Effects of BMI on prognosis , disease-free survival and overall survival of breast cancer

Effects of BMI on prognosis , disease-free survival and overall survival of breast cancer | 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 Effects of BMI on prognosis , disease-free survival and overall survival of breast cancer Vahid Zangouri, Souzan Soufizadeh Balaneji, Roya Golmoradi, Ehsan Kafili, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4376201/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 13 Feb, 2025 Read the published version in BMC Cancer → Version 1 posted 4 You are reading this latest preprint version Abstract Background Obese breast cancer patients have worse prognosis than normal weight patients, but the level at which obesity is prognostically unfavorable is unclear. This study aimed to investigate different effects of Body Mass Index (BMI) on prognosis disease-free survival and overall survivor of breast cancer patients. Method This retrospective cohort study analyzed the medical records of breast cancer patients who sought treatment at Namazi hospital in Shiraz, Iran between 2014 and 2019. Three groups of patients were divided according to BMI. Menopausal status, BMI status, clinicopathological characteristics, treatment, and overall survival (OS), and disease free survival (DFS) were comprehensively evaluated. Results Of the 7134 breast cancer patients, the majority (42.6%) were in 25–30 kg/m 2 . Menopausal status significantly were associated with obesity (P <0 .001). The majority of patients were categorized as grade 2 and stage 2 according to the BMI categories (P = 0.12, P = 0.08, respectively). BMI categories regardless of menopausal status displayed increased 1, 3, and 5-year DFS and 5- year OS in stage 1 and increased 1, 3, and 5-year OS and 1 and 3-year DFS in stage 2. In stage 3, the risks of relapse and death were significantly decreased in all three groups of BMI patients with post-menopausal period. Conclusion Obesity leads to worse DFS and OS in patients with BC and the effects of obesity on the breast cancer prognosis seem to be clinically related to menopausal status. Once validated, these results should be considered in the development of prevention programs. Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Figure 7 Figure 8 Figure 9 Figure 10 Figure 11 Figure 12 Introduction Breast cancer (BC) stands as the most prevalent malignant tumor and ranks among the primary contributors to cancer-related fatalities in women ( 1 , 2 ). Over the last decade, there has been a gradual rise in the global incidence of BC ( 3 ). Thanks to advancements in early detection and the enhancement of treatment modalities, the outlook for breast cancer sufferers has significantly improved ( 4 ). Various factors impacting the prognosis of BC comprise axillary lymph nodes, primary tumor size, the utilization of adjuvant systemic treatments, tumor-infiltrating lymphocytes, estrogen receptor, human epidermal growth factor receptor-2 (HER-2), age, menopausal status, ethnicity, alcohol consumption, and smoking habits ( 5 ). Research shows that excess body fat increases the risk for several cancers ( 6 ). Additionally, there is now a widespread consensus on the adverse prognostic implications of obesity or overweight for breast cancer beyond its role as a risk factor ( 7 ). Currently, obesity has reached epidemic proportions, with 69% of adults in the United States and 38% globally falling into the overweight or obese category ( 8 , 9 ). Obesity is linked to changes in overall body physiology and hormonal balance that contribute to various health conditions like diabetes and cardiovascular diseases ( 10 ). Moreover, obesity is correlated with an elevated likelihood of developing several types of cancer and with reduced survival rates for individuals diagnosed with those cancers ( 11 ). The National Institute of Health (NIH) categorizes body mass index (BMI) as follows: underweight < 18.5 kg/m 2 , normal weight 18.5 to < 25 kg/m 2 , overweight 25.0 to < 30 kg/m 2 , and obesity ≥ 30.0 kg/m 2 ( 12 ). Around 75% of women in the United States and 50% in Europe are overweight or obese at the time of breast cancer diagnosis, and treatments for breast cancer frequently lead to additional weight gain ( 13 ). A high BMI is linked to poorer clinical outcomes in patients with early-stage breast cancer (EBC) ( 14 ). The precise biological mechanisms behind the relationship between adiposity and breast cancer (BC) survival are not fully understood, but they may involve the interplay of hormones, adipocytokines, and inflammatory cytokines, which play roles in cell survival, apoptosis, migration, and proliferation ( 15 ). Numerous studies have explored the connection between obesity and BC outcomes ( 5 , 16 , 17 ). Li et al. found that a high BMI significantly impacts overall survival (OS) but does not significantly affect disease-free survival (DFS) ( 18 ). Conversely, Fontanella et al. demonstrated that obese patients have significantly shorter average DFS and OS compared to patients with a healthy weight ( 19 ). Most research investigating the correlation between breast cancer and BMI has focused on Western populations. However, the mechanistic understanding of the association between obesity/overweight and the risk of breast cancer recurrence and mortality among Asian women, based on menopausal status, is limited. Given that Asian women typically have lower BMIs than Western women, this study aimed to examine the varying effects of BMI on prognostic factors, OS, and DFS in BC patients with Invasive Ductal Carcinoma subtypes. Methods The study was conducted under the Declaration of Helsinki and with approval from the Ethics Committee of Shiraz Medical Science University. This retrospective cohort study analyzed the medical records of breast cancer patients who sought treatment at Namazi hospital in Shiraz, Iran between 2014 and 2019. These data were studied in 2024. All cases included in the study displayed tumor characteristics that align with the morphological guidelines specified in the World Health Organization (WHO) histological classification of breast tumors ( 20 ). The selection criteria for patients were centered on the verification of primary breast cancer through histological analysis after curative surgical procedures, as well as the patient being over 18 years of age. Individuals under 18.5 kg/m2, diagnosed with stage IV breast cancer recently, those lacking complete pathological or postoperative treatment data, and patients who were lost to follow-up were excluded from the study. Weight and height data were documented at the time of the initial diagnosis, and BMI was computed by dividing the weight in kilograms by the square of the height in meters. BMI was categorized according to WHO standard: normal weight, BMI < 25.0 kg/m2; overweight, 25.0 ≤ BMI < 30.0 kg/m2; and obesity, BMI ≥ 30.0kg/m2. Three groups were divided according to BMI when breast cancer diagnosis: normal weight group, overweight group, and obesity group. Furthermore, a stratified analysis about relationship between BMI and prognosis of breast cancer was conducted in line with menopausal status when breast cancer diagnosed. Menopausal status was defined by 1 year of amenorrhea, or previous bilateral oophorectomy and post-menopause refers to the final stage of the menopause process, and marks the end of the reproductive stage of life ( 7 ). All participants in the study underwent regular monitoring following surgery, chemotherapy, radiation therapy, and hormonal treatment. This follow-up was conducted every 3–6 months within the first two years after surgery, every 6 months over the subsequent 5 years, and annually thereafter with imaging under guide of National Comprehensive Cancer Network (NCCN) ( 21 ). All occurrences were meticulously documented in the database. Pathology Analysis Immunohistochemical (IHC) staining was utilized to evaluate the levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu) in adherence to a standardized protocol established by the Pathology Department at Shiraz University of Medical Sciences. A confirmed case of HER2neu-amplified breast cancer was used as a positive control for HER2neu. A sample is considered ER negative if < 1% or 0%, tumors demonstrating 1% or more positive nuclear staining for ER or PR were categorized as ER-positive or PR-positive, respectively. In cases where intermediate (2+) immunohistochemical expression of HER2neu was observed, subsequent testing using fluorescent in situ hybridization (FISH) was conducted to assess HER2neu gene amplification. The breast tumors were stratified into four subtypes based on ER, PR, and HER2neu expression: luminal A (ER-positive and/or PR-positive, HER2neu-negative), luminal B (ER-positive and/or PR-positive, HER2neu-positive), HER2neu+ (ER-negative and PR-negative, HER2-positive), and triple-negative (TN) (ER-negative, PR-negative, and HER2neu-negative), following the criteria delineated by Carey ( 22 ). Overall survival (OS) was defined as the period from the initial diagnosis of breast cancer until either death from any cause or the last recorded follow-up visit. Disease-free survival (DFS) was calculated as the duration from the date of surgery to the occurrence of the first metastasis or recurrence ( 23 ). The TNM staging system for breast cancer was assessed according to the guidelines outlined in the seventh edition of the American Joint Committee on Cancer (AJCC). Statistical analysis The normality of the distribution of continuous variables was tested using a one-sample Kolmogorov-Smirnov test. Continuous variables with a normal distribution were presented as mean (SD), while non-normal variables were reported as frequency (percentage). The means of two continuous normally distributed variables were compared using independent samples Student’s T-test. When appropriate, frequencies of categorical variables were compared using Pearson Chi-square or Fisher’s exact test. Overall survival (OS) and disease-free survival (DFS) were evaluated using the Kaplan-Meier analysis. Analyses were performed using SPSS statistical software (version 25), and a P-value of < 0.05 was considered statistically significant. Results Table 1 displays a comparative analysis of patients based on their body mass index (BMI) status. Among the 7134 breast cancer patients studied, 2026 (28.31%) had a BMI < 25 kg/m2, 3045 (42.6%) fell within the range of 25.0 ≤ BMI < 30.0 kg/m2, and 2063 (29.1%) had a BMI of 30 kg/m2 or higher. The mean age at diagnosis was similar across the three BMI groups, but there was a tendency for older patients to be more prevalent in the obese group (P > 0.05). Premenopausal patients were more likely to have a lower BMI compared to postmenopausal patients, with almost half of the obese patients being in the postmenopausal period (58.9%). Menopausal status was significantly associated with BMI status (P < 0.001). The majority of patients were classified as grade 2 and stage 2 across the BMI categories (P = 0.12, P = 0.08, respectively). The Luminal A molecular subtype was the most prevalent hormone receptor subtype across all BMI categories, while the Her2 molecular subtype positive was the least common hormone receptor subtype across all BMI categories (P = 0.14). The rate of patients undergoing axillary lymph node dissection (ALND) initially was higher compared to other Axillary Types across all BMI categories (P = 0.82). Hormone therapy was equally distributed among these three groups (P = 0.26). In all three groups, over 80% of patients did not receive preoperative chemotherapy (P = 0.02); however, postoperative chemotherapy was administered to over 80% of patients in all three groups (P = 0.14). The highest proportion of patients undergoing axillary and chest radiotherapy had a BMI higher than 25 kg/m 2 , while this proportion was lower in patients with a BMI below 25 kg/m 2 (P < 0.001). Table 1 Comparative analysis of patient characteristics across body mass index (kg/m 2 ) status of studied patients. BMI group P-value BMI < 25 (n = 2026) 25.0 ≤ BMI 0.05 Menopausal status Premenopausal 1107 (54.6%) 1510 (49.5%) 846 (41.1%) < 0.001 Postmenopausal 919(55.4%) 1550 (50.5%) 1217 (58.9%) Pathology Tumor Grade 1 363 (19.4%) 498 (17.7%) 336 (17.6%) 0.12 2 1137 (60.8%) 1739 (61.9%) 1145 (59.9%) 3 370 (19.8%) 571 (20.3%) 432 (22.6%) Axillary Type ALND at first 916 (45.2%) 1357 (44.6%) 924 (44.8%) 0.82 SLNB only 787 (38.8%) 1230 (40.4%) 823 (39.9%) SLNB then ALND 323 (15.9%) 458 (15.0%) 316 (15.3%) Stage 1 403 (32.5%) 582 (29.9%) 380 (28.2%) 0.08 2 730 (58.9%) 1172 (60.1%) 820 (60.8%) 3 107 (8.6%) 195 (10.0%) 149 (11.0%) Preoperative Chemotherapy No 1674 (81.1%) 2574 (83.3%) 1765 (84.0%) 0.02 yes 391 (18.9%) 515 (16.7%) 336 (16.0%) postoperative Chemotherapy No 309 (15.0%) 416 (13.5%) 272 (12.9%) 0.14 yes 1756 (85.0%) 2673 (86.5%) 1829 (87.1%) Axillary and Chest Radiotherapy No 541 (26.2%) 700 (22.7%) 442 (21.0%) < 0.001 yes 1524 (73.8%) 2389 (77.3%) 1659 (79.0%) Hormone therapy No 495 (24.0%) 725 (23.5%) 534 (25.4%) 0.26 Yes 1570 (76.0%) 2364 (76.5%) 1567 (74.6%) Hormone receptor Luminal A 1089(53.8%) 1726 (56.7%) 1223 (59.3%) 0.14 Luminal B 435 (21.5%) 682 (22.4%) 389 (18.9%) Her2 210 (10.4%) 304 (10%) 223(10.8%) Triple Negative 292(14.6%) 333 (10.9%) 228(11%) Table 2 presents a comparative analysis of patient characteristics and menopausal status based on the BMI (kg/m2) status of the patients under study. Quadrantectomy (BCS) emerged as the most common type of surgery among both pre- and post-menopausal women in all three groups. Mastectomy was more prevalent among postmenopausal patients than premenopausal patients in all three groups (P < 0.001 for BMI < 25 and 25.0 ≤ BMI < 30.0 kg/m 2 , P = 0.6 for patients with BMI ≥ 30 kg/m 2 ). Regardless of menopausal status, the majority of patients were classified as grade II based on BMI. Furthermore, stage 3 was more frequently observed in postmenopausal patients across all three groups (P = 0.16, P = 0.17, P = 0.51, respectively). The incidence of multifocal breast tumors was higher in premenopausal patients compared to postmenopausal patients in all three BMI status groups. A statistically significant association was found between the presence of multifocal breast tumors and menopausal status across the three BMI status groups (P = 0.004, < 0.001, and 0.01, respectively). A statistical examination of tumor grading across three defined categories indicated that the majority of premenopausal patients in all three groups were classified as grade II, regardless of BMI status. Conversely, postmenopausal in all three groups were predominantly classified as grade II. Notably, Grade III Permanent Pathology Tumors were more prevalent in premenopausal women compared to postmenopausal women in all three groups (P < 0.001, P = 0.01, and P = 0.01, respectively). While the majority of patients did not exhibit tumor invasion across the three BMI categories, premenopausal patients displayed a higher prevalence of non-invasive tumors compared to postmenopausal patients. A statistically significant relationship was observed between the occurrence of various types of invasion and menopausal status in the studied population with a 25.0 ≤ BMI < 30.0 kg/m2 (P = 0.03). Vascular invasion was more frequently observed in postmenopausal patients across all three BMI categories. Both Vascular and Preneural invasion, as well as Lymphatic and Vascular invasion, displayed similar distributions based on menopausal status in all three BMI categories. Furthermore, a statistically significant correlation was noted between the occurrence of different invasion types and tumor subtypes (P < 0.001). Axillary lymph node dissection (ALND) was the most common type of axillary surgery performed in postmenopausal patients within the BMI < 25 kg/m2 and 25.0 ≤ BMI < 30.0 kg/m2 groups. For postmenopausal patients with a BMI ≥ 30 kg/m 2 , ALND then SLNB were the predominant types of axillary surgeries performed (P = 0.56). Conversely, a higher proportion of patients in the premenopausal period underwent SLNB alone, regardless of BMI status. A statistically significant correlation was identified between the type of axillary surgery and menopausal status within the studied population with a BMI of 25.0 ≤ BMI < 30.0 kg/m2 (P = 0.002). The Luminal A hormone receptor subtype was prevalent among all breast cancer patients, irrespective of menopausal or BMI status, while Luminal B was more commonly found in premenopausal patients compared to postmenopausal patients across all three BMI groups. A statistically significant variance was noted in the distribution of hormone receptor subtypes based on menopausal status within the three BMI groups (P < 0.001 for patients with BMI < 25 kg/m2 and BMI 25.0 ≤ BMI < 30.0 kg/m2, and P = 0.007 for patients with BMI ≥ 30 kg/m 2 , respectively). Hormone therapy was provided to the majority of patients in all three groups regardless of menopausal status, with postmenopausal women receiving hormone therapy more frequently than premenopausal women across all BMI groups. A statistically significant relationship was found between hormone therapy and menopausal status in patients with a higher BMI of ≥ 30 kg/m 2 (P = 0.006). Radiotherapy was administered to a significant percentage of patients in all three BMI groups, with a higher prevalence among postmenopausal patients in all three groups (P < 0.001 in all groups). Postoperative chemotherapy was utilized in a considerable number of patients across all three groups, but it was more common among premenopausal patients in all three BMI groups (P = 0.01, P < 0.001, P = 0.01 in the three groups, respectively). Preoperative chemotherapy was not a common treatment regardless of the patients' BMI status. Preoperative chemotherapy was more frequently administered to premenopausal patients in all three BMI groups (P < 0.001 in patients with BMI < 25 kg/m2 and BMI 25.0 ≤ BMI < 30.0 kg/m2, and P = 0.01 in patients with BMI ≥ 30 kg/m 2 , respectively). Table 2 comparative analysis of patient characteristics and menopausal status according body mass index (kg/m2 ) status of studied patients. BMI < 25 kg/m 2 25.0 ≤ BMI < 30.0 kg/m2 BMI ≥ 30 kg/m 2 Pre menopausal Post menopausal P-value Pre menopausal Post menopausal Pvalue Pre menopausal Post menopausal P-value Mean age (SD) 47.57(8.27) 66.12(9.36) 49.31(7.86) 65.29(8.855) 50.62(7.56) 64.67(8.28) Surgery Type < 0.001 < 0.001* 0.06 Quadrantectomy (BCS) 664(57.7%) 436 (49.1%) 991 (61.4%) 849 (58.2%) 585 (61.4%) 718 (62.7%) Mastectomy 417 (36.1%) 417 (46.9%) 508 (31.4%) 553 (37.9%) 304 (31.9%) 374 (32.6%) Quadrantectomy (BCS) ,then Mastectomy 69 (6.0%) 28 (3.1%) 111 (6.9%) 49 (3.4%) 111 (6.9%) 49 (3.4%) Stage 1 242 (33.5%) 158 (31.7%) 0.16 313 (29.4%) 267 (30.8%) 0.17 192 (29.4%) 184 (26.9%) 0.51 2 427 (59.1%) 288 (57.8%) 655 (61.6%) 503 (58.1%) 392 (60.1%) 420 (61.4%) 3 53 (7.3%) 52 (10.4%) 95 (8.9%) 96 (11.1%) 68 (10.4%) 80 (11.7%) Permanent Pathology Multifocal No 1049 (91.2%) 833 (94.6%) 0.004 1479 (91.9%) 1387 (95.7%) < 0.001 867 (91.4%) 1070 (94.1%) 0.01 Yes 101 (8.8%) 48 (5.4%) 867 (8.1%) 1070 (4.3%) 82 (8.6%) 67 (5.9%) Permanent Pathology Tumor Grade 1 174 (16.7%) 184 (23.1%) < 0.001 232 (15.7%) 255 (19.5%) 0.01 149 (17.3%) 185 (17.8%) 0.01 2 638 (61.3%) 480 (60.2%) 921 (62.5%) 806 (61.7%) 491 (57.0%) 645 (62.2%) 3 228 (21.9%) 134 (16.8%) 321 (21.8%) 246 (18.8%) 222 (25.8%) 207 (20.0%) Invasion Non 587) 51.0%( 414)47.0%( 0.06 756(47%) 626(43.2) 0.03 439(46.3%) 499(43.9%) 0.3 Vascular 271)23.6%( 217)24.6%( 392 (24.3%) 406 (28.0%) 239 (25.2%) 315 (27.7%) Preneural 75)6.5%( 76) 8.6%( 120 (7.5%) 110 (7.6%) 68 (7.2%) 80 (7.0%) Both of