Comparison of clinicopathologic characteristics and survival outcomes of various subtypes of breast cancer

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This study aimed to compare the histopathological features, prognostic indicators, and clinical outcomes of diverse breast cancer subtypes. Patients and methods: A retrospective study was undertaken and all patients of various subtype of breast cancer over a 5 year period were included. Clinicopathological characteristics, including tumor size, lymph node (LN) metastasis, histological grade, immunohistochemical markers (estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu status), TNM staging, lymphovascular invasion (LVI), perineural invasion (PNI), and overall survival (OS),and Disease free survival(DFS) were comprehensively evaluated. Results Of the 9310 individuals diagnosed with breast cancer, a vast majority (99.4%) was females. Patients with invasive papillary carcinoma tumor subtypes presented with an older mean age (57.24 ± 12.92) years. Tumor grade exhibited a statistically significant correlation with tumor subtype (P < 0.001). Invasive lobular carcinoma (94.8%), IPC (94.3%), and mucinous carcinoma (93.6%) demonstrated excellent OS rates in stages I, II, and III. However, ICMP (94.6%) exhibited superior OS in stages II and III. In terms of DFS, IPC (94.2%), mucinous carcinoma (94.5%), and ICMP (93.6%) showed favorable DFS rates in TNM stages 1 and 2, with ICMP maintaining exceptional DFS rates in stage 3. Conclusion Invasive carcinoma with medullary features has the highest DFS rate across all stages, while mucinous and invasive papillary carcinoma have the highest DFS rates in TNM stage 1. Mucinous tumors have the highest DFS rates in TNM stage 2, followed by invasive carcinoma with medullary features. Invasive lobular carcinoma, invasive papillary carcinoma, and mucinous tumors had excellent overall survival (OS) rates in stages I, II, and III. Invasive carcinoma with medullary features had superior OS in stages II and III. Breast cancer Tumor size Lymph node Histological grade Immunohistochemical markers Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 Introduction Breast cancer is the most prevalent cancer among women globally 1 . The incidence and mortality rates of breast cancer are influenced by various factors, including age, ethnicity, socioeconomic status, and tumor-related characteristics such as size, histological grade, and hormone receptor status 2 . Breast cancer incidence in women begins to rise after the age of 24 and persists as the most common cancer even after age 70 3 . Breast cancer is a complex and diverse disease composed of a spectrum of subtypes with varying pathological, prognostic, and molecular characteristics 4 . This heterogeneity manifests in diverse biological and pathological features, clinical presentations, treatment responses, clinical behavior, and outcomes 5 . Pathologists have long recognized the histological diversity of breast carcinomas. The World Health Organization (WHO) classification recognizes up to 21 distinct histological subtypes based on cell morphology, growth patterns, and architectural features 6 . However, in histopathological practice, tumor classification primarily relies on cell type characteristics, cell number, secretion type and location, immunohistochemical profile, and architectural features, rather than precise anatomical location within the mammary tissue 7 . Invasive ductal carcinoma (IDC) is the most prevalent subtype of breast cancer, accounting for approximately 80% of all diagnosed cases in women of all ages and 85% of male breast cancers 8 , 9 . Invasive lobular carcinoma (ILC), the second most common subtype, accounts for 10–15% of all breast cancers 10 . Other subtypes include invasive papillary carcinoma (IPC), Characterized by a papillary architecture, IPC accounts for approximately 0.5% of all invasive breast cancers 11 , 12 ; invasive carcinoma with medullary features (ICMF) Responsible for approximately 5% of all cases, ICMF is associated with better clinical outcomes and a lower risk of lymph node involvement 6 ; neuroendocrine breast cancer (NEBC) is a rare subtype comprising 2–5% of all invasive breast cancers and typically exhibits positive hormone receptors and negative HER2 expressio 10 , 13 ; and mucinous breast cancer is a relatively uncommon subtype representing about 2% of all breast carcinomas, and is classified as a special type of breast cancer in the latest WHO classification 10 , 6 . This study aimed to comprehensively elucidate the histopathological features, prognostic indicators, and clinical outcomes of diverse breast cancer subtypes. By understanding these characteristics, we aim to illuminate treatment strategies and potentially improve patient outcomes for those with special histological breast cancers. Methods The study was conducted under the Declaration of Helsinki and with approval from the Ethics Committee of Shiraz Medical Science University (No.: IR.SUMS.MED.REC.1397.226). This retrospective cohort study analyzed the medical records of 9310 breast cancer patients who sought treatment at Fagihi hospital in Shiraz, Iran between December 2015 and September 2018 and these data were studied in 2023. All included cases exhibited tumor components consistent with the morphological criteria outlined in the WHO histological classification of breast tumors 14 . Patient selection criteria were based on the confirmation of primary BC by histological examination following curative surgical intervention and the patient's age being over 18 years old. Exclusion criteria included patients with synchronous and metachronous cancers and patients with irregular follow-up. A comprehensive analysis of histologic subtypes, including invasive ductal carcinoma, invasive papillary carcinoma, invasive lobular carcinoma, invasive carcinoma with medullary features, and mucinous carcinoma, was conducted. Clinicopathological characteristics, such as tumor size, lymph node (LN) metastasis, nuclear grade, histological grade, immunohistochemical markers (estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu status)), TNM staging, lymphovascular invasion (LVI), perineural invasion (PNI), and overall survival, were meticulously examined. Demographic information, including age, case number, and surgery types, was meticulously extracted using a dedicated data collection form. The tumor size and nodal status was determined using pathological samples. Pathology Analysis Immunohistochemical (IHC) staining was employed to assess the expression levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu), following a standard operating procedure established by the Pathology Department at Shiraz University of Medical Sciences. Normal breast tissue served as a positive control for ER and PR and a negative control for HER2neu. A known case of HER2neu-amplified breast cancer was used as a positive control for HER2neu. Tumors exhibiting 1% or more positive nuclear staining for ER or PR were classified as ER-positive or PR-positive, respectively. Tumors with an IHC score of 3 + based on circumferential membrane-bound staining (Dako Cytomation, Carpinteria, CA, US) or confirmed HER2neu amplification through fluorescent in situ hybridization were categorized as HER2-positive. The breast tumors were classified into four subgroups 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), adhering to the guidelines outlined by Carey 15 . Rigorous follow-up evaluations were conducted at the hospital every three months for the initial two years, every six months for the subsequent three years, and then annually thereafter. The HER2neu status was assessed on a scale ranging from 0 to 3+, determined by the intensity and proportion of positive cells, in accordance with the standardized guidelines set forth by the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP) 15 , 16 For cases exhibiting intermediate (2+) immunohistochemical expression of HER2neu, subsequent fluorescent in situ hybridization (FISH) testing was employed to assess HER2neu gene amplification. FISH testing was conducted using the FDA-approved Path Vysion HER2neu DNA Probe kit and interpreted in adherence to CAP guidelines. Overall survival (OS) was defined as the time span from breast cancer diagnosis until death from any cause or the last follow-up visit. Disease-free survival (DFS) was calculated as the duration from surgery to the first occurrence of metastasis or recurrence. The TNM staging system for breast cancer was evaluated based on the American Joint Committee on Cancer (AJCC) seventh edition guidelines. 