Chi-square, Fisher’s exact, and Kruskal–Wallis tests. Survival was analysed using Kaplan–Meier estimates and Cox regression models. YLL and YDFL were derived from Weibull survival models, using stage I patients as the reference. Most patients (69.5%) were symptomatic at diagnosis, with palpable tumours in 94.3%. Compared with asymptomatic cases, symptomatic women were younger and presented with more advanced stages, and aggressive tumours. They more frequently underwent mastectomy and neoadjuvant chemotherapy (p \u0026lt; 0.001). Both YLL and YDFL increased progressively with advancing clinical stage, reaching over 15 years in stage III. The predominance of advanced-stage diagnoses reflects the limited effectiveness of non-systematic screening implementation. Advanced disease was associated with substantial loss of lifetime and disease-free years, reinforcing the prognostic value of early-stage detection.\u003c/p\u003e","manuscriptTitle":"Survival implications of non-organized breast cancer screening in a Brazilian tertiary women’s health center: A retrospective cohort study of 1517 patients","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-02-12 13:54:01","doi":"10.21203/rs.3.rs-8701531/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-23T16:35:31+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-23T11:47:14+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31348281946362662465027102843238649378","date":"2026-03-02T20:37:03+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-02-10T01:00:58+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"142141448788304341210487080578650140057","date":"2026-02-10T00:49:27+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-02-09T15:48:32+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-03T04:35:29+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-03T03:15:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-03T03:14:25+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2026-01-26T14:45:21+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8e02b7a6-48c5-4202-8f46-112c78c300d4","owner":[],"postedDate":"February 12th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-04-02T20:08:26+00:00","versionOfRecord":[],"versionCreatedAt":"2026-02-12 13:54:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8701531","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8701531","identity":"rs-8701531","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}