them 178)15.5%( 155) 17.6%( 290(18.0%) 278 (19.2% 170 (17.9%) 217 (19.1%) Lymphatic, Vascular 39) 3.4%( 19)2.2%( 52 (3.2%) 30 (2.1%) 33 (3.5%) 26 (2.3%) Axillary Type ALND at first 488 (42.7%) 403 (47.5%) 0.07 660 (41.3%) 678 (47.8%) 0.002 381(40.5%) 442(39.9%) 0.56 SLNB 458 (40.1%) 323 (38.0%) 682 (42.7%) 543 (38.3%) 151 (16.0%) 162 (14.6%) SLNB then ALND 197 (17.2%) 123 (14.5%) 255 (16.0%) 198 (14.0%) 409 (43.5%) 503 (45.4%) Hormone receptor Luminal A 564 (49.0%) 406 (46.1%) < 0.001 772 (48.0%) 717 (49.4%) < 0.001 449 (47.3%) 579 (50.9%) 0.007 Luminal B 211 (18.3%) 129 (14.6%) 288 (17.9%) 187 (12.9%) 142 (15.0%) 149 (13.1%) Her2 80 (7.0%) 71 (8.1%) 143 (8.9%) 135 (9.3%) 102 (10.7%) 81 (7.1%) Triple Negative 130 (11.3%) 88 (10.0%) 172 (10.7%) 110 (7.6%) 106 (11.2%) 113 (9.9%) Preoperative Chemotherapy No 892 (77.6%) 753 (85.5%) < 0.001 1300 (80.7%) 1248 (86.1%) < 0.001 776 (81.8%) 976 (85.8%) 0.01 Yes 258 (22.4%) 128 (14.5%) 310 (19.3%) 202 (13.9%) 173 (18.2%) 161 (14.2%) Postoperative Chemotherapy No 154 (13.4%) 152 (17.3%) 0.01 185 (11.5%) 228 (15.7%) < 0.001 106 (11.2%) 164 (14.4%) 0.01 Yes 996 (86.6%) 729 (82.7%) 1425 (88.5%) 1222 (84.3%) 843 (88.8%) 973 (85.6%) Radiotherapy postoperative No 324 (36.8%) 204 (17.7%) < 0.001 410 (28.3%) 280 (17.4%) < 0.001 272 (23.9%) 162 (17.1%) < 0.001 Yes 557 (63.2%) 946 (82.3%) 1040 (71.7%0 1330 (82.6%) 865 (76.1%) 787 (82.9%) Hormone therapy No 278(24.2%) 211(24.0%) 0.9 392(24.3%) 328(22.6%) 0.26 268(28.2%) 261(23.0%) 0.006 Yes 872(75.8%) 670(76.0%) 1218(75.7%) 1122(77.4%) 681(71.8%) 876(77.0%) Table 3 presents a summary of the 1-, 3-, and 5-year OS and DFS outcomes for different BMI categories across TNM stages. In stages 1 and 2, all three BMI groups showed OS rates above 99% at 1 and 3 years. Moreover, patients across all BMI categories in stages 1 and 2 exhibited OS rates exceeding 87% at 5 years (Figs. 1 and 2). The OS rates for BMI categories in TNM stages 1 and 2 did not show any statistically significant differences (P = 0.34 in TNM stage 1 and P = 0.98 in TNM stage 2). Moving on to stage 3, all three BMI groups demonstrated OS rates surpassing 97% at 1 and 3 years among the studied patients. For patients in TNM stage 3, the OS rates were above 71% at 5 years (see Fig. 3). The OS outcomes for BMI categories in TNM stage 3 did not show statistically significant discrepancies (P = 0.33). In stages 1 and 2, all three BMI groups displayed DFS rates exceeding 95% at 1 year. Additionally, the DFS rates were higher than 95% at 3 years for patients in TNM stages 1 and 2. Patients in TNM stages 1 and 2 showcased DFS rates above 81% at 5 years (Figs. 4 and 5). The DFS outcomes for BMI categories in TNM stages 1 and 2 did not demonstrate any statistically significant variances (P = 0.77 in TNM stage 1 and P = 0.11 in TNM stage 2). Moving to stage 3, the three BMI groups exhibited DFS rates of 92%, 88%, and 92% at 1 year, respectively. These patients also displayed DFS rates ranging from 81–86% at 3 years (Fig. 6). The DFS rates were between 74–84% at 5 years. The DFS rates for BMI categories in TNM stage 3 did not show any statistically significant differences (P = 0.57). Table 3 summarizes the 1-, 3-, and 5-year OS and DFS outcomes for BMI categories across TNM stage. Overall Survival times (%) Disease Survival times (%) 1 3 5 P value* 1 3 5 P value* Stage1 BMI < 25 100 99 87 0.34 98 96 92 0.77 25.0 ≤ BMI < 30.0 100 99 93 97 95 91 BMI ≥ 30 99 99 93 97 95 92 Stage2 BMI < 25 100 99 87 0.98 95 92 88 0.11 25.0 ≤ BMI < 30.0 100 99 92 97 93 91 BMI ≥ 30 100 99 89 96 93 90 Stage3 BMI < 25 100 100 78 0.33 92 85 74 0.57 25.0 ≤ BMI < 30.0 99 97 71 88 81 78 BMI ≥ 30 100 97 77 92 86 84 * Wilcoxon (Gehan) test Table 4 provides a summary of the 1-, 3-, and 5-year OS and DFS outcomes for various BMI categories based on menopausal status in different TNM stages. In stage 1, all three BMI groups showed OS rates above 99% at 1 and 3 years in premenopausal patients (Fig. 7). For post-menopausal patients, those with BMI < 25 kg/m 2 and BMI 25.0 ≤ BMI < 30.0 kg/m 2 categories displayed exceptional 100% OS rates at 1 and 3 years. Additionally, post-menopausal patients with BMI ≥ 30 kg/m 2 exhibited OS rates of 99% and 98% at 1 and 3 years, respectively (Fig. 10). Irrespective of menopausal status, all patients across all BMI categories demonstrated OS rates of ≥ 85% at 5 years in TNM stage 1 (Figs. 7 and 10). The OS outcomes for BMI categories based on menopausal status in stage 1 did not show any statistically significant differences (P = 0.83 in premenopausal and P = 0.91 in postmenopausal women). Moving to stage 2, patients in all BMI categories, regardless of menopausal status, exhibited OS rates above 98% for 1, 3, and 5 years. Notably, postmenopausal patients with BMI less than 25 kg/m 2 exhibited OS rates of 85% at 5 years (Figs. 8 and 11). The OS outcomes for BMI categories based on menopausal status in stage 2 did not reveal any statistically significant variations (P = 0.43 in premenopausal women and P = 0.81 in postmenopausal women). In TNM stage 3, premenopausal patients categorized as BMI < 25 displayed exceptional 100% OS rates over 1, 3, and 5 years. Patients in the other two BMI categories in the premenopausal group showed OS rates exceeding 97% at 1 and 3 years of follow-up. Moreover, premenopausal patients in the remaining two BMI categories demonstrated OS rates of 70% and 78% at the 5-year mark in stage 3 (Fig. 9). During this stage, all three BMI groups exhibited OS rates surpassing 97% at 1 and 3 years in post-menopausal patients. Post-menopausal patients in the BMI < 25 category showed a 63% OS rate at the 5-year mark. Additionally, post-menopausal patients in the other two BMI categories displayed OS rates of 80% and 79% at 5 years in stage 3, respectively (Fig. 12). The OS outcomes for BMI categories based on menopausal status in stage 2 did not yield statistically significant differences (P = 0.05 in premenopausal and P = 0.42 in postmenopausal women). In stage 1, all three BMI groups exhibited DFS rates of 89% or higher for 1, 3, and 5 years, irrespective of menopausal status (Figs. 1 and 10). The DFS outcomes for BMI categories across menopausal status in TNM stage 1 did not show statistically significant differences (P = 0.31 in premenopausal women and P = 0.25 in postmenopausal women). Moving to stage 2, all three BMI groups demonstrated DFS rates exceeding 90% for 1 and 3 years, regardless of menopausal status (Figs. 14 and 17). Premenopausal patients with a BMI between 25.0 ≤ BMI < 30.0 kg/m2 exhibited a 91% DFS rate over 5 years. Patients in the other two BMI categories achieved an 88% DFS rate over 5 years (Fig. 8). Postmenopausal patients with BMI between 25.0 ≤ BMI 25 kg/m 2 had an 87% DFS rate over the same period (Fig. 17). Similar to stage 1, DFS outcomes for BMI categories across menopausal status in TNM stage 2 were not statistically significant (P = 0.35 in premenopausal women and P = 0.25 in postmenopausal women). In stage 3, patients across all BMI categories, irrespective of menopausal status, exhibited DFS rates higher than 90% for 1 year. Notably, patients with a BMI of 25.0 ≤ BMI < 30.0 kg/m 2 showed an 88% DFS rate in the first year, regardless of menopausal status. Furthermore, all three BMI categories displayed DFS rates exceeding 80% for 3 years, independent of menopausal status (Figs. 15 and 18). Specifically, premenopausal patients in the BMI ≥ 30 kg/m 2 category showed an 81% DFS rate over 5 years. Patients in the other two BMI categories demonstrated DFS rates of 70% and 78% over 5 years in TNM stage 3 (Fig. 15). As in the previous stages, DFS outcomes for BMI categories across menopausal status in TNM stage 3 did not yield statistically significant differences (P = 0.82 in premenopausal women and P = 0.67 in postmenopausal women). Table 4 Overall survival and Disease Survival rate for BMI categories across menopausal status in TNM stage Overall Survival times (%) Disease Survival times (%) Stage 1 1 3 5 P value* 1 3 5 P value* Pre-menopausal BMI < 25 99 99 91 0.83 97 96 92 0.31 25.0 ≤ BMI < 30.0 100 99 95 96 93 89 BMI ≥ 30 100 99 90 97 96 94 Post-menopausal BMI < 25 100 100 85 0.91 99 97 94 0.25 25.0 ≤ BMI < 30.0 100 100 91 98 97 94 BMI ≥ 30 99 98 96 96 95 90 Stage 2 Pre-menopausal BMI < 25 100 98 88 0.43 96 92 88 0.35 25.0 ≤ BMI < 30.0 100 99 93 98 93 91 BMI ≥ 30 99 99 81 96 91 88 Post-menopausal BMI < 25 100 100 85 0.81 94 91 87 0.09 25.0 ≤ BMI < 30.0 100 98 91 96 94 92 BMI ≥ 30 100 99 90 96 95 92 Stage 3 Pre-menopausal BMI < 25 100 100 100 0.05 92 82 70 0.82 25.0 ≤ BMI < 30.0 98 97 70 88 82 78 BMI ≥ 30 100 97 78 91 85 81 Post-menopausal BMI < 25 100 98 63 0.42 90 86 82 0.67 25.0 ≤ BMI < 30.0 99 98 80 88 81 80 BMI ≥ 30 100 97 79 92 87 85 * Wilcoxon (Gehan) test Discussion Obesity is a significant factor in the development of several prevalent diseases such as cardiovascular diseases, diabetes, and cancers ( 24 ). Evidence is accumulating regarding the association between obesity and the early onset, recurrence, and elevated risk of cancer-related mortality, whether in terms of susceptibility or prevention. The influence of obesity on the prognosis of breast cancer has been extensively documented in Western nations, although conflicting perspectives exist ( 25 , 26 ). To bridge this knowledge gap, we undertook a retrospective study to investigate the correlation between obesity and the prognosis of breast cancer. In our investigation, we observed a correlation between the elevated incidence of breast cancer and a high BMI, possibly attributable to metabolic and endocrine alterations ( 27 ). Obesity could accentuate estrogen production, instigate chronic subclinical inflammation, and elevate the presence of proinflammatory proteins in the bloodstream, thereby promoting cancer development ( 28 ). Furthermore, our analysis of patients across various clinicopathological groups revealed a significant association between BMI and age. Typically, patients were of advanced age with a higher representation of postmenopausal individuals. Numerous studies indicate that obese women are prone to developing aggressive forms of breast cancer when compared to women of normal weight ( 29 , 6 ). Additionally, patients with a BMI greater than or equal to 25 kg/m 2 tended to be older, with a prevalence of postmenopausal patients in the higher BMI group (BMI ≥ 25.8 kg/m 2 ) ( 30 ). Research suggests that women tend to gain weight primarily as they age ( 31 ). Following menopause, there is an escalation in the free androgen index and a decline in sex hormone-binding globulin levels, likely contributing to a gradual increase in patient BMI ( 32 ). This explanation aligns with the findings derived from our study. In congruence with a study ( 33 ) Luminal A and B subtypes are indicative of hormone receptor-positive breast cancer patients. This investigation revealed that Luminal A molecular subtype predominated as the most prevalent hormone receptor subtype across all BMI categories, while the HER2 molecular subtype exhibited the lowest incidence of hormone receptor positivity across all BMI categories. Correspondingly, Elidrissi et al. discovered that the luminal A subtype was the most frequent subtype at 65%, whereas the HER2 subtype was the least common at 6% ( 34 ). These results contrast with the findings of Sahin et al., who noted a lower prevalence of the luminal-like subtype among patients with a BMI ≥ 30 kg/m 2 ( 35 ). Moreover, Verdial et al., in their investigation at the University of Washington, found that women with luminal B tumors were more inclined to have a BMI < 25 kg/m 2 ( 36 ). The nodal status of the axilla (ALN) undoubtedly plays a crucial role in surgical decision-making and the formulation of treatment plans, exerting a significant impact on overall prognosis ( 37 ). Surgical axillary staging remains the standard method for assessing ALN status in breast cancer patients, utilizing either axillary lymph node dissection (ALND) or sentinel lymph node biopsy (SLNB) ( 38 ). Currently, SLNB has replaced ALND for the evaluation of ALN in patients presenting with clinically negative nodes ( 39 ). In our investigation, the majority of patients initially underwent ALND compared to other types of axillary procedures, which is similar to study by Zangouri et al. ( 33 ) For postmenopausal patients with a BMI ≥ 30 kg/m2, ALND and SLNB were the predominant types of axillary surgeries performed (P = 0.56). Conversely, a higher proportion of patients in the premenopausal period underwent sentinel lymph node biopsy (SLNB) alone, regardless of BMI status. Furthermore, a higher proportion of patients receiving axillary and chest radiotherapy had a BMI exceeding 25 kg/m2. Recent research has shown that lymphedema rates are elevated among patients subjected to ALND, particularly those with more advanced disease stages and higher BMIs ( 40 ). Moreover, not only are obese women at greater risk of developing post-operative lymphedema, but they also face an increased likelihood of pre-operative lymphedema ( 41 ). Numerous studies concentrate on the diagnosis and management of primary malignancies, aiming to enhance survival rates, particularly in the context of breast cancer treatment ( 42 ). For early-stage breast cancer, surgical interventions such as mastectomy or quadrantectomy are commonly recommended for local control and the prevention of disease progression. The lack of early breast cancer detection emphasizes the importance of surgical interventions in treatment strategies ( 42 ) that in the study by Zangouri et al. ( 43 ) mastectomy was performed in most of the breast cancer patients. In our recent investigation, quadrantectomy emerged as the predominant surgical approach among both pre- and post-menopausal women in three distinct groups, while mastectomy was more prevalent among postmenopausal individuals compared to their premenopausal counterparts across the three BMI categories. Noteworthy, we did not observe significant variations in the choice of surgical procedures, chemotherapy regimens, or hormone therapy across different BMI groups. This observation suggests that treatment decisions are typically guided by the Chinese Society of Clinical Oncology (CSCO) guidelines ( 44 ) and NCCN guidelines ( 21 ) for breast cancer management, regardless of the patient's BMI. Patients with varying BMIs exhibit comparable prognoses following the implementation of standardized treatment regimens. Thus, the treatment protocols outlined in the guidelines are deemed suitable for all patients irrespective of their BMI, with no significant differences in patient outcomes based on BMI following the administration of identical treatment modalities. In this investigation, it was observed that the majority of BC patients were classified as grade II, regardless of their menopausal status. This result is in the opposite line with a study reported lower proportions of grade II tumors and a higher prevalence of grade III histology ( 34 ). Tumor grade emerged as a significant factor influencing OS and DFS, corroborating findings from prior research ( 45 ). Histological grading plays a pivotal role as a robust prognostic indicator and is an essential component of various clinical decision-making tools like the Nottingham Prognostic Index and Adjuvant online ( 46 ). The histological type of the tumor was identified as an independent predictor of survival outcomes in BC patients. Multifocality, defined as the presence of two or more clearly separated tumor foci within the same breast ( 47 ), exhibited a higher prevalence among premenopausal patients compared to postmenopausal patients across three distinct BMI groups in this study. This trend aligns with existing literature indicating multifocality incidences ranging from 30–60% in women under 35 years of age and highlighting that multifocal breast carcinomas are associated with a heightened occurrence of positive lymph nodes and unfavorable patient prognoses when compared to unifocal tumors ( 46 , 48 ). A study reported the occurrence of multifocal breast tumors was more common in BC patients with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) subtypes ( 34 ). There is a scarcity of literature that directly compares the clinical and progressive characteristics of in situ breast cancer based on menopausal status. Sheikh et al. ( 49 ) conducted an analysis of breast cancer in a patient cohort divided by age, specifically comparing those aged above and below 50 years. They observed a similar prevalence of the in situ component in both groups, ranging from 9–14%. Conversely, Reinier et al. ( 50 ) identified nulliparity and advanced maternal age as risk factors for ductal carcinoma in situ (DCIS) that were more prevalent among premenopausal patients. In our research, we observed that premenopausal patients in our study exhibited in situ components across three BMI groups in varying proportions (58.9%, 58%, and 60%, respectively). While there exists debate regarding the link between obesity/overweight and the prognosis of breast cancer patients, it has been suggested that the impact of BMI on breast cancer prognosis could be influenced by menopausal status ( 51 ). In our present investigation, we did not observe a statistically significant association between BMI and DFS or OS among both premenopausal and postmenopausal breast cancer patients. Notably, in stage 3, the 3-year OS was 97% and the 5-year OS was 71% in the 25.0 ≤ BMI < 30.0 group, indicating a potentially negative impact on survival in stage 3. Conversely, in stages 1 and 2, the OS was lower in the group with BMI < 25 (87%) compared to other groups, suggesting a predictive value for breast cancer mortality. The general adverse effect of obesity on outcomes in breast cancer patients has been widely recognized and has recently been reinforced by two extensive meta-analyses ( 52 , 53 ). In the past years, an increasing body of literature has highlighted an inverse relationship between obesity and survival rates among individuals diagnosed with breast cancer ( 54 ). Adequate evidence supports the notion that elevated BMI (25.0 kg/m 2 ) is correlated with a poorer prognosis in patients with breast cancer ( 6 , 7 , 15 ). Patients exhibiting a BMI of less than 25 kg/m 2 displayed a DFS rate of 74% in stage 3, which was lower than that of the other groups. This suggests that BMI below 25 may be indicative of a poorer prognosis for disease relapse in stage 3 of breast cancer. A recent meta-analysis investigating the relationship between obesity and survival outcomes revealed that individuals with breast cancer and obesity experienced higher overall mortality (HR: 1.26, 95% CI: 1.20–1.33, P < 0.001) and inferior DFS (HR: 1.14, 95% CI: 1.10–1.19, P < 0.001) compared to those without obesity ( 55 ). Additionally, findings from a study conducted by Ladoire et al. indicated a moderate association between obesity and decreased DFS (HR: 1.18, 95% CI: 1.01–1.39, P = 0.04), predominantly affecting OS (HR: 1.38, 95% CI: 1.13–1.69, P = 0.002) based on their univariate analysis results ( 56 ). These outcomes contrast with the findings of our study. According to certain authors, postmenopausal women with a higher BMI may experience an elevated synthesis of peripheral estrogen in adipose tissue and a reduction in sex hormone binding globulin, potentially contributing to an unfavorable prognosis in breast cancer. The heightened aromatase activity resulting from these factors could promote the proliferation of abnormal mammary cells, leading to poorer outcomes ( 57 , 58 ). Furthermore, it has been suggested that postmenopausal women with higher BMI might not fully benefit from aromatase inhibitors ( 59 ). In stage 2, postmenopausal women with a BMI less than 25 kg/m 2 demonstrated a DFS rate of 87%, which was lower compared to other groups. Consequently, a BMI below 25 kg/m 2 was linked to a non-significantly higher risk of breast cancer recurrence in postmenopausal women ( 60 ). Similarly, in stage 3, postmenopausal women with a BMI ranging between 25.0 ≤ BMI < 30.0 kg/m 2 exhibited a 70% OS rate, which was lower than that of other groups. Therefore, a 25.0 ≤ BMI < 30.0 kg/m 2 was associated with a non-significantly higher risk of breast cancer-related mortality in postmenopausal women. In stage 3, premenopausal women with a BMI less than 25 kg/m 2 displayed a DFS rate of 70%, which was lower than other groups. As a result, a BMI below 25 kg/m 2 was associated with a non-significantly higher risk of breast cancer recurrence in premenopausal women. Limitations of study The study assessed BMI only in invasive ductal carcinoma and at a singular time point; however, alterations in weight and body composition over time and assessing BMI in different subtypes could exert the most significant impact on cancer outcomes. Conclusion Our observations reveal correlations between BMI, age, and the prognosis of breast cancer, suggesting that elevated BMI levels (indicative of being overweight or obese) constitute a risk factor for the prognosis of individuals diagnosed with breast cancer. It was observed that the majority of BC patients were classified as grade 2, regardless of their menopausal status. Furthermore, the majority of patients initially underwent ALND compared to other types of axillary procedures. For postmenopausal patients with a BMI ≥ 30 kg/m 2 , SLNB then ALND were the predominant types of axillary surgeries performed (P = 0.56). Conversely, a higher proportion of patients in the premenopausal period underwent SLNB alone, regardless of BMI status. The incidence of multifocal breast tumors was higher in premenopausal patients compared to postmenopausal patients in all three BMI status groups. Moreover, we did not observe a statistically significant association between BMI status and DFS or OS among both premenopausal and postmenopausal breast cancer patients. Declarations Ethical Approval and consent to participate This study conformed to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ethics Committee of Shiraz University of Medical Sciences. The study was carried out with the informed consent of all participants. All participants were fully informed of the aim and confidentiality of the study and were assured that the information provided by them would be kept confidential. Consent for publication Not applicable. Competing interests The authors declare that they have no conflict of interest. Funding This project is financially supported by the vice chancellor of research, Shiraz University of Medical Sciences. Author Contribution M. A., V. Z., S. S. B., and A. A. H. contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by R. G., E. K., S. B., S. A. M., M. A..The first draft of the manuscript was written by M. A. All authors read and approved the final manuscript. Acknowledgment: The authors would like to express their gratitude to the clinical research development unit of Imam Khomeini Hospital, Urmia University of Medical Sciences, for English editing. Data availability The original data supporting these findings are available at any time upon request to the corresponding author. References - Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast cancer—epidemiology, risk factors, classification, prognostic markers, and current treatment strategies—an updated review. Cancers. 2021;13(17):4287. - Farhood B, Geraily G, Alizadeh A. Incidence and Mortality of Various Cancers in Iran and Compare to Other Countries: A Review Article. Iran J Public Health. 2018;47(3):309–16. PMID: 29845017; PMCID: PMC5971166. - Xu Y, Gong M, Wang Y, Yang Y, Liu S, Zeng Q. Global trends and forecasts of breast cancer incidence and deaths. Sci Data. 2023;10(1):334. 10.1038/s41597-023-02253-5 . - Barrios CH. Global challenges in breast cancer detection and treatment. Breast. 2022;62(1):S3–6. 10.1016/j.breast.2022.02.003 . Epub 2022 Feb 8. - Li Z, Shen G, Shi M, Zheng Y, Guan Y, Xin Y, Wang M, Zhao F, Ren D, Zhao J. Association between high body mass index and prognosis of patients with early-stage breast cancer: A systematic review and meta-analysis. Cancer Pathog Ther. 2023;1(3):205–15. 10.1016/j.cpt.2023.03.002 . - Picon-Ruiz M, Morata-Tarifa C, Valle-Goffin JJ, Friedman ER, Slingerland JM. Obesity and adverse breast cancer risk and outcome: Mechanistic insights and strategies for intervention. CA Cancer J Clin. 2017;67(5):378–97. 10.3322/caac.21405 . - Sun L, Zhu Y, Qian Q, Tang L. Body mass index and prognosis of breast cancer: An analysis by menstruation status when breast cancer diagnosis. Medicine. 2018;97(26). - Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011–2012. JAMA. 2014;311(8):806–14. - Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, Mullany EC, Biryukov S, Abbafati C, Abera SF, Abraham JP. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980–2013: a systematic analysis for the Global Burden of Disease Study 2013. lancet. 2014;384(9945):766–81. - Fruh SM, Obesity. Risk factors, complications, and strategies for sustainable long-term weight management. J Am Assoc Nurse Pract. 2017;29(S1):S3–14. 10.1002/2327-6924.12510 . - Devericks EN, Carson MS, McCullough LE, Coleman MF, Hursting SD. The obesity-breast cancer link: a multidisciplinary perspective. Cancer Metastasis Rev. 2022;41(3):607–25. - Weir CB, Jan A. BMI Classification Percentile And Cut Off Points. [Updated 2023 Jun 26]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. https://www.ncbi.nlm.nih.gov/books/NBK541070/ . Makari-Judson G, Braun B, Jerry DJ, Mertens WC. Weight gain following breast cancer diagnosis: implication and proposed mechanisms. World J Clin Oncol. 2014;5:272–82. https://doi.org/10.5306/wjco.v5.i3.272 . - Shaikh H, Bradhurst P, Ma LX, Tan SY, Egger SJ, Vardy JL. Body weight management in overweight and obese breast cancer survivors. Cochrane Database Syst Reviews. 2020;1210.1002/14651858.CD012110.pub2. - Copson ER, Cutress RI, Maishman T, et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol. 2015;26:101–12. 10.1093/annonc/mdu509 . - Chen HL, Ding A, Wang ML. Impact of central obesity on prognostic outcome of triple negative breast cancer in Chinese women. Springerplus. 2016;5:594. 10.1186/s40064-016-2200-y . - Cihan YB. Relationship of body mass index with prognosis in breast cancer patients treated with adjuvant radiotherapy and chemotherapy. Asian Pac J Cancer Prev APJCP. 2014;15:4233–8. https://doi.org/10.7314/APJCP.2014.15.10.4233 . - Li S, Chen L, Jin W, Ma X, Ma Y, Dong F, Zhu H, Li J, Wang K. Influence of body mass index on incidence and prognosis of acute myeloid leukemia and acute promyelocytic leukemia: A meta-analysis. Sci Rep. 2017;7(1):17998. - Fontanella C, Lederer B, Gade S, Vanoppen M, Blohmer JU, Costa SD, Denkert C, Eidtmann H, Gerber B, Hanusch C, Hilfrich J, Huober J, Schneeweiss A, Paepke S, Jackisch C, Mehta K, Nekljudova V, Untch M, Neven P, von Minckwitz G, Loibl S. Impact of body mass index on neoadjuvant treatment outcome: a pooled analysis of eight prospective neoadjuvant breast cancer trials. Breast Cancer Res Treat. 2015;150(1):127–39. 10.1007/s10549-015-3287-5 . - Tan PH, Ellis I, Allison K, Brogi E, Fox SB, Lakhani S et al. The 2019 WHO classification of tumours of the breast. Histopathology. 2020. - Schmults CD, Blitzblau R, Aasi SZ, Alam M, Amini A, Bibee K, Bolotin D, Bordeaux J, Chen PL, Contreras CM, DiMaio D. NCCN Guidelines® Insights: Merkel Cell Carcinoma, Version 1.2024: Featured Updates to the NCCN Guidelines. J Natl Compr Canc Netw. 2024;22(1D). - Tang S, Zhang Q, Tang X, et al. Long-term comparisons of the efficacy, safety, and pregnancy outcomes of adjuvant tamoxifen plus ovarian function suppression in premenopausal Han and Zhuang Chinese patients with hormone receptor-positive early breast cancer. J Int Med Res. 2019;47:641–52. - Wolff AC, Hammond MEH, Hicks DG, Dowsett M, McShane LM, Allison KH, et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. Arch Pathol Lab Med. 2014;138(2):241–56. - Garg SK, Maurer H, Reed K, Selagamsetty R. Diabetes and cancer: two diseases with obesity as a common risk factor. Diabetes Obes Metab. 2014;16(2):97–110. 10.1111/dom.12124 . Epub 2013 Jun 12. - Kann S, Schmid SM, Eichholzer M, Huang DJ, Amann E, Güth U. The impact of overweight and obesity on breast cancer: data from Switzerland, so far a country little affected by the current global obesity epidemic. Gland Surg. 2014;3(3):181. - Heetun A, Cutress RI, Copson ER. Early breast cancer: why does obesity affect prognosis? Proceedings of the Nutrition Society. 2018;77(4):369 – 81. - Tan X, Huang D, Zhang F, Zhao Y, Tan M, Li H, et al. Evaluation of the body mass index in breast cancer prognosis in a cohort of small-stature overweight patients: multi-center study in China. Gland Surg. 2021;10(1):23. - Kolb R, Zhang W. Obesity and Breast Cancer: A Case of Inflamed Adipose Tissue. Cancers (Basel). 2020;12(6):1686. 10.3390/cancers12061686 . - Dehesh T, Fadaghi S, Seyedi M, Abolhadi E, Ilaghi M, Shams P, et al. The relation between obesity and breast cancer risk in women by considering menstruation status and geographical variations: a systematic review and meta-analysis. BMC Womens Health. 2023;23(1):392. 10.1186/s12905-023-02543-5 . - Kawai M, Minami Y, Nishino Y, et al. Body mass index and survival after breast cancer diagnosis in Japanese women. BMC Cancer. 2012;12:149. - Brzozowska M, Lewiński A. Changes of androgens levels in menopausal women. Prz Menopauzalny. 2020;19(4):151–4. 10.5114/pm.2020.101941 . - Brown WJ, Flores TR, Keating SE, Mielke GI. Trajectories and determinants of weight gain in two cohorts of young adult women born 16 years apart. Int J Obes. 2021;45(7):1553–64. - Zangouri V, Balaneji SS, Deylami I, Zeinalpor A, Mousavi SA, Amestejani M. Comparison of clinicopathologic characteristics and survival outcomes of various subtypes of breast cancer. BMC Cancer. - Elidrissi Errahhali M, Ouarzane M, El Harroudi T, Afqir S, Bellaoui M. First report on molecular breast cancer subtypes and their clinico-pathological characteristics in Eastern Morocco: series of 2260 cases. BMC Womens Health. 2017;17(1):3. - Sahin S, Erdem GU, Karatas F, Aytekin A, Sever AR, Ozisiket Y et al. The association between body mass index and immunohistochemical subtypes in breast cancer. Breast. 2017;32:227 – 36. 10.1016/j.breast . 2016.09.019. - Verdial FC, Javid SH, Tang MC, Peggy L, Cook LS, Li CI. Body mass index and risks of recurrence and mortality by breast cancer subtype. J Am Coll Surg. 2018; 227(4), S31. 10.1016/j. jamcollsurg. 2018.07.047. - Chen ST, Lai HW, Wu WP, Chen ST, Liao CY, Wu HK, Chen DR, Mok CW. The impact of body mass index (BMI) on MRI diagnostic performance and surgical management for axillary lymph node in breast cancer. World J Surg Oncol. 2022;20(1):45. - Pop CF, Nziki LD, El Helou E, Moreau M, Radermecker M, Larsimont D, et al. Axillary Surgical Attitude Changing with Retrospective Application of ACOSOG Z0011 Eligible Criteria: An Institutional Evaluation. Eur J Breast Health. 2023;19(4):318. 10.4274/ejbh.galenos.2023.2023-6-4 . - Galimberti V, Cole BF, Zurrida S, Viale G, Luini A, Veronesi P, et al. Axillary dissection versus no axillary dissection in patients with sentinel-node micrometastases (IBCSG 23 – 01): a phase 3 randomised controlled trial. Lancet Oncol. 2013;14:297–305. - Phelan SM, Griffin JM, Hellerstedt WL, Sayer NA, Jensen AC, Burgess DJ, Perceived stigma, strain, and mental health among caregivers of veterans with traumatic brain injury. Disabil Health J., Friedman AM, Hemler JR, Rossetti E, Clemow LP, Ferrante JM et al. Obese women’s barriers to mammography and Pap smear: the possible role of personality. Obesity. 2012;20(8):1611–7. - Iyigun ZE, Duymaz T, Ilgun AS, Alco G, Ordu C, Sarsenov D, et al. Preoperative Lymphedema-Related Risk Factors in Early-Stage Breast Cancer. Lymphat Res Biol. 2018;16(1):28–35. 10.1089/lrb.2016.0045 . - Sajikumar NR, Syamsunder S, Pinheiro C. Proportions and reasons for breast conservation surgery and modified radical mastectomy in early breast carcinoma. Int Surg J. 2019;6(7):2405–10. - Zangouri V, Nourinejad N, Balaneji SS, Hesarooeih GA, Mousavi SA, Ranjbar A, et al. Comparison of clinicopathologic characteristics and survival outcome between invasive papillary carcinoma and invasive ductal carcinoma. Pol J Surg. 2024;96(2):1–6. 10.5604/01.3001.0053.7691 . - Jiang Z, Li J, Chen J, Liu Y, Wang K, Nie J, Wang X, Hao C, Yin Y, Wang S, Yan M. Chinese society of clinical oncology (CSCO) Breast Cancer Guidelines 2022. Translational Breast Cancer Res. 2022;3. - Gong Y, Zhang J, Ji P, Houvenaeghel G, Goncalves A, Classe JM et al. Incidence proportions and prognosis of breast cancer patients with bone metastases at initial diagnosis. Cancer Med. Characteristics and clinical outcome of T1 breast cancer: a multicenter retrospective cohort study. Ann Oncol 2014;25:623-8. 10.1093/annonc/mdt532. - Neri A, Marrelli D, Megha T, Bettarini F, Tacchini D, De Franco L, Roviello F. Clinical significance of multifocal and multicentric breast cancers and choice of surgical treatment: a retrospective study on a series of 1158 cases. BMC Surg. 2015;15:1–0. - McCrorie AD, Ashfield S, Begley A, Mcilmunn C, Morrison PJ, Boyd C, Eccles B, Greville-Heygate S, Copson ER, Cutress RI, Eccles DM, Savage KI, McIntosh SA. Multifocal breast cancers are more prevalent in BRCA2 versus BRCA1 mutation carriers. J Pathol Clin Res. 2020;6(2):146–53. 10.1002/cjp2.155 . - Donker M, Straver ME, Van Tienhoven G, Van De Velde CJ, Mansel RE, Litière S, Werutsky G, et al. Comparison of the sentinel node procedure between patients with multifocal and unifocal breast cancer in the EORTC 10981–22023 AMAROS Trial: identification rate and nodal outcome. Eur J Cancer. 2013;49(9):2093–100. - Tsang JYS, Tse GM. Molecular Classification of Breast Cancer. Adv Anat Pathol. 2020;27(1):27–35. 10.1097/PAP.0000000000000232 . - Sheikh MK, Khan FA, Imran Abdul Khalid IK, Kumar G. Age specific histologic types of carcinoma breast in Malaysians. J Coll Physicians Surg Pak. 2009;19(3):201-2. PMID: 19268026. - Reinier KS, Vacek PM, Geller BM. Risk factors for breast carcinoma in situ versus invasive breast cancer in a prospective study of pre- and postmenopausal women. Breast Cancer Res Treat. 2007;103:343–8. - García-Estévez L, Cortés J, Pérez S, Calvo I, Gallegos I, Moreno-Bueno G. Obesity and breast cancer: a paradoxical and controversial relationship influenced by menopausal status. Front Oncol. 2021;11:705911. - Chan DSM, Vieira AR, Aune D, Bandera EV, Greenwood DC, McTiernan A, et al. Body mass index and survival in women with breast cancer-systematic literature review and meta-analysis of 82 follow-up studies. Ann Oncol. 2014;25:1901–14. 10.1093/annonc/mdu042 . - Protani M, Coory M, Martin JH. Effect of obesity on survival of women with breast cancer: systematic review and meta-analysis. Breast Cancer Res Treat. 2010;123:627–35. - Devericks EN, Carson MS, McCullough LE, Coleman MF, Hursting SD. The obesity-breast cancer link: a multidisciplinary perspective. Cancer Metastasis Rev. 2022;41(3):607–25. https://doi.org/10.1007/s10555-022-10043-5 . - Petrelli F, Cortellini A, Indini A, et al. Association of obesity with survival outcomes in patients with cancer: a systematic review and meta-analysis. JAMA Netw Open. 2021;4:e213520. - Ladoire S, Dalban C, Roché H, et al. Effect of obesity on disease-free and overall survival in node-positive breast cancer patients in a large French population: a pooled analysis of two randomised trials. Eur J Cancer. 2014;50(3):506–16. 10.1016/j.ejca.2013.11.013 . - Mohanty SS, Mohanty PK. Obesity as potential breast cancer risk factor for postmenopausal women. Genes Dis. 2019;8(2):117–23. 10.1016/j.gendis.2019.09.006 . - Mair KM, Gaw R, MacLean MR. Obesity, estrogens and adipose tissue dysfunction–implications for pulmonary arterial hypertension. Pulmonary circulation. 2020;10(3):2045894020952019. - Pfeiler G, Königsberg R, Hadji P, Fitzal F, Maroske M, Dressel-Ban G, et al. Impact of body mass index on estradiol depletion by aromatase inhibitors in postmenopausal women with early breast cancer. Br J Cancer. 2013;109(6):1522–7. 10.1038/bjc.2013.499 . - Quartuccio N, Ialuna S, Pulizzi S, D'Oppido D, Antoni M, Moreci AM. The Correlation of Body Mass Index with Risk of Recurrence in Post-Menopausal Women with Breast Cancer Undergoing Fluorodeoxyglucose Positron Emission Tomography/Computed Tomograph. J Clin Med. 2024;13(6):1575. https://doi.org/10.3390/jcm13061575 . - Prado CM, Gonzalez MC, Heymsfield SB. Body composition phenotypes and obesity paradox. Curr Opin Clin Nutr Metab Care. 2015;18:535–51. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Published Journal Publication published 13 Feb, 2025 Read the published version in BMC Cancer → Version 1 posted Editorial decision: Revision requested 07 May, 2024 Submission checks completed at journal 07 May, 2024 Editor assigned by journal 07 May, 2024 First submitted to journal 06 May, 2024 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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Sciences","correspondingAuthor":false,"prefix":"","firstName":"Souzan","middleName":"Soufizadeh","lastName":"Balaneji","suffix":""},{"id":299973129,"identity":"a7df72fc-ed37-4e1f-b63f-31e32e7ef086","order_by":2,"name":"Roya Golmoradi","email":"","orcid":"","institution":"Shiraz University of Medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Roya","middleName":"","lastName":"Golmoradi","suffix":""},{"id":299973131,"identity":"ac6b14bd-b461-43be-860b-625146018f42","order_by":3,"name":"Ehsan Kafili","email":"","orcid":"","institution":"Shiraz University of Medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Ehsan","middleName":"","lastName":"Kafili","suffix":""},{"id":299973133,"identity":"fd9319ab-ac9b-46c2-940d-49227d28e9e9","order_by":4,"name":"Saleh Bologhi","email":"","orcid":"","institution":"Shiraz University of Medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Saleh","middleName":"","lastName":"Bologhi","suffix":""},{"id":299973136,"identity":"d4c5d5e1-64f2-48bf-bd7d-52036f7ddf8b","order_by":5,"name":"Seyed Amin Mousavi","email":"","orcid":"","institution":"Shiraz University of Medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Seyed","middleName":"Amin","lastName":"Mousavi","suffix":""},{"id":299973138,"identity":"f81c35cd-a30f-453e-b799-1e003b692862","order_by":6,"name":"Ataollah Ahmadi Hesar","email":"","orcid":"","institution":"Shiraz University of Medical sciences","correspondingAuthor":false,"prefix":"","firstName":"Ataollah","middleName":"Ahmadi","lastName":"Hesar","suffix":""},{"id":299973140,"identity":"0731ae74-a6fe-4bbe-994d-04eb9aecbdeb","order_by":7,"name":"Morteza Amestejani","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA80lEQVRIiWNgGAWjYDADxgYGhgMfgAw2duI0GIC1HJwB0sJMrBYQYOYBkwTU6jYwP93w4c8fOeb2swcP2/zaJs/HzMD44WMObi1mB9jMbs5sMzBm7MlLOJzbd9uwjZmBWXLmNnxaGMxu8zYYJDY25Bgczu25zQjUwsbMi1cL+7fbf/4Y1Df2vzE4bNlz254ILTxmtxnYDBIYZwBtYfhxO5GwlsM8ZTd724wNG2e8MTjY23A7uY2ZsRm/X463b7vx44+cvGF/jvGHH39u285vbz744SMeLfBYMGwAEoxtICYoVokB8mDyD3GKR8EoGAWjYGQBAL8yVTJdguRoAAAAAElFTkSuQmCC","orcid":"","institution":"Urmia University of Medical Sciences","correspondingAuthor":true,"prefix":"","firstName":"Morteza","middleName":"","lastName":"Amestejani","suffix":""}],"badges":[],"createdAt":"2024-05-06 10:44:39","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4376201/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4376201/v1","draftVersion":[],"editorialEvents":[{"content":"https://doi.org/10.1186/s12885-025-13638-7","type":"published","date":"2025-02-13T15:58:07+00:00"}],"editorialNote":"","failedWorkflow":false,"files":[{"id":56549712,"identity":"86e6c9b0-24a6-4aa5-8322-e25fdb39150f","added_by":"auto","created_at":"2024-05-15 15:47:21","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":19230,"visible":true,"origin":"","legend":"\u003cp\u003eOS times-based patient’s BMI status among \u0026nbsp;patients in premenopausal period in Stage 1\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/3aa14b9f904e9a16e382dbd3.png"},{"id":56549707,"identity":"6f7da43e-e3bc-4924-9ca8-39fcf732e272","added_by":"auto","created_at":"2024-05-15 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\u0026nbsp;in post-menopausal period in stage2\u003c/p\u003e","description":"","filename":"5.