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 Of the 9310 individuals diagnosed with breast cancer, a vast majority (99.4%) was females. The patients were classified into distinct groups based on their ER, PR, HER2 status: luminal A (42%), luminal B (19.2%), triple-negative (23.8%), and HER2-positive (15%). The mean age of the patients was 48.93 ± 11.72 years (ranging from 22 to 85 years). A statistically significant difference in mean age at diagnosis was observed among breast cancer subtypes (P > 0.003). Patients with invasive papillary carcinoma tumor subtypes presented with an older mean age (57.24 ± 12.92 years). Table 1 presents a comparative analysis of patient characteristics across different breast cancer subtypes. Male patients exhibited a higher prevalence of invasive ductal carcinoma (0.6%), mucinous (0.9%), and invasive papillary carcinoma (6.0%) breast cancer subtypes (P = 0.005). Patients with invasive carcinoma with medullary features (53.0%) and invasive papillary carcinoma tumors (57.8%) displayed a greater likelihood of right-sided breast involvement. Conversely, patients with invasive ductal carcinoma (51.3%), invasive lobular carcinoma (55.9%), and mucinous tumors (54.4%) exhibited a higher proportion of left-sided breast involvement. Side of involved breast was found to be statistically associated with tumor types (P < 0.001). Across all subtypes, tumor size distribution predominantly fell within the 2 to 5 centimeter range. However, tumor size less than 2 centimeters was more frequent among patients with invasive papillary carcinoma tumors (37.5%). Tumor size greater than 5 centimeters was observed more frequently in patients with mucinous tumors (11.8%). A statistically significant difference in tumor size was evident between the subgroups (P = 0.003). A statistical analysis of tumor grade based on three defined categories revealed that 60.9% of invasive ductal carcinoma cases and 58.3% of invasive lobular carcinoma cases were classified as grade II. In contrast, the majority of patients with mucinous (75.8%) and invasive papillary carcinoma (52.0%) tumor subtypes were assigned to grade I. More than half of patients with invasive carcinoma with medullary features (57.1%) were categorized as grade III. Moreover, tumor size at the time of diagnosis exhibited a statistically significant correlation with tumor subtype (P < 0.001). The occurrence of multifocal breast tumors was more common in individuals with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) subtypes, with respective frequencies of 6.1% and 7.9%. However, the incidence of multifocal breast tumors was relatively low among patients with ICMF, with an incidence of 1.6%. A statistically significant relationship was established between the presence of multifocal breast tumors and tumor subtype (P = 0.01). In contrast, no statistically significant association was found between multicentric breast tumors and tumor subtype (P = 0.12). A substantial percentage of invasive ductal carcinoma cases (56.3%) exhibited in situ components, while invasive carcinoma with medullary features displayed a lower prevalence of in situ components (17.8%). In situ component was not significantly correlated with tumor subtype (P = 0.12). Invasive ductal carcinoma demonstrated the highest incidence of tumor necrosis (45.6%), whereas invasive carcinoma with medullary features exhibited the lowest frequency of tumor necrosis (11.7%). Tumor necrosis exhibited a statistically significant association with tumor subtype (P < 0.001). The presence of vascular invasion was more common in patients with invasive ductal carcinoma (IDC), accounting for 27.1% of cases. Invasive papillary carcinoma tumors exhibited a significantly lower prevalence