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/cc6da489535576a228adbe31.png"},{"id":56549711,"identity":"d0d9d6a4-40d8-4b6b-961d-199695be5067","added_by":"auto","created_at":"2024-05-15 15:47:21","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":17087,"visible":true,"origin":"","legend":"\u003cp\u003eOS times-based patient’s BMI status among patients \u0026nbsp;in post-menopausal period in stage3\u003c/p\u003e","description":"","filename":"6.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/00d53eaf9a452c069c9e9817.png"},{"id":56549710,"identity":"3a27fc3c-901e-4325-8695-4dc513854472","added_by":"auto","created_at":"2024-05-15 15:47:20","extension":"png","order_by":7,"title":"Figure 7","display":"","copyAsset":false,"role":"figure","size":16414,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times-based patient’s BMI status among \u0026nbsp;patients in premenopausal period in Stage 1\u003c/p\u003e","description":"","filename":"7.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/3d80ccd6103f0a24c28c3ce8.png"},{"id":56549714,"identity":"386a94ff-8db5-40d5-a140-af526c163300","added_by":"auto","created_at":"2024-05-15 15:47:21","extension":"png","order_by":8,"title":"Figure 8","display":"","copyAsset":false,"role":"figure","size":20087,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times-based patient’s BMI status among \u0026nbsp;patients in premenopausal period in stage2\u003c/p\u003e","description":"","filename":"8.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/a9201c0d976e5d4bec898900.png"},{"id":56549717,"identity":"103e30c2-cad9-48f1-b0d1-69fb35bcae06","added_by":"auto","created_at":"2024-05-15 15:47:21","extension":"png","order_by":9,"title":"Figure 9","display":"","copyAsset":false,"role":"figure","size":16663,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times-based patient’s BMI status among patients in premenopausal period in stage3\u003c/p\u003e","description":"","filename":"9.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/f34c725c6cc1719f5053214e.png"},{"id":56550824,"identity":"01d65c5e-b87f-4695-976d-02625395cd35","added_by":"auto","created_at":"2024-05-15 15:55:20","extension":"png","order_by":10,"title":"Figure 10","display":"","copyAsset":false,"role":"figure","size":15560,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times-based patient’s BMI status among patients in post-menopausal period in Stage 1\u003c/p\u003e","description":"","filename":"10.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/785aa5680458f068464a1b2b.png"},{"id":56550825,"identity":"698a5fe7-420e-4a22-9b91-194f73739a90","added_by":"auto","created_at":"2024-05-15 15:55:21","extension":"png","order_by":11,"title":"Figure 11","display":"","copyAsset":false,"role":"figure","size":19034,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times-based patient’s BMI status among patients \u0026nbsp;in post-menopausal period in stage2\u003c/p\u003e","description":"","filename":"11.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/ea0a720c625f16ae10e97ed2.png"},{"id":56549718,"identity":"03e445e3-b876-45a0-b4d0-f0a56777621d","added_by":"auto","created_at":"2024-05-15 15:47:21","extension":"png","order_by":12,"title":"Figure 12","display":"","copyAsset":false,"role":"figure","size":15825,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times-based patient’s BMI status among patients \u0026nbsp;in post-menopausal period in stage3\u003c/p\u003e","description":"","filename":"12.png","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/364b153dde8e713839981a4b.png"},{"id":76487718,"identity":"1e5ab0e1-7150-4108-94bf-6db535e790cc","added_by":"auto","created_at":"2025-02-17 16:11:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1374120,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4376201/v1/7ddef2f3-6527-4597-960b-781c682d40d2.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Effects of BMI on prognosis , disease-free survival and overall survival of breast cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer (BC) stands as the most prevalent malignant tumor and ranks among the primary contributors to cancer-related fatalities in women (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e). Over the last decade, there has been a gradual rise in the global incidence of BC (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e). Thanks to advancements in early detection and the enhancement of treatment modalities, the outlook for breast cancer sufferers has significantly improved (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e). Various factors impacting the prognosis of BC comprise axillary lymph nodes, primary tumor size, the utilization of adjuvant systemic treatments, tumor-infiltrating lymphocytes, estrogen receptor, human epidermal growth factor receptor-2 (HER-2), age, menopausal status, ethnicity, alcohol consumption, and smoking habits (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e). Research shows that excess body fat increases the risk for several cancers (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Additionally, there is now a widespread consensus on the adverse prognostic implications of obesity or overweight for breast cancer beyond its role as a risk factor (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eCurrently, obesity has reached epidemic proportions, with 69% of adults in the United States and 38% globally falling into the overweight or obese category (\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e). Obesity is linked to changes in overall body physiology and hormonal balance that contribute to various health conditions like diabetes and cardiovascular diseases (\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e). Moreover, obesity is correlated with an elevated likelihood of developing several types of cancer and with reduced survival rates for individuals diagnosed with those cancers (\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e). The National Institute of Health (NIH) categorizes body mass index (BMI) as follows: underweight\u0026thinsp;\u0026lt;\u0026thinsp;18.5 kg/m\u003csup\u003e2\u003c/sup\u003e, normal weight 18.5 to \u0026lt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e, overweight 25.0 to \u0026lt;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e, and obesity\u0026thinsp;\u0026ge;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e (\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e). Around 75% of women in the United States and 50% in Europe are overweight or obese at the time of breast cancer diagnosis, and treatments for breast cancer frequently lead to additional weight gain (\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e). A high BMI is linked to poorer clinical outcomes in patients with early-stage breast cancer (EBC) (\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe precise biological mechanisms behind the relationship between adiposity and breast cancer (BC) survival are not fully understood, but they may involve the interplay of hormones, adipocytokines, and inflammatory cytokines, which play roles in cell survival, apoptosis, migration, and proliferation (\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e). Numerous studies have explored the connection between obesity and BC outcomes (\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e). Li et al. found that a high BMI significantly impacts overall survival (OS) but does not significantly affect disease-free survival (DFS) (\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e). Conversely, Fontanella et al. demonstrated that obese patients have significantly shorter average DFS and OS compared to patients with a healthy weight (\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e). Most research investigating the correlation between breast cancer and BMI has focused on Western populations. However, the mechanistic understanding of the association between obesity/overweight and the risk of breast cancer recurrence and mortality among Asian women, based on menopausal status, is limited. Given that Asian women typically have lower BMIs than Western women, this study aimed to examine the varying effects of BMI on prognostic factors, OS, and DFS in BC patients with Invasive Ductal Carcinoma subtypes.\u003c/p\u003e"},{"header":"Methods","content":"\u003cp\u003e The study was conducted under the Declaration of Helsinki and with approval from the Ethics Committee of Shiraz Medical Science University.\u003c/p\u003e \u003cp\u003eThis retrospective cohort study analyzed the medical records of breast cancer patients who sought treatment at Namazi hospital in Shiraz, Iran between 2014 and 2019. These data were studied in 2024. All cases included in the study displayed tumor characteristics that align with the morphological guidelines specified in the World Health Organization (WHO) histological classification of breast tumors (\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e). The selection criteria for patients were centered on the verification of primary breast cancer through histological analysis after curative surgical procedures, as well as the patient being over 18 years of age. Individuals under 18.5 kg/m2, diagnosed with stage IV breast cancer recently, those lacking complete pathological or postoperative treatment data, and patients who were lost to follow-up were excluded from the study.\u003c/p\u003e \u003cp\u003eWeight and height data were documented at the time of the initial diagnosis, and BMI was computed by dividing the weight in kilograms by the square of the height in meters. BMI was categorized according to WHO standard: normal weight, BMI\u0026thinsp;\u0026lt;\u0026thinsp;25.0 kg/m2; overweight, 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2; and obesity, BMI\u0026thinsp;\u0026ge;\u0026thinsp;30.0kg/m2. Three groups were divided according to BMI when breast cancer diagnosis: normal weight group, overweight group, and obesity group. Furthermore, a stratified analysis about relationship between BMI and prognosis of breast cancer was conducted in line with menopausal status when breast cancer diagnosed. Menopausal status was defined by 1 year of amenorrhea, or previous bilateral oophorectomy and post-menopause refers to the final stage of the menopause process, and marks the end of the reproductive stage of life (\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eAll participants in the study underwent regular monitoring following surgery, chemotherapy, radiation therapy, and hormonal treatment. This follow-up was conducted every 3\u0026ndash;6 months within the first two years after surgery, every 6 months over the subsequent 5 years, and annually thereafter with imaging under guide of National Comprehensive Cancer Network (NCCN) (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e). All occurrences were meticulously documented in the database.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePathology Analysis\u003c/h2\u003e \u003cp\u003eImmunohistochemical (IHC) staining was utilized to evaluate the levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu) in adherence to a standardized protocol established by the Pathology Department at Shiraz University of Medical Sciences. A confirmed case of HER2neu-amplified breast cancer was used as a positive control for HER2neu. A sample is considered ER negative if\u0026thinsp;\u0026lt;\u0026thinsp;1% or 0%, tumors demonstrating 1% or more positive nuclear staining for ER or PR were categorized as ER-positive or PR-positive, respectively. In cases where intermediate (2+) immunohistochemical expression of HER2neu was observed, subsequent testing using fluorescent in situ hybridization (FISH) was conducted to assess HER2neu gene amplification. The breast tumors were stratified into four subtypes based on ER, PR, and HER2neu expression: luminal A (ER-positive and/or PR-positive, HER2neu-negative), luminal B (ER-positive and/or PR-positive, HER2neu-positive), HER2neu+ (ER-negative and PR-negative, HER2-positive), and triple-negative (TN) (ER-negative, PR-negative, and HER2neu-negative), following the criteria delineated by Carey (\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eOverall survival (OS) was defined as the period from the initial diagnosis of breast cancer until either death from any cause or the last recorded follow-up visit. Disease-free survival (DFS) was calculated as the duration from the date of surgery to the occurrence of the first metastasis or recurrence (\u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e). The TNM staging system for breast cancer was assessed according to the guidelines outlined in the seventh edition of the American Joint Committee on Cancer (AJCC).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003eStatistical analysis\u003c/h2\u003e \u003cp\u003eThe normality of the distribution of continuous variables was tested using a one-sample Kolmogorov-Smirnov test. Continuous variables with a normal distribution were presented as mean (SD), while non-normal variables were reported as frequency (percentage). The means of two continuous normally distributed variables were compared using independent samples Student\u0026rsquo;s T-test. When appropriate, frequencies of categorical variables were compared using Pearson Chi-square or Fisher\u0026rsquo;s exact test. Overall survival (OS) and disease-free survival (DFS) were evaluated using the Kaplan-Meier analysis. Analyses were performed using SPSS statistical software (version 25), and a P-value of \u0026lt;\u0026thinsp;0.05 was considered statistically significant.\u003c/p\u003e \u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displays a comparative analysis of patients based on their body mass index (BMI) status. Among the 7134 breast cancer patients studied, 2026 (28.31%) had a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m2, 3045 (42.6%) fell within the range of 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2, and 2063 (29.1%) had a BMI of 30 kg/m2 or higher. The mean age at diagnosis was similar across the three BMI groups, but there was a tendency for older patients to be more prevalent in the obese group (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05).\u003c/p\u003e \u003cp\u003ePremenopausal patients were more likely to have a lower BMI compared to postmenopausal patients, with almost half of the obese patients being in the postmenopausal period (58.9%). Menopausal status was significantly associated with BMI status (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). The majority of patients were classified as grade 2 and stage 2 across the BMI categories (P\u0026thinsp;=\u0026thinsp;0.12, P\u0026thinsp;=\u0026thinsp;0.08, respectively).\u003c/p\u003e \u003cp\u003eThe Luminal A molecular subtype was the most prevalent hormone receptor subtype across all BMI categories, while the Her2 molecular subtype positive was the least common hormone receptor subtype across all BMI categories (P\u0026thinsp;=\u0026thinsp;0.14). The rate of patients undergoing axillary lymph node dissection (ALND) initially was higher compared to other Axillary Types across all BMI categories (P\u0026thinsp;=\u0026thinsp;0.82). Hormone therapy was equally distributed among these three groups (P\u0026thinsp;=\u0026thinsp;0.26). In all three groups, over 80% of patients did not receive preoperative chemotherapy (P\u0026thinsp;=\u0026thinsp;0.02); however, postoperative chemotherapy was administered to over 80% of patients in all three groups (P\u0026thinsp;=\u0026thinsp;0.14).\u003c/p\u003e \u003cp\u003eThe highest proportion of patients undergoing axillary and chest radiotherapy had a BMI higher than 25 kg/m\u003csup\u003e2\u003c/sup\u003e, while this proportion was lower in patients with a BMI below 25 kg/m\u003csup\u003e2\u003c/sup\u003e (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\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\u003eComparative analysis of patient characteristics across body mass index (kg/m\u003csup\u003e2\u003c/sup\u003e) status of studied patients.\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=\"char\" char=\".\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"2\" morerows=\"1\" nameend=\"c2\" namest=\"c1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c5\" namest=\"c3\"\u003e \u003cp\u003eBMI group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2026)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 (n\u0026thinsp;=\u0026thinsp;3045)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003cp\u003e(n\u0026thinsp;=\u0026thinsp;2063)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eAge at diagnosis,(Mean\u0026thinsp;\u0026plusmn;\u0026thinsp;SD) (year)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e47.50\u0026thinsp;\u0026plusmn;\u0026thinsp;12.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e48.64\u0026thinsp;\u0026plusmn;\u0026thinsp;11.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e50.13\u0026thinsp;\u0026plusmn;\u0026thinsp;10.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP\u0026thinsp;\u0026gt;\u0026thinsp;0.05\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003eMenopausal status Premenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1107 (54.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1510 (49.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e846 (41.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"2\" nameend=\"c2\" namest=\"c1\"\u003e \u003cp\u003ePostmenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e919(55.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1550 (50.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1217 (58.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePathology Tumor Grade\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e363 (19.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e498 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e336 (17.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.12\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\u003e1137 (60.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1739 (61.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1145 (59.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e370 (19.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e571 (20.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e432 (22.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eAxillary Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eALND at first\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e916 (45.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1357 (44.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e924 (44.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSLNB only\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e787 (38.