of vascular invasion (2.2%). Perineural invasion, on the other hand, was more prevalent in patients with invasive lobular carcinoma and IDC, with respective frequencies of 18.4% and 18.2%. A statistically significant correlation was observed between the occurrence of different invasion types and tumor subtypes (P < 0.001). The proportion of patients undergoing sentinel lymph node biopsy (SLNB) alone was higher in those with IDC, ILC, and ICMF subtypes, reaching 49.8%, 52.5%, and 56.6%, respectively. Mucinous and invasive papillary carcinoma tumors, however, displayed a higher frequency of SLNB followed by axillary lymph node dissection (ALND), with percentages of 54.1% and 62.2%, respectively. A statistically significant association was established between axillary staging and tumor subtypes (P < 0.001). TNM stage 2 was the most prevalent stage across all breast cancer subtypes. TNM stage 3 was more frequently observed in invasive lobular carcinoma groups (18.1%) compared to other subtypes. Conversely, TNM stage 1 was more common in invasive lobular carcinoma (47.4%) compared to other subtypes. TNM staging exhibited a statistically significant association with breast cancer subtypes (P < 0.001). Luminal A molecular subtype was common across all of the breast cancer histological tumor subtypes. Luminal B was more frequent among Invasive ductal carcinoma than other subtypes (18.7%). Triple negativity was more frequent among Invasive carcinoma with medullary features than other subtypes (35.4%). Her2neu positive was more frequent in Invasive carcinoma with medullary features than other subtypes (18.7%). The distribution of molecular subtypes among breast cancer histological tumor subtypes showed a statistically significant difference (P < 0.001). The majority of patients remained recurrence-free during the study period (more than 70% in all cancer subtypes). The highest recurrence rate observed during the study period was among patients with invasive lobular carcinoma subtype, while the lowest recurrence rate was observed among patients with mucinous subtype. This observed recurrence distribution was statistically significant (P = 0.01) (Table 1 ). Table 1 The population demographics, histological, and clinicopathological characteristics at baseline of study tumor Subtype P value ** Invasive ductal carcinoma invasive lobular carcinoma Invasive carcinoma with medullary features mucinous Invasive papillary carcinoma Gender Female 8561(99.4) 304(100.0) 253(100.0%) 105(99.1%) 47(94.0%) **0.005 Male 49(0.6%) 0(0.0%) 0(0.0%) 1(0.9%) 3(6.0%) Mean of diagnose Age (SD) year 49.04(11.55) 52.01(10.6) 46.21(10.45) 54.65(16.31) 57.24(12.92) 0.003 Involved Breast Right 4189 (48.7%) 132(44.1%) 134(53.0%) 47(45.6%) 26 (57.8%) 0.001 left 4421 (51.3%) 167 (55.9%) 119 (47.0%) 56 (54.4%) 19(42.2%) Tumor size 5 584(7.4%) 29(10.7%) 19(8.4%) 11(11.8%) 4(10.0%) Permanent Pathology Tumor Grade 1 1434(18.5) 38(31.7%) 14(18.2%) 50(75.8%) 13(52.0%) < 0.001 2 4723(60.9) 70(58.3%) 19(24.7%) 14(21.2%) 11(44.0%) 3 1603(20.7) 12(10.0%) 44(57.1%) 2(3.0%) 1(4.0%) Permanent Pathology Multifocal No 8086(93.9) 280(92.1%) 249(98.4%) 102(96.2%) 48(96.0%) 0.01 Yes 524(6.1%) 24(7.9%) 4(1.6%) 4(3.8%) 2(4.0%) Permanent Pathology multicentric No 8583(99.7) 302(99.3%) 253(100.0%) 105(99.1%) 49(98.0%) 0.12 Yes 27(0.3%) 2(0.7%) 0(0.0%) 1(0.9%) 1(2.0%) Permanent Pathology In-situ Component No 3763(43.7) 159(52.3%) 208(82.2%) 65(61.3%) 32(64.0%) *<0.001 Yes 4847(56.3) 145(47.7%) 45(17.8%) 41(38.7%) 18(36.0%) Permanent Pathology Tumor necrosis No 4686 (54.4%) 244 (81.6%) 140 (55.3%) 91 (88.3%) 32 (71.1%) <*0.001 yes 3924 (45.6%) 55 (18.4%) 113 (44.7%) 12 (11.7%) 13 (28.9%) Invasion Non 3863 (44.9%) 140 (46%) 169 (66.8%) 75 (70.8%) 43 (87.8%) < 0.001 Vascular 2336 (27.1%) 57 (18.8%) 59 (23.3%) 22 (20.8%) 1 (2.2%) Preneural 622 (7.2%) 47 (15.5%) 6 (1.9%) 2 (1.9%) 2 (4.0%) Both of them 1568 (18.2%) 56 (18.4%) 13 (5.1%) 4 (3.8%) 3 (6.0%) Lymphatc, Vascular 221 (2.6%) 4 (1.3%) 6 (2.4%) 3 (2.8%) 0 (0.0%) Axillary Type Only SLNB 4184 (49.8%) 155 (52.5%) 142 (56.6%) 39 (39.8%) 12 (26.7%) <*0.001 SlNB then ALND 3012(35.9) 103(34.9%) 