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1230 (40.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e823 (39.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eSLNB then ALND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323 (15.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e458 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e316 (15.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e403 (32.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e582 (29.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e380 (28.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.08\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\u003e730 (58.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1172 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e820 (60.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e107 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e195 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e149 (11.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003ePreoperative Chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1674 (81.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2574 (83.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1765 (84.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e391 (18.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e515 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e336 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003epostoperative Chemotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e309 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e416 (13.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e272 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1756 (85.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2673 (86.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1829 (87.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eAxillary and Chest Radiotherapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e541 (26.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e700 (22.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e442 (21.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eyes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1524 (73.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2389 (77.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1659 (79.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eHormone therapy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e495 (24.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e725 (23.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e534 (25.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1570 (76.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e2364 (76.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1567 (74.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003eHormone receptor\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLuminal A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1089(53.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1726 (56.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1223 (59.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c6\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.14\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eLuminal B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e435 (21.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e682 (22.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e389 (18.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHer2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e210 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e304 (10%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e223(10.8%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e292(14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e333 (10.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e228(11%)\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e presents a comparative analysis of patient characteristics and menopausal status based on the BMI (kg/m2) status of the patients under study. Quadrantectomy (BCS) emerged as the most common type of surgery among both pre- and post-menopausal women in all three groups. Mastectomy was more prevalent among postmenopausal patients than premenopausal patients in all three groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 and 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e, P\u0026thinsp;=\u0026thinsp;0.6 for patients with BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e). Regardless of menopausal status, the majority of patients were classified as grade II based on BMI. Furthermore, stage 3 was more frequently observed in postmenopausal patients across all three groups (P\u0026thinsp;=\u0026thinsp;0.16, P\u0026thinsp;=\u0026thinsp;0.17, P\u0026thinsp;=\u0026thinsp;0.51, respectively).\u003c/p\u003e \u003cp\u003eThe incidence of multifocal breast tumors was higher in premenopausal patients compared to postmenopausal patients in all three BMI status groups. A statistically significant association was found between the presence of multifocal breast tumors and menopausal status across the three BMI status groups (P\u0026thinsp;=\u0026thinsp;0.004, \u0026lt;\u0026thinsp;0.001, and 0.01, respectively).\u003c/p\u003e \u003cp\u003eA statistical examination of tumor grading across three defined categories indicated that the majority of premenopausal patients in all three groups were classified as grade II, regardless of BMI status. Conversely, postmenopausal in all three groups were predominantly classified as grade II. Notably, Grade III Permanent Pathology Tumors were more prevalent in premenopausal women compared to postmenopausal women in all three groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;=\u0026thinsp;0.01, and P\u0026thinsp;=\u0026thinsp;0.01, respectively).\u003c/p\u003e \u003cp\u003eWhile the majority of patients did not exhibit tumor invasion across the three BMI categories, premenopausal patients displayed a higher prevalence of non-invasive tumors compared to postmenopausal patients. A statistically significant relationship was observed between the occurrence of various types of invasion and menopausal status in the studied population with a 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2 (P\u0026thinsp;=\u0026thinsp;0.03). Vascular invasion was more frequently observed in postmenopausal patients across all three BMI categories. Both Vascular and Preneural invasion, as well as Lymphatic and Vascular invasion, displayed similar distributions based on menopausal status in all three BMI categories. Furthermore, a statistically significant correlation was noted between the occurrence of different invasion types and tumor subtypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eAxillary lymph node dissection (ALND) was the most common type of axillary surgery performed in postmenopausal patients within the BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m2 and 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2 groups. For postmenopausal patients with a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e, ALND then SLNB were the predominant types of axillary surgeries performed (P\u0026thinsp;=\u0026thinsp;0.56). Conversely, a higher proportion of patients in the premenopausal period underwent SLNB alone, regardless of BMI status. A statistically significant correlation was identified between the type of axillary surgery and menopausal status within the studied population with a BMI of 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2 (P\u0026thinsp;=\u0026thinsp;0.002).\u003c/p\u003e \u003cp\u003eThe Luminal A hormone receptor subtype was prevalent among all breast cancer patients, irrespective of menopausal or BMI status, while Luminal B was more commonly found in premenopausal patients compared to postmenopausal patients across all three BMI groups. A statistically significant variance was noted in the distribution of hormone receptor subtypes based on menopausal status within the three BMI groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 for patients with BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m2 and BMI 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2, and P\u0026thinsp;=\u0026thinsp;0.007 for patients with BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e, respectively).\u003c/p\u003e \u003cp\u003eHormone therapy was provided to the majority of patients in all three groups regardless of menopausal status, with postmenopausal women receiving hormone therapy more frequently than premenopausal women across all BMI groups. A statistically significant relationship was found between hormone therapy and menopausal status in patients with a higher BMI of \u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e (P\u0026thinsp;=\u0026thinsp;0.006).\u003c/p\u003e \u003cp\u003eRadiotherapy was administered to a significant percentage of patients in all three BMI groups, with a higher prevalence among postmenopausal patients in all three groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 in all groups). Postoperative chemotherapy was utilized in a considerable number of patients across all three groups, but it was more common among premenopausal patients in all three BMI groups (P\u0026thinsp;=\u0026thinsp;0.01, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;=\u0026thinsp;0.01 in the three groups, respectively). Preoperative chemotherapy was not a common treatment regardless of the patients' BMI status. Preoperative chemotherapy was more frequently administered to premenopausal patients in all three BMI groups (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001 in patients with BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m2 and BMI 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2, and P\u0026thinsp;=\u0026thinsp;0.01 in patients with BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e, respectively).\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\u003ecomparative analysis of patient characteristics and menopausal status according body mass index (kg/m2 ) status of studied patients.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003cp\u003emenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003cp\u003emenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003cp\u003emenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003cp\u003emenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003ePvalue\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003ePre\u003c/p\u003e \u003cp\u003emenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003ePost\u003c/p\u003e \u003cp\u003emenopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP-value\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMean age (SD)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e47.57(8.27)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e66.12(9.36)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e49.31(7.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e65.29(8.855)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e50.62(7.56)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e64.67(8.28)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"4\" nameend=\"c4\" namest=\"c1\"\u003e \u003cp\u003eSurgery Type\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c7\" namest=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c10\" namest=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001*\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuadrantectomy (BCS)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e664(57.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e436 (49.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e991 (61.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e849 (58.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e585 (61.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e718 (62.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eMastectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e417 (36.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e417 (46.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e508 (31.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e553 (37.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e304 (31.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e374 (32.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eQuadrantectomy (BCS) ,then Mastectomy\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e69 (6.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e28 (3.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e111 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e49 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e111 (6.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e49 (3.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eStage\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e242 (33.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e158 (31.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e313 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e267 (30.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.17\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e192 (29.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e184 (26.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e427 (59.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e288 (57.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e655 (61.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e503 (58.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e392 (60.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e420 (61.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e53 (7.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e52 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96 (11.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68 (10.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80 (11.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003ePermanent Pathology Multifocal\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1049 (91.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e833 (94.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.004\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1479 (91.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1387 (95.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e867 (91.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1070 (94.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e101 (8.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e48 (5.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e867 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1070 (4.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82 (8.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e67 (5.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003ePermanent Pathology Tumor Grade\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e174 (16.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e184 (23.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e232 (15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e255 (19.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e149 (17.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e185 (17.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e638 (61.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e480 (60.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e921 (62.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e806 (61.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e491 (57.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e645 (62.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e228 (21.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e134 (16.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e321 (21.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e246 (18.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e222 (25.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e207 (20.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eInvasion\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNon\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e587) 51.0%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e414)47.0%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e756(47%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e626(43.2)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.03\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e439(46.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e499(43.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"4\" rowspan=\"5\"\u003e \u003cp\u003e0.3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eVascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e271)23.6%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e217)24.6%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e392 (24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e406 (28.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e239 (25.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e315 (27.7%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003ePreneural\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e75)6.5%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e76) 8.6%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e120 (7.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e68 (7.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoth of them\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e178)15.5%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e155) 17.6%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e290(18.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e278 (19.2%\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e170 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e217 (19.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLymphatic, Vascular\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e39) 3.4%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e19)2.2%(\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e52 (3.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e30 (2.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e33 (3.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e26 (2.3%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAxillary Type\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eALND at first\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e488 (42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e403 (47.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e660 (41.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e678 (47.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.002\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e381(40.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e442(39.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.56\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLNB\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e458 (40.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e323 (38.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e682 (42.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e543 (38.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e151 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e162 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eSLNB then ALND\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e197 (17.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e123 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e255 (16.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e198 (14.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e409 (43.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e503 (45.4%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHormone receptor\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminal A\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e564 (49.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e406 (46.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e772 (48.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e717 (49.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e449 (47.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e579 (50.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"3\" rowspan=\"4\"\u003e \u003cp\u003e0.007\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eLuminal B\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e211 (18.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e129 (14.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e288 (17.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e187 (12.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e142 (15.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e149 (13.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eHer2\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e80 (7.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e71 (8.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e143 (8.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e135 (9.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e102 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e81 (7.1%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTriple Negative\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e130 (11.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e88 (10.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e172 (10.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e110 (7.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e106 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e113 (9.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePreoperative Chemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e892 (77.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e753 (85.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1300 (80.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1248 (86.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e776 (81.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e976 (85.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e258 (22.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e128 (14.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e310 (19.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e202 (13.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e173 (18.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e161 (14.2%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003ePostoperative Chemotherapy\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e154 (13.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e152 (17.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e185 (11.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e228 (15.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e106 (11.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e164 (14.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e996 (86.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e729 (82.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1425 (88.5%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1222 (84.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e843 (88.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e973 (85.6%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eRadiotherapy postoperative\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e324 (36.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e204 (17.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e410 (28.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e280 (17.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e272 (23.9%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e162 (17.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e557 (63.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e946 (82.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1040 (71.7%0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1330 (82.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e865 (76.1%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e787 (82.9%)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eHormone therapy\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e278(24.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e211(24.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e392(24.3%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e328(22.6%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.26\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e268(28.2%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e261(23.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e0.006\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e872(75.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e670(76.0%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1218(75.7%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1122(77.4%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e681(71.8%)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e876(77.0%)\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\u003eTable\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e presents a summary of the 1-, 3-, and 5-year OS and DFS outcomes for different BMI categories across TNM stages. In stages 1 and 2, all three BMI groups showed OS rates above 99% at 1 and 3 years. Moreover, patients across all BMI categories in stages 1 and 2 exhibited OS rates exceeding 87% at 5 years (Figs.\u0026nbsp;1 and 2). The OS rates for BMI categories in TNM stages 1 and 2 did not show any statistically significant differences (P\u0026thinsp;=\u0026thinsp;0.34 in TNM stage 1 and P\u0026thinsp;=\u0026thinsp;0.98 in TNM stage 2).\u003c/p\u003e \u003cp\u003eMoving on to stage 3, all three BMI groups demonstrated OS rates surpassing 97% at 1 and 3 years among the studied patients. For patients in TNM stage 3, the OS rates were above 71% at 5 years (see Fig.\u0026nbsp;3). The OS outcomes for BMI categories in TNM stage 3 did not show statistically significant discrepancies (P\u0026thinsp;=\u0026thinsp;0.33).\u003c/p\u003e \u003cp\u003eIn stages 1 and 2, all three BMI groups displayed DFS rates exceeding 95% at 1 year. Additionally, the DFS rates were higher than 95% at 3 years for patients in TNM stages 1 and 2. Patients in TNM stages 1 and 2 showcased DFS rates above 81% at 5 years (Figs.\u0026nbsp;4 and 5). The DFS outcomes for BMI categories in TNM stages 1 and 2 did not demonstrate any statistically significant variances (P\u0026thinsp;=\u0026thinsp;0.77 in TNM stage 1 and P\u0026thinsp;=\u0026thinsp;0.11 in TNM stage 2).\u003c/p\u003e \u003cp\u003eMoving to stage 3, the three BMI groups exhibited DFS rates of 92%, 88%, and 92% at 1 year, respectively. These patients also displayed DFS rates ranging from 81\u0026ndash;86% at 3 years (Fig.\u0026nbsp;6). The DFS rates were between 74\u0026ndash;84% at 5 years. The DFS rates for BMI categories in TNM stage 3 did not show any statistically significant differences (P\u0026thinsp;=\u0026thinsp;0.57).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003esummarizes the 1-, 3-, and 5-year OS and DFS outcomes for BMI categories across TNM stage.\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c5\" namest=\"c2\"\u003e \u003cp\u003eOverall Survival times (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"4\" nameend=\"c9\" namest=\"c6\"\u003e \u003cp\u003eDisease Survival times (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eP value*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eP value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eStage1\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.34\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.77\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eStage2\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.11\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"9\" nameend=\"c9\" namest=\"c1\"\u003e \u003cp\u003eStage3\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.57\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e77\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e84\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003e* Wilcoxon (Gehan) test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab4\" class=\"InternalRef\"\u003e4\u003c/span\u003e provides a summary of the 1-, 3-, and 5-year OS and DFS outcomes for various BMI categories based on menopausal status in different TNM stages.\u003c/p\u003e \u003cp\u003eIn stage 1, all three BMI groups showed OS rates above 99% at 1 and 3 years in premenopausal patients (Fig.\u0026nbsp;7). For post-menopausal patients, those with BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e and BMI 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e categories displayed exceptional 100% OS rates at 1 and 3 years. Additionally, post-menopausal patients with BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e exhibited OS rates of 99% and 98% at 1 and 3 years, respectively (Fig.\u0026nbsp;10). Irrespective of menopausal status, all patients across all BMI categories demonstrated OS rates of \u0026ge;\u0026thinsp;85% at 5 years in TNM stage 1 (Figs.\u0026nbsp;7 and 10). The OS outcomes for BMI categories based on menopausal status in stage 1 did not show any statistically significant differences (P\u0026thinsp;=\u0026thinsp;0.83 in premenopausal and P\u0026thinsp;=\u0026thinsp;0.91 in postmenopausal women).\u003c/p\u003e \u003cp\u003eMoving to stage 2, patients in all BMI categories, regardless of menopausal status, exhibited OS rates above 98% for 1, 3, and 5 years. Notably, postmenopausal patients with BMI less than 25 kg/m\u003csup\u003e2\u003c/sup\u003e exhibited OS rates of 85% at 5 years (Figs.\u0026nbsp;8 and 11). The OS outcomes for BMI categories based on menopausal status in stage 2 did not reveal any statistically significant variations (P\u0026thinsp;=\u0026thinsp;0.43 in premenopausal women and P\u0026thinsp;=\u0026thinsp;0.81 in postmenopausal women).\u003c/p\u003e \u003cp\u003eIn TNM stage 3, premenopausal patients categorized as BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 displayed exceptional 100% OS rates over 1, 3, and 5 years. Patients in the other two BMI categories in the premenopausal group showed OS rates exceeding 97% at 1 and 3 years of follow-up. Moreover, premenopausal patients in the remaining two BMI categories demonstrated OS rates of 70% and 78% at the 5-year mark in stage 3 (Fig.\u0026nbsp;9). During this stage, all three BMI groups exhibited OS rates surpassing 97% at 1 and 3 years in post-menopausal patients. Post-menopausal patients in the BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 category showed a 63% OS rate at the 5-year mark. Additionally, post-menopausal patients in the other two BMI categories displayed OS rates of 80% and 79% at 5 years in stage 3, respectively (Fig.\u0026nbsp;12). The OS outcomes for BMI categories based on menopausal status in stage 2 did not yield statistically significant differences (P\u0026thinsp;=\u0026thinsp;0.05 in premenopausal and P\u0026thinsp;=\u0026thinsp;0.42 in postmenopausal women).\u003c/p\u003e \u003cp\u003eIn stage 1, all three BMI groups exhibited DFS rates of 89% or higher for 1, 3, and 5 years, irrespective of menopausal status (Figs.\u0026nbsp;1 and 10). The DFS outcomes for BMI categories across menopausal status in TNM stage 1 did not show statistically significant differences (P\u0026thinsp;=\u0026thinsp;0.31 in premenopausal women and P\u0026thinsp;=\u0026thinsp;0.25 in postmenopausal women).\u003c/p\u003e \u003cp\u003eMoving to stage 2, all three BMI groups demonstrated DFS rates exceeding 90% for 1 and 3 years, regardless of menopausal status (Figs.\u0026nbsp;14 and 17). Premenopausal patients with a BMI between 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m2 exhibited a 91% DFS rate over 5 years. Patients in the other two BMI categories achieved an 88% DFS rate over 5 years (Fig.\u0026nbsp;8). Postmenopausal patients with BMI between 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 and BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 categories showed 92% DFS rates over 5 years, while patients with a BMI\u0026thinsp;\u0026gt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e had an 87% DFS rate over the same period (Fig.\u0026nbsp;17). Similar to stage 1, DFS outcomes for BMI categories across menopausal status in TNM stage 2 were not statistically significant (P\u0026thinsp;=\u0026thinsp;0.35 in premenopausal women and P\u0026thinsp;=\u0026thinsp;0.25 in postmenopausal women).\u003c/p\u003e \u003cp\u003eIn stage 3, patients across all BMI categories, irrespective of menopausal status, exhibited DFS rates higher than 90% for 1 year. Notably, patients with a BMI of 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e showed an 88% DFS rate in the first year, regardless of menopausal status. Furthermore, all three BMI categories displayed DFS rates exceeding 80% for 3 years, independent of menopausal status (Figs.\u0026nbsp;15 and 18). Specifically, premenopausal patients in the BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e category showed an 81% DFS rate over 5 years. Patients in the other two BMI categories demonstrated DFS rates of 70% and 78% over 5 years in TNM stage 3 (Fig.\u0026nbsp;15). As in the previous stages, DFS outcomes for BMI categories across menopausal status in TNM stage 3 did not yield statistically significant differences (P\u0026thinsp;=\u0026thinsp;0.82 in premenopausal women and P\u0026thinsp;=\u0026thinsp;0.67 in postmenopausal women).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab4\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 4\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eOverall survival and Disease Survival rate for BMI categories across menopausal status in TNM stage\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"10\"\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 \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c10\" colnum=\"10\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c5\" namest=\"c1\"\u003e \u003cp\u003eOverall Survival times (%)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"5\" nameend=\"c10\" namest=\"c6\"\u003e \u003cp\u003eDisease Survival times (%)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003eStage 1\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eP value*\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003e5\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c10\"\u003e \u003cp\u003eP value*\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePre-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.83\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.31\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePost-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.25\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage 2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePre-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.43\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.35\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e93\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePost-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.09\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e94\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e96\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e95\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"10\" nameend=\"c10\" namest=\"c1\"\u003e \u003cp\u003e\u003cb\u003eStage 3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePre-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.82\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e70\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e78\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e91\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003ePost-menopausal\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e63\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e90\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e86\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c10\" morerows=\"2\" rowspan=\"3\"\u003e \u003cp\u003e0.67\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e99\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e98\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e88\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e81\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e80\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;30\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e100\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e79\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e92\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e87\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e85\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"10\"\u003e* Wilcoxon (Gehan) test\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eObesity is a significant factor in the development of several prevalent diseases such as cardiovascular diseases, diabetes, and cancers (\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e). Evidence is accumulating regarding the association between obesity and the early onset, recurrence, and elevated risk of cancer-related mortality, whether in terms of susceptibility or prevention. The influence of obesity on the prognosis of breast cancer has been extensively documented in Western nations, although conflicting perspectives exist (\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e). To bridge this knowledge gap, we undertook a retrospective study to investigate the correlation between obesity and the prognosis of breast cancer.\u003c/p\u003e \u003cp\u003eIn our investigation, we observed a correlation between the elevated incidence of breast cancer and a high BMI, possibly attributable to metabolic and endocrine alterations (\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e). Obesity could accentuate estrogen production, instigate chronic subclinical inflammation, and elevate the presence of proinflammatory proteins in the bloodstream, thereby promoting cancer development (\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e). Furthermore, our analysis of patients across various clinicopathological groups revealed a significant association between BMI and age. Typically, patients were of advanced age with a higher representation of postmenopausal individuals. Numerous studies indicate that obese women are prone to developing aggressive forms of breast cancer when compared to women of normal weight (\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e). Additionally, patients with a BMI greater than or equal to 25 kg/m\u003csup\u003e2\u003c/sup\u003e tended to be older, with a prevalence of postmenopausal patients in the higher BMI group (BMI\u0026thinsp;\u0026ge;\u0026thinsp;25.8 kg/m\u003csup\u003e2\u003c/sup\u003e) (\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e). Research suggests that women tend to gain weight primarily as they age (\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e). Following menopause, there is an escalation in the free androgen index and a decline in sex hormone-binding globulin levels, likely contributing to a gradual increase in patient BMI (\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e). This explanation aligns with the findings derived from our study.\u003c/p\u003e \u003cp\u003eIn congruence with a study (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) Luminal A and B subtypes are indicative of hormone receptor-positive breast cancer patients. This investigation revealed that Luminal A molecular subtype predominated as the most prevalent hormone receptor subtype across all BMI categories, while the HER2 molecular subtype exhibited the lowest incidence of hormone receptor positivity across all BMI categories. Correspondingly, Elidrissi et al. discovered that the luminal A subtype was the most frequent subtype at 65%, whereas the HER2 subtype was the least common at 6% (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). These results contrast with the findings of Sahin et al., who noted a lower prevalence of the luminal-like subtype among patients with a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e (\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e). Moreover, Verdial et al., in their investigation at the University of Washington, found that women with luminal B tumors were more inclined to have a BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 kg/m\u003csup\u003e2\u003c/sup\u003e (\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe nodal status of the axilla (ALN) undoubtedly plays a crucial role in surgical decision-making and the formulation of treatment plans, exerting a significant impact on overall prognosis (\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e). Surgical axillary staging remains the standard method for assessing ALN status in breast cancer patients, utilizing either axillary lymph node dissection (ALND) or sentinel lymph node biopsy (SLNB) (\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e). Currently, SLNB has replaced ALND for the evaluation of ALN in patients presenting with clinically negative nodes (\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e). In our investigation, the majority of patients initially underwent ALND compared to other types of axillary procedures, which is similar to study by Zangouri et al. (\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e) For postmenopausal patients with a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m2, ALND and SLNB were the predominant types of axillary surgeries performed (P\u0026thinsp;=\u0026thinsp;0.56). Conversely, a higher proportion of patients in the premenopausal period underwent sentinel lymph node biopsy (SLNB) alone, regardless of BMI status. Furthermore, a higher proportion of patients receiving axillary and chest radiotherapy had a BMI exceeding 25 kg/m2. Recent research has shown that lymphedema rates are elevated among patients subjected to ALND, particularly those with more advanced disease stages and higher BMIs (\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e). Moreover, not only are obese women at greater risk of developing post-operative lymphedema, but they also face an increased likelihood of pre-operative lymphedema (\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eNumerous studies concentrate on the diagnosis and management of primary malignancies, aiming to enhance survival rates, particularly in the context of breast cancer treatment (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e). For early-stage breast cancer, surgical interventions such as mastectomy or quadrantectomy are commonly recommended for local control and the prevention of disease progression. The lack of early breast cancer detection emphasizes the importance of surgical interventions in treatment strategies (\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e) that in the study by Zangouri et al. (\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e) mastectomy was performed in most of the breast cancer patients. In our recent investigation, quadrantectomy emerged as the predominant surgical approach among both pre- and post-menopausal women in three distinct groups, while mastectomy was more prevalent among postmenopausal individuals compared to their premenopausal counterparts across the three BMI categories. Noteworthy, we did not observe significant variations in the choice of surgical procedures, chemotherapy regimens, or hormone therapy across different BMI groups. This observation suggests that treatment decisions are typically guided by the Chinese Society of Clinical Oncology (CSCO) guidelines (\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e) and NCCN guidelines (\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) for breast cancer management, regardless of the patient's BMI. Patients with varying BMIs exhibit comparable prognoses following the implementation of standardized treatment regimens. Thus, the treatment protocols outlined in the guidelines are deemed suitable for all patients irrespective of their BMI, with no significant differences in patient outcomes based on BMI following the administration of identical treatment modalities.\u003c/p\u003e \u003cp\u003eIn this investigation, it was observed that the majority of BC patients were classified as grade II, regardless of their menopausal status. This result is in the opposite line with a study reported lower proportions of grade II tumors and a higher prevalence of grade III histology (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e). Tumor grade emerged as a significant factor influencing OS and DFS, corroborating findings from prior research (\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e). Histological grading plays a pivotal role as a robust prognostic indicator and is an essential component of various clinical decision-making tools like the Nottingham Prognostic Index and Adjuvant online (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThe histological type of the tumor was identified as an independent predictor of survival outcomes in BC patients. Multifocality, defined as the presence of two or more clearly separated tumor foci within the same breast (\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e47\u003c/span\u003e), exhibited a higher prevalence among premenopausal patients compared to postmenopausal patients across three distinct BMI groups in this study. This trend aligns with existing literature indicating multifocality incidences ranging from 30\u0026ndash;60% in women under 35 years of age and highlighting that multifocal breast carcinomas are associated with a heightened occurrence of positive lymph nodes and unfavorable patient prognoses when compared to unifocal tumors (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e, \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e48\u003c/span\u003e). A study reported the occurrence of multifocal breast tumors was more common in BC patients with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) subtypes (\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e).\u003c/p\u003e \u003cp\u003eThere is a scarcity of literature that directly compares the clinical and progressive characteristics of in situ breast cancer based on menopausal status. Sheikh et al. (\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e49\u003c/span\u003e) conducted an analysis of breast cancer in a patient cohort divided by age, specifically comparing those aged above and below 50 years. They observed a similar prevalence of the in situ component in both groups, ranging from 9\u0026ndash;14%. Conversely, Reinier et al. (\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e50\u003c/span\u003e) identified nulliparity and advanced maternal age as risk factors for ductal carcinoma in situ (DCIS) that were more prevalent among premenopausal patients. In our research, we observed that premenopausal patients in our study exhibited in situ components across three BMI groups in varying proportions (58.9%, 58%, and 60%, respectively).\u003c/p\u003e \u003cp\u003eWhile there exists debate regarding the link between obesity/overweight and the prognosis of breast cancer patients, it has been suggested that the impact of BMI on breast cancer prognosis could be influenced by menopausal status (\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e51\u003c/span\u003e). In our present investigation, we did not observe a statistically significant association between BMI and DFS or OS among both premenopausal and postmenopausal breast cancer patients. Notably, in stage 3, the 3-year OS was 97% and the 5-year OS was 71% in the 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 group, indicating a potentially negative impact on survival in stage 3. Conversely, in stages 1 and 2, the OS was lower in the group with BMI\u0026thinsp;\u0026lt;\u0026thinsp;25 (87%) compared to other groups, suggesting a predictive value for breast cancer mortality. The general adverse effect of obesity on outcomes in breast cancer patients has been widely recognized and has recently been reinforced by two extensive meta-analyses (\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e53\u003c/span\u003e). In the past years, an increasing body of literature has highlighted an inverse relationship between obesity and survival rates among individuals diagnosed with breast cancer (\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e54\u003c/span\u003e). Adequate evidence supports the notion that elevated BMI (25.0 kg/m\u003csup\u003e2\u003c/sup\u003e) is correlated with a poorer prognosis in patients with breast cancer (\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e).\u003c/p\u003e \u003cp\u003ePatients exhibiting a BMI of less than 25 kg/m\u003csup\u003e2\u003c/sup\u003e displayed a DFS rate of 74% in stage 3, which was lower than that of the other groups. This suggests that BMI below 25 may be indicative of a poorer prognosis for disease relapse in stage 3 of breast cancer. A recent meta-analysis investigating the relationship between obesity and survival outcomes revealed that individuals with breast cancer and obesity experienced higher overall mortality (HR: 1.26, 95% CI: 1.20\u0026ndash;1.33, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and inferior DFS (HR: 1.14, 95% CI: 1.10\u0026ndash;1.19, P\u0026thinsp;\u0026lt;\u0026thinsp;0.001) compared to those without obesity (\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e55\u003c/span\u003e). Additionally, findings from a study conducted by Ladoire et al. indicated a moderate association between obesity and decreased DFS (HR: 1.18, 95% CI: 1.01\u0026ndash;1.39, P\u0026thinsp;=\u0026thinsp;0.04), predominantly affecting OS (HR: 1.38, 95% CI: 1.13\u0026ndash;1.69, P\u0026thinsp;=\u0026thinsp;0.002) based on their univariate analysis results (\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e56\u003c/span\u003e). These outcomes contrast with the findings of our study.\u003c/p\u003e \u003cp\u003eAccording to certain authors, postmenopausal women with a higher BMI may experience an elevated synthesis of peripheral estrogen in adipose tissue and a reduction in sex hormone binding globulin, potentially contributing to an unfavorable prognosis in breast cancer. The heightened aromatase activity resulting from these factors could promote the proliferation of abnormal mammary cells, leading to poorer outcomes (\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e57\u003c/span\u003e, \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e58\u003c/span\u003e). Furthermore, it has been suggested that postmenopausal women with higher BMI might not fully benefit from aromatase inhibitors (\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e59\u003c/span\u003e). In stage 2, postmenopausal women with a BMI less than 25 kg/m\u003csup\u003e2\u003c/sup\u003e demonstrated a DFS rate of 87%, which was lower compared to other groups. Consequently, a BMI below 25 kg/m\u003csup\u003e2\u003c/sup\u003e was linked to a non-significantly higher risk of breast cancer recurrence in postmenopausal women (\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e60\u003c/span\u003e). Similarly, in stage 3, postmenopausal women with a BMI ranging between 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e exhibited a 70% OS rate, which was lower than that of other groups. Therefore, a 25.0\u0026thinsp;\u0026le;\u0026thinsp;BMI\u0026thinsp;\u0026lt;\u0026thinsp;30.0 kg/m\u003csup\u003e2\u003c/sup\u003e was associated with a non-significantly higher risk of breast cancer-related mortality in postmenopausal women. In stage 3, premenopausal women with a BMI less than 25 kg/m\u003csup\u003e2\u003c/sup\u003e displayed a DFS rate of 70%, which was lower than other groups. As a result, a BMI below 25 kg/m\u003csup\u003e2\u003c/sup\u003e was associated with a non-significantly higher risk of breast cancer recurrence in premenopausal women.\u003c/p\u003e"},{"header":"Limitations of study","content":"\u003cp\u003eThe study assessed BMI only in invasive ductal carcinoma and at a singular time point; however, alterations in weight and body composition over time and assessing BMI in different subtypes could exert the most significant impact on cancer outcomes.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eOur observations reveal correlations between BMI, age, and the prognosis of breast cancer, suggesting that elevated BMI levels (indicative of being overweight or obese) constitute a risk factor for the prognosis of individuals diagnosed with breast cancer. It was observed that the majority of BC patients were classified as grade 2, regardless of their menopausal status. Furthermore, the majority of patients initially underwent ALND compared to other types of axillary procedures. For postmenopausal patients with a BMI\u0026thinsp;\u0026ge;\u0026thinsp;30 kg/m\u003csup\u003e2\u003c/sup\u003e, SLNB then ALND were the predominant types of axillary surgeries performed (P\u0026thinsp;=\u0026thinsp;0.56). Conversely, a higher proportion of patients in the premenopausal period underwent SLNB alone, regardless of BMI status. The incidence of multifocal breast tumors was higher in premenopausal patients compared to postmenopausal patients in all three BMI status groups. Moreover, we did not observe a statistically significant association between BMI status and DFS or OS among both premenopausal and postmenopausal breast cancer patients.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003ch2\u003eEthical Approval and consent to participate\u003c/h2\u003e \u003cp\u003e This study conformed to the ethical guidelines of the 1975 Declaration of Helsinki and was approved by the Ethics Committee of Shiraz University of Medical Sciences. The study was carried out with the informed consent of all participants. All participants were fully informed of the aim and confidentiality of the study and were assured that the information provided by them would be kept confidential.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis project is financially supported by the vice chancellor of research, Shiraz University of Medical Sciences.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eM. A., V. Z., S. S. B., and A. A. H. contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by R. G., E. K., S. B., S. A. M., M. A..The first draft of the manuscript was written by M. A. All authors read and approved the final manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgment:\u003c/h2\u003e \u003cp\u003eThe authors would like to express their gratitude to the clinical research development unit of Imam Khomeini Hospital, Urmia University of Medical Sciences, for English editing.\u003c/p\u003e\u003ch2\u003eData availability\u003c/h2\u003e \u003cp\u003eThe original data supporting these findings are available at any time upon request to the corresponding author.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003e- Łukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. Breast cancer\u0026mdash;epidemiology, risk factors, classification, prognostic markers, and current treatment strategies\u0026mdash;an updated review. Cancers. 2021;13(17):4287.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Farhood B, Geraily G, Alizadeh A. Incidence and Mortality of Various Cancers in Iran and Compare to Other Countries: A Review Article. Iran J Public Health. 2018;47(3):309\u0026ndash;16. PMID: 29845017; PMCID: PMC5971166.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Xu Y, Gong M, Wang Y, Yang Y, Liu S, Zeng Q. Global trends and forecasts of breast cancer incidence and deaths. Sci Data. 2023;10(1):334. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/s41597-023-02253-5\u003c/span\u003e\u003cspan address=\"10.1038/s41597-023-02253-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Barrios CH. Global challenges in breast cancer detection and treatment. Breast. 2022;62(1):S3\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.breast.2022.02.003\u003c/span\u003e\u003cspan address=\"10.1016/j.breast.2022.02.003\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2022 Feb 8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Li Z, Shen G, Shi M, Zheng Y, Guan Y, Xin Y, Wang M, Zhao F, Ren D, Zhao J. Association between high body mass index and prognosis of patients with early-stage breast cancer: A systematic review and meta-analysis. Cancer Pathog Ther. 2023;1(3):205\u0026ndash;15. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.cpt.2023.03.002\u003c/span\u003e\u003cspan address=\"10.1016/j.cpt.2023.03.002\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Picon-Ruiz M, Morata-Tarifa C, Valle-Goffin JJ, Friedman ER, Slingerland JM. Obesity and adverse breast cancer risk and outcome: Mechanistic insights and strategies for intervention. CA Cancer J Clin. 2017;67(5):378\u0026ndash;97. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3322/caac.21405\u003c/span\u003e\u003cspan address=\"10.3322/caac.21405\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Sun L, Zhu Y, Qian Q, Tang L. Body mass index and prognosis of breast cancer: An analysis by menstruation status when breast cancer diagnosis. Medicine. 2018;97(26).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Ogden CL, Carroll MD, Kit BK, Flegal KM. Prevalence of childhood and adult obesity in the United States, 2011\u0026ndash;2012. JAMA. 2014;311(8):806\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono C, Mullany EC, Biryukov S, Abbafati C, Abera SF, Abraham JP. Global, regional, and national prevalence of overweight and obesity in children and adults during 1980\u0026ndash;2013: a systematic analysis for the Global Burden of Disease Study 2013. lancet. 2014;384(9945):766\u0026ndash;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Fruh SM, Obesity. Risk factors, complications, and strategies for sustainable long-term weight management. J Am Assoc Nurse Pract. 2017;29(S1):S3\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/2327-6924.12510\u003c/span\u003e\u003cspan address=\"10.1002/2327-6924.12510\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Devericks EN, Carson MS, McCullough LE, Coleman MF, Hursting SD. The obesity-breast cancer link: a multidisciplinary perspective. Cancer Metastasis Rev. 2022;41(3):607\u0026ndash;25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Weir CB, Jan A. BMI Classification Percentile And Cut Off Points. [Updated 2023 Jun 26]. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2024 Jan-. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK541070/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK541070/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMakari-Judson G, Braun B, Jerry DJ, Mertens WC. Weight gain following breast cancer diagnosis: implication and proposed mechanisms. World J Clin Oncol. 2014;5:272\u0026ndash;82. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.5306/wjco.v5.i3.272\u003c/span\u003e\u003cspan address=\"10.5306/wjco.v5.i3.272\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Shaikh H, Bradhurst P, Ma LX, Tan SY, Egger SJ, Vardy JL. Body weight management in overweight and obese breast cancer survivors. Cochrane Database Syst Reviews. 2020;1210.1002/14651858.CD012110.pub2.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Copson ER, Cutress RI, Maishman T, et al. Obesity and the outcome of young breast cancer patients in the UK: the POSH study. Ann Oncol. 2015;26:101\u0026ndash;12. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/annonc/mdu509\u003c/span\u003e\u003cspan address=\"10.1093/annonc/mdu509\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Chen HL, Ding A, Wang ML. Impact of central obesity on prognostic outcome of triple negative breast cancer in Chinese women. Springerplus. 2016;5:594. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s40064-016-2200-y\u003c/span\u003e\u003cspan address=\"10.1186/s40064-016-2200-y\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Cihan YB. Relationship of body mass index with prognosis in breast cancer patients treated with adjuvant radiotherapy and chemotherapy. Asian Pac J Cancer Prev APJCP. 2014;15:4233\u0026ndash;8. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.7314/APJCP.2014.15.10.4233\u003c/span\u003e\u003cspan address=\"10.7314/APJCP.2014.15.10.4233\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Li S, Chen L, Jin W, Ma X, Ma Y, Dong F, Zhu H, Li J, Wang K. Influence of body mass index on incidence and prognosis of acute myeloid leukemia and acute promyelocytic leukemia: A meta-analysis. Sci Rep. 2017;7(1):17998.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Fontanella C, Lederer B, Gade S, Vanoppen M, Blohmer JU, Costa SD, Denkert C, Eidtmann H, Gerber B, Hanusch C, Hilfrich J, Huober J, Schneeweiss A, Paepke S, Jackisch C, Mehta K, Nekljudova V, Untch M, Neven P, von Minckwitz G, Loibl S. Impact of body mass index on neoadjuvant treatment outcome: a pooled analysis of eight prospective neoadjuvant breast cancer trials. Breast Cancer Res Treat. 2015;150(1):127\u0026ndash;39. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1007/s10549-015-3287-5\u003c/span\u003e\u003cspan address=\"10.1007/s10549-015-3287-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tan PH, Ellis I, Allison K, Brogi E, Fox SB, Lakhani S et al. The 2019 WHO classification of tumours of the breast. Histopathology. 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Schmults CD, Blitzblau R, Aasi SZ, Alam M, Amini A, Bibee K, Bolotin D, Bordeaux J, Chen PL, Contreras CM, DiMaio D. NCCN Guidelines\u0026reg; Insights: Merkel Cell Carcinoma, Version 1.2024: Featured Updates to the NCCN Guidelines. J Natl Compr Canc Netw. 2024;22(1D).\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tang S, Zhang Q, Tang X, et al. Long-term comparisons of the efficacy, safety, and pregnancy outcomes of adjuvant tamoxifen plus ovarian function suppression in premenopausal Han and Zhuang Chinese patients with hormone receptor-positive early breast cancer. J Int Med Res. 2019;47:641\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Wolff AC, Hammond MEH, Hicks DG, Dowsett M, McShane LM, Allison KH, et al. Recommendations for human epidermal growth factor receptor 2 testing in breast cancer: American Society of Clinical Oncology/College of American Pathologists clinical practice guideline update. Arch Pathol Lab Med. 2014;138(2):241\u0026ndash;56.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Garg SK, Maurer H, Reed K, Selagamsetty R. Diabetes and cancer: two diseases with obesity as a common risk factor. Diabetes Obes Metab. 2014;16(2):97\u0026ndash;110. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1111/dom.12124\u003c/span\u003e\u003cspan address=\"10.1111/dom.12124\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Epub 2013 Jun 12.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Kann S, Schmid SM, Eichholzer M, Huang DJ, Amann E, G\u0026uuml;th U. The impact of overweight and obesity on breast cancer: data from Switzerland, so far a country little affected by the current global obesity epidemic. Gland Surg. 2014;3(3):181.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Heetun A, Cutress RI, Copson ER. Early breast cancer: why does obesity affect prognosis? Proceedings of the Nutrition Society. 2018;77(4):369\u0026thinsp;\u0026ndash;\u0026thinsp;81.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tan X, Huang D, Zhang F, Zhao Y, Tan M, Li H, et al. Evaluation of the body mass index in breast cancer prognosis in a cohort of small-stature overweight patients: multi-center study in China. Gland Surg. 2021;10(1):23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Kolb R, Zhang W. Obesity and Breast Cancer: A Case of Inflamed Adipose Tissue. Cancers (Basel). 2020;12(6):1686. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.3390/cancers12061686\u003c/span\u003e\u003cspan address=\"10.3390/cancers12061686\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Dehesh T, Fadaghi S, Seyedi M, Abolhadi E, Ilaghi M, Shams P, et al. The relation between obesity and breast cancer risk in women by considering menstruation status and geographical variations: a systematic review and meta-analysis. BMC Womens Health. 2023;23(1):392. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1186/s12905-023-02543-5\u003c/span\u003e\u003cspan address=\"10.1186/s12905-023-02543-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Kawai M, Minami Y, Nishino Y, et al. Body mass index and survival after breast cancer diagnosis in Japanese women. BMC Cancer. 2012;12:149.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Brzozowska M, Lewiński A. Changes of androgens levels in menopausal women. Prz Menopauzalny. 2020;19(4):151\u0026ndash;4. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5114/pm.2020.101941\u003c/span\u003e\u003cspan address=\"10.5114/pm.2020.101941\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Brown WJ, Flores TR, Keating SE, Mielke GI. Trajectories and determinants of weight gain in two cohorts of young adult women born 16 years apart. Int J Obes. 2021;45(7):1553\u0026ndash;64.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Zangouri V, Balaneji SS, Deylami I, Zeinalpor A, Mousavi SA, Amestejani M. Comparison of clinicopathologic characteristics and survival outcomes of various subtypes of breast cancer. BMC Cancer.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Elidrissi Errahhali M, Ouarzane M, El Harroudi T, Afqir S, Bellaoui M. First report on molecular breast cancer subtypes and their clinico-pathological characteristics in Eastern Morocco: series of 2260 cases. BMC Womens Health. 2017;17(1):3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Sahin S, Erdem GU, Karatas F, Aytekin A, Sever AR, Ozisiket Y et al. The association between body mass index and immunohistochemical subtypes in breast cancer. \u003cem\u003eBreast.\u003c/em\u003e 2017;32:227\u0026thinsp;\u0026ndash;\u0026thinsp;36. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.breast\u003c/span\u003e\u003cspan address=\"10.1016/j.breast\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. 2016.09.019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Verdial FC, Javid SH, Tang MC, Peggy L, Cook LS, Li CI. Body mass index and risks of recurrence and mortality by breast cancer subtype. \u003cem\u003eJ Am Coll Surg.\u003c/em\u003e 2018; 227(4), S31. 10.1016/j. jamcollsurg. 2018.07.047.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Chen ST, Lai HW, Wu WP, Chen ST, Liao CY, Wu HK, Chen DR, Mok CW. The impact of body mass index (BMI) on MRI diagnostic performance and surgical management for axillary lymph node in breast cancer. World J Surg Oncol. 2022;20(1):45.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Pop CF, Nziki LD, El Helou E, Moreau M, Radermecker M, Larsimont D, et al. Axillary Surgical Attitude Changing with Retrospective Application of ACOSOG Z0011 Eligible Criteria: An Institutional Evaluation. Eur J Breast Health. 2023;19(4):318. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.4274/ejbh.galenos.2023.2023-6-4\u003c/span\u003e\u003cspan address=\"10.4274/ejbh.galenos.2023.2023-6-4\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Galimberti V, Cole BF, Zurrida S, Viale G, Luini A, Veronesi P, et al. Axillary dissection versus no axillary dissection in patients with sentinel-node micrometastases (IBCSG 23\u0026thinsp;\u0026ndash;\u0026thinsp;01): a phase 3 randomised controlled trial. Lancet Oncol. 2013;14:297\u0026ndash;305.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Phelan SM, Griffin JM, Hellerstedt WL, Sayer NA, Jensen AC, Burgess DJ, Perceived stigma, strain, and mental health among caregivers of veterans with traumatic brain injury. Disabil Health J., Friedman AM, Hemler JR, Rossetti E, Clemow LP, Ferrante JM et al. Obese women\u0026rsquo;s barriers to mammography and Pap smear: the possible role of personality. Obesity. 2012;20(8):1611\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Iyigun ZE, Duymaz T, Ilgun AS, Alco G, Ordu C, Sarsenov D, et al. Preoperative Lymphedema-Related Risk Factors in Early-Stage Breast Cancer. Lymphat Res Biol. 2018;16(1):28\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1089/lrb.2016.0045\u003c/span\u003e\u003cspan address=\"10.1089/lrb.2016.0045\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Sajikumar NR, Syamsunder S, Pinheiro C. Proportions and reasons for breast conservation surgery and modified radical mastectomy in early breast carcinoma. Int Surg J. 2019;6(7):2405\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Zangouri V, Nourinejad N, Balaneji SS, Hesarooeih GA, Mousavi SA, Ranjbar A, et al. Comparison of clinicopathologic characteristics and survival outcome between invasive papillary carcinoma and invasive ductal carcinoma. Pol J Surg. 2024;96(2):1\u0026ndash;6. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.5604/01.3001.0053.7691\u003c/span\u003e\u003cspan address=\"10.5604/01.3001.0053.7691\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Jiang Z, Li J, Chen J, Liu Y, Wang K, Nie J, Wang X, Hao C, Yin Y, Wang S, Yan M. Chinese society of clinical oncology (CSCO) Breast Cancer Guidelines 2022. Translational Breast Cancer Res. 2022;3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Gong Y, Zhang J, Ji P, Houvenaeghel G, Goncalves A, Classe JM et al. Incidence proportions and prognosis of breast cancer patients with bone metastases at initial diagnosis. Cancer Med. Characteristics and clinical outcome of T1 breast cancer: a multicenter retrospective cohort study. Ann Oncol 2014;25:623-8. 10.1093/annonc/mdt532.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Neri A, Marrelli D, Megha T, Bettarini F, Tacchini D, De Franco L, Roviello F. Clinical significance of multifocal and multicentric breast cancers and choice of surgical treatment: a retrospective study on a series of 1158 cases. BMC Surg. 2015;15:1\u0026ndash;0.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- McCrorie AD, Ashfield S, Begley A, Mcilmunn C, Morrison PJ, Boyd C, Eccles B, Greville-Heygate S, Copson ER, Cutress RI, Eccles DM, Savage KI, McIntosh SA. Multifocal breast cancers are more prevalent in BRCA2 versus BRCA1 mutation carriers. J Pathol Clin Res. 2020;6(2):146\u0026ndash;53. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1002/cjp2.155\u003c/span\u003e\u003cspan address=\"10.1002/cjp2.155\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Donker M, Straver ME, Van Tienhoven G, Van De Velde CJ, Mansel RE, Liti\u0026egrave;re S, Werutsky G, et al. Comparison of the sentinel node procedure between patients with multifocal and unifocal breast cancer in the EORTC 10981\u0026ndash;22023 AMAROS Trial: identification rate and nodal outcome. Eur J Cancer. 2013;49(9):2093\u0026ndash;100.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Tsang JYS, Tse GM. Molecular Classification of Breast Cancer. Adv Anat Pathol. 2020;27(1):27\u0026ndash;35. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1097/PAP.0000000000000232\u003c/span\u003e\u003cspan address=\"10.1097/PAP.0000000000000232\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Sheikh MK, Khan FA, Imran Abdul Khalid IK, Kumar G. Age specific histologic types of carcinoma breast in Malaysians. J Coll Physicians Surg Pak. 2009;19(3):201-2. PMID: 19268026.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Reinier KS, Vacek PM, Geller BM. Risk factors for breast carcinoma in situ versus invasive breast cancer in a prospective study of pre- and postmenopausal women. Breast Cancer Res Treat. 2007;103:343\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Garc\u0026iacute;a-Est\u0026eacute;vez L, Cort\u0026eacute;s J, P\u0026eacute;rez S, Calvo I, Gallegos I, Moreno-Bueno G. Obesity and breast cancer: a paradoxical and controversial relationship influenced by menopausal status. Front Oncol. 2021;11:705911.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Chan DSM, Vieira AR, Aune D, Bandera EV, Greenwood DC, McTiernan A, et al. Body mass index and survival in women with breast cancer-systematic literature review and meta-analysis of 82 follow-up studies. Ann Oncol. 2014;25:1901\u0026ndash;14. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1093/annonc/mdu042\u003c/span\u003e\u003cspan address=\"10.1093/annonc/mdu042\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Protani M, Coory M, Martin JH. Effect of obesity on survival of women with breast cancer: systematic review and meta-analysis. Breast Cancer Res Treat. 2010;123:627\u0026ndash;35.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Devericks EN, Carson MS, McCullough LE, Coleman MF, Hursting SD. The obesity-breast cancer link: a multidisciplinary perspective. Cancer Metastasis Rev. 2022;41(3):607\u0026ndash;25. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s10555-022-10043-5\u003c/span\u003e\u003cspan address=\"10.1007/s10555-022-10043-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Petrelli F, Cortellini A, Indini A, et al. Association of obesity with survival outcomes in patients with cancer: a systematic review and meta-analysis. JAMA Netw Open. 2021;4:e213520.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Ladoire S, Dalban C, Roch\u0026eacute; H, et al. Effect of obesity on disease-free and overall survival in node-positive breast cancer patients in a large French population: a pooled analysis of two randomised trials. Eur J Cancer. 2014;50(3):506\u0026ndash;16. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.ejca.2013.11.013\u003c/span\u003e\u003cspan address=\"10.1016/j.ejca.2013.11.013\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Mohanty SS, Mohanty PK. Obesity as potential breast cancer risk factor for postmenopausal women. Genes Dis. 2019;8(2):117\u0026ndash;23. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1016/j.gendis.2019.09.006\u003c/span\u003e\u003cspan address=\"10.1016/j.gendis.2019.09.006\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Mair KM, Gaw R, MacLean MR. Obesity, estrogens and adipose tissue dysfunction\u0026ndash;implications for pulmonary arterial hypertension. Pulmonary circulation. 2020;10(3):2045894020952019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Pfeiler G, K\u0026ouml;nigsberg R, Hadji P, Fitzal F, Maroske M, Dressel-Ban G, et al. Impact of body mass index on estradiol depletion by aromatase inhibitors in postmenopausal women with early breast cancer. Br J Cancer. 2013;109(6):1522\u0026ndash;7. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1038/bjc.2013.499\u003c/span\u003e\u003cspan address=\"10.1038/bjc.2013.499\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Quartuccio N, Ialuna S, Pulizzi S, D'Oppido D, Antoni M, Moreci AM. The Correlation of Body Mass Index with Risk of Recurrence in Post-Menopausal Women with Breast Cancer Undergoing Fluorodeoxyglucose Positron Emission Tomography/Computed Tomograph. J Clin Med. 2024;13(6):1575. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.3390/jcm13061575\u003c/span\u003e\u003cspan address=\"10.3390/jcm13061575\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003e- Prado CM, Gonzalez MC, Heymsfield SB. Body composition phenotypes and obesity paradox. Curr Opin Clin Nutr Metab Care. 2015;18:535\u0026ndash;51.\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":true,"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":"","lastPublishedDoi":"10.21203/rs.3.rs-4376201/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4376201/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eObese breast cancer patients have worse prognosis than normal weight patients, but the level at which obesity is prognostically unfavorable is unclear. This study aimed to investigate different effects of Body Mass Index (BMI) on prognosis disease-free survival and overall survivor of breast cancer patients.\u003c/p\u003e\u003ch2\u003eMethod\u003c/h2\u003e \u003cp\u003eThis retrospective cohort study analyzed the medical records of breast cancer patients who sought treatment at Namazi hospital in Shiraz, Iran between 2014 and 2019. Three groups of patients were divided according to BMI. Menopausal status, BMI status, clinicopathological characteristics, treatment, and overall survival (OS), and disease free survival (DFS) were comprehensively evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 7134 breast cancer patients, the majority (42.6%) were in 25\u0026ndash;30 kg/m\u003csup\u003e2\u003c/sup\u003e. Menopausal status significantly were associated with obesity (P \u0026lt;0 .001). The majority of patients were categorized as grade 2 and stage 2 according to the BMI categories (P\u0026thinsp;=\u0026thinsp;0.12, P\u0026thinsp;=\u0026thinsp;0.08, respectively). BMI categories regardless of menopausal status displayed increased 1, 3, and 5-year DFS and 5- year OS in stage 1 and increased 1, 3, and 5-year OS and 1 and 3-year DFS in stage 2. In stage 3, the risks of relapse and death were significantly decreased in all three groups of BMI patients with post-menopausal period.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eObesity leads to worse DFS and OS in patients with BC and the effects of obesity on the breast cancer prognosis seem to be clinically related to menopausal status. Once validated, these results should be considered in the development of prevention programs.\u003c/p\u003e","manuscriptTitle":"Effects of BMI on prognosis , disease-free survival and overall survival of breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-05-15 15:47:14","doi":"10.21203/rs.3.rs-4376201/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2024-05-08T03:39:46+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2024-05-07T12:55:35+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2024-05-07T12:55:35+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2024-05-06T10:43:17+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":"562c8506-5766-4177-ab5f-bc1d56d0f20c","owner":[],"postedDate":"May 15th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"published-in-journal","subjectAreas":[],"tags":[],"updatedAt":"2025-02-17T16:07:17+00:00","versionOfRecord":{"articleIdentity":"rs-4376201","link":"https://doi.org/10.1186/s12885-025-13638-7","journal":{"identity":"bmc-cancer","isVorOnly":false,"title":"BMC Cancer"},"publishedOn":"2025-02-13 15:58:07","publishedOnDateReadable":"February 13th, 2025"},"versionCreatedAt":"2024-05-15 15:47:14","video":"","vorDoi":"10.1186/s12885-025-13638-7","vorDoiUrl":"https://doi.org/10.1186/s12885-025-13638-7","workflowStages":[]},"version":"v1","identity":"rs-4376201","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4376201","identity":"rs-4376201","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}