87(34.7%) 53(54.1%) 26(62.2%) ALND as first 1203 (14.3%) 37(12.5%) 22 (8.8%) 5 (8.8%) 5 (11.1%) TNM Stage 1 1485(28.2) 35(21.9%) 23(21.3%) 8(17.0%) 9(47.4%) <*0.001 2 3195(60.8) 96(60.0%) 79(73.1%) 39(83.0%) 10(52.6%) 3 576(11.0%) 29(18.1%) 6(5.6%) 0(0.0%) 0(0.0%) Molecular subtype Luminal A 4899(56.9) 247(81.7%) 77(30.4%) 84 (79.5%) 37(78.8%) <*0.001 Luminal B 1611(18.7) 41(13.6%) 39(15.5%) 10(9.5%) 3(6.3%) HER2 1162(13.5) 8(2.6%) 47(18.7%) 4(4.2%) 2(4.2%) Triple negative 938(10.9%) 8(2.6%) 90(35.4%) 7(6.8%) 5(10.7%) recurrence No 6864(81.8) 236(79.1%) 204 (83.3%) 98 (94.2%) 41 (87.2%) 0.01 Yes 1523(18.2) 62(20.8%) 41 (16.7%) 6 (5.8%) 6(12.8%) *chi-square test, **Fisher exact test Table 2 summarizes the pattern of oncological treatment utilization across breast cancer subtypes among the cohort. Preoperative chemotherapy and intraoperative radiotherapy were uncommon treatments regardless of tumor subtype. Postoperative chemotherapy was more commonly administered to patients with invasive ductal carcinoma (81.5%) and invasive carcinoma with medullary features (85.4%) subtypes. Chest and axillary radiotherapy was applied to a substantial proportion of patients across all subtypes. Hormone therapy was administered to most patients, except for 61.7% of women with invasive carcinoma with medullary features subtype. A statistically significant association was observed between all investigated oncological treatments and breast cancer subtypes, with the exception of intraoperative radiotherapy (P < 0.001, P = 0.08). Breast conservating surgery (BCS) was the most frequently performed surgical procedure across all subtypes. Mastectomy was the second most common treatment (P < 0.001). Table 2 Oncological treatments process across breast cancer subtypes among cohort population Tumor subtype P value** Invasive ductal carcinoma invasive lobular carcinoma Invasive carcinoma with medullary features mucinous Invasive papillary carcinoma Preoperative chemotherapy No 7327(85.1%) 260 (87.0%) 241 (95.3%) 91 (88.3%) 44 (97.8%) *<0.001 Yes 1283 (14.9%) 39 (13.0%) 12 (4.7%) 12 (11.7%) 1 (2.2%) postoperative chemotherapy No 1595 (16.4%) 67 (22.4%) 37 (14.6%) 38(36.9%) 27 (60.0%) *<0.001 Yes 7015 (81.5%) 232 (77.6%) 216 (85.4%) 65 (63.1%) 18 (40.0%) Chest and axilla radiotherapy No 2469 (28.7%) 109 (35.9%) 68 (26.9%) 48 (45.3%) 24 (48.0%) *<0.001 Yes 6141 (71.3%) 195 (64.1%) 185 (73.1%) 58 (54.7%) 26 (52%) Intraoperative radiotherapy No 8267 (96.0%) 289 (96.7%) 251 (99.2%) 98 (95.1%) 43 (95.6%) *0.08 Yes 343 (4.0%) 10 (3.3%) 2 (0.8%) 5 (4.9%) 2 (4.4%) Hormone therapy no 2500(29.0%) 44(14.5%) 156(61.7%) 12(11.3%) 16(32.0%) *<0.001 yes 6110(71.0%) 260(85.5%) 97(38.3%) 94(88.7%) 34(68.0%) Surgery Type Breast-conservating surgery (BCS) 4731(54.9%) 152(50.0%) 173(68.7%) 55(52.4%) 29(64.4%) P < 0.001 Simple Mastectomy at first 3461 (40.2%) 140(46.1%) 74 (29.2%) 47 (44.8%) 14 (31.2%) Breast-canservating surgery (BCS), then simple Mastectomy 369(4.9%) 10(3.9%) 5(2.1%) 3(2.8%) 2(4.4%) Table 3 summarizes the 1-, 3-, and 5-year OS and DFS outcomes for breast cancer subtypes across TNM stages. Invasive lobular carcinoma and mucinous tumors exhibited remarkable 100% OS rates in stage I, while papillary tumors maintained 100% OS rates for 1 and 3 years (Fig. 1 ). In stage II, all three subtypes (invasive lobular carcinoma, mucinous, and papillary) maintained 100% OS rates for 1, 3, and 5 years (Fig. 2). In stage III, invasive lobular carcinoma demonstrated 100% 1-year OS and invasive carcinoma with medullary features maintained 100% OS rates for 1, 3, and 5 years. Nevertheless, other breast tumor subtypes exhibited less than 100% OS rates across all three stages (Fig. 3). A statistical analysis of OS in TNM stage I failed to reveal a significant association with breast cancer subtypes (P value = 0.69). Conversely, OS rates in stages II and III were significantly different among breast cancer subtypes (P value = 0.03 and 0.02, respectively). Patients with invasive carcinoma with medullary features tumor exhibited 100% DFS rates at 1 and 3 years of follow-up. Mucinous and papillary tumors demonstrated 100% DFS rates at 1, 3, and 5 years of follow-up in TNM stage 1 (Fig. 4). Mucinous tumors also maintained 100% DFS rates at 1, 3, and 5 years of follow-up in TNM stage 2 (Fig. 5), while invasive carcinoma with medullary features tumor displayed 100% DFS rates at 1, 3, and 5 years of follow-up in TNM stage 3 (Fig. 6). Other breast tumor subtypes exhibited DFS rates below 100% across the three stages. However, none of these differences were statistically significant (Table 3 ). Table 3 Overall survival and Disease Survival rate according to breast cancer subtypes at each TNM Stage. Overall Survival times (%) P value* Disease Survival times (%) P value* Stage1 1 3 5 1 3 5 Invasive ductal carcinoma 100 99 98 0.69 96 95 91 0.32 invasive lobular carcinoma 100 100 100 91 84 84 Invasive carcinoma with medullary features 100 96 91 100 100 95 mucinous 100 100 100 100 100 100 Invasive papillary carcinoma 100 100 100 100 100 100 Stage2 Invasive ductal carcinoma 99 97 95 0.03 95 91 88 0.24 invasive lobular carcinoma 100 99 99 96 95 89 Invasive carcinoma with medullary features 99 97 96 97 95 92 mucinous 100 100 100 100 100 100 Invasive papillary carcinoma 100 100 100 90 90 90 Stage 3 Invasive ductal carcinoma 99 95 92 0.02 89 81 76 0.13 invasive lobular carcinoma 100 93 82 83 71 65 Invasive carcinoma with medullary features 100 100 100 100 100 100 mucinous - - - - - - Invasive papillary carcinoma - - - - - - ** Wilcoxon (Gehan) test Discussion BC is a multifaceted and heterogeneous disease influenced by a range of clinical, pathological, and biological factors that exhibit variability across different populations 1 . These prognostic factors play a crucial role in the management of breast cancer. Therefore, to gain a deeper understanding of breast cancer and its molecular subtypes, we conducted an analysis of 9310 breast cancer cases. Our study determined that the age at breast cancer diagnosis ranged from 22 to 85 years, with a mean of 48.93 ± 11.72 years. This finding is consistent with the results of earlier studies 3 , 17 . However, in Western and Asian countries, breast cancer typically occurs at a later age 18 . The age at diagnosis is a crucial prognostic factor, as tumors diagnosed in younger individuals tend to be more aggressive and/or less responsive to treatment 3 . Several factors may influence the variation in age at diagnosis, including population characteristics, genetic predisposition, and environmental factors 2 . Our study also revealed a statistically significant difference in mean age at diagnosis among various breast cancer subtypes (P > 0.003). Patients with Invasive papillary carcinoma subtypes were generally older than those with other subtypes (57.24 ± 12.92) years. Invasive papillary carcinoma is classified as a low-grade carcinoma 19 . Owing to the rarity of the disease and the complexity of its histological classification, there is no universally accepted consensus on the management of patients with invasive papillary carcinoma 20 . Interestingly, invasive papillary carcinoma is relatively more prevalent among males 21 which is consistent with our observation of invasive papillary carcinoma breast cancer subtypes in male patients. Our study also reported a significantly higher female-to-male ratio (99.43%) compared to other studies 22 , 23 . Our study identified invasive ductal carcinoma as the predominant histological subtype, aligning with the findings of most previous studies on breast cancer 28 . Patients with invasive carcinoma with medullary features (53.0%) and invasive papillary carcinoma (57.8%) exhibited a greater tendency for right breast involvement. Conversely, patients with invasive ductal carcinoma (51.3%), invasive lobular carcinoma (55.9%), and mucinous tumor (54.4%) showed a higher prevalence of left breast involvement. A statistically significant correlation was established between the involved breast side and tumor type (P < 0.001). Numerous studies have delved into the possible reasons for the observed left-sided predominance in breast cancer 24 , 25 . Furthermore, a study reported that patients with left-sided breast cancer treated with radiation therapy were at an increased risk of cardiovascular complications and historically had worse outcomes 26 . Over half of all tumor sizes across subtypes fell within the 2 to 5 centimeter range, with tumor size less than 2 centimeters being more prevalent among patients with invasive papillary carcinoma (37.5%). Tumor size greater than 5 centimeters was more common among patients with mucinous tumors (11.8%). A statistically significant difference in tumor size was observed between the subgroups (P = 0.003). Moreover, tumor size at the time of diagnosis was significantly correlated with tumor subtype (P < 0.001). According to the "Size-Note" hypothesis, tumor size and the number of positive lymph nodes independently contribute to the lethality of invasive breast cancer 27 . Smaller tumors (diameter less than 2 cm) exhibit a lower risk of axillary lymph node metastasis, and tumor size serves as an independent predictor of nodal positivity 28 . Therefore, we propose that tumor size can predict survival by influencing regional lymph node metastasis, as larger tumors tend to invade adjacent tissues more extensively, increasing the likelihood of lymph node involvement 29 . In Western countries, the majority of breast tumors are less than 2 cm in diameter, reflecting the early detection of the disease 30 . However, the percentage of tumors larger than 2 cm in our study was higher compared to other studies 30 , 31 . Our study revealed that 60.9% of invasive ductal carcinoma cases and 58.3% of invasive lobular carcinoma cases exhibited grade II histology. The majority of patients with mucinous (75.8%) and invasive papillary carcinoma (52.0%) tumors had grade I histology. Notably, more than half of patients with invasive carcinoma with medullary features (57.1%) had grade III histology. This finding contrasts with studies reporting a lower percentage of grade II tumors and a higher level of grade III histology 32 . Histological grading serves as a powerful prognostic factor and is an integral component of several clinical decision-making tools, such as the Nottingham prognostic index and Adjuvant online 33 . Interestingly, specific genetic and transcriptomic features of breast cancers were associated with distinct tumor grades 34 . However, a multicenter study indicated that only lymph node status and lymphovascular invasion influenced prognosis, not tumor size or histological grade 35 . TNM stage 2 was the most frequently observed stage across all breast cancer subtypes, and a statistically significant association was established between TNM stage and breast cancer tumor g staging which was devised to classify the extent of local, regional, and distant disease involvement at the time of initial treatment, providing objective and enduring descriptions of the disease 36 . Categories with similar prognostic significance can be combined to define the disease stages 37 . However, our findings contrast with those of other studies, which have reported an unclear relationship between tumor stage and clinical outcome across the breast cancer patient population 38 . This implies that TNM staging alone may not be an adequate predictor of therapeutic outcomes in breast cancer patients, not because of limitations in the staging system but rather due to the distinct biological characteristics of TNBC compared to other subtypes. Our study determined that luminal A molecular subtype was widespread across all breast cancer histological subtypes, and luminal B was more prevalent among invasive ductal carcinoma than other subtypes (18.7%), consistent with the results of another study 39 . However, our findings differ from those of other studies, which reported luminal B tumors as the most common subtype 40 . Genetic, racial, and environmental factors may explain these inconsistencies, and variations in diagnostic facilities may also contribute. Our findings corroborate those of other studies 41 , in demonstrating a higher frequency of triple negativity among invasive carcinoma with medullary features than other subtypes (35.4%). A statistically significant difference was observed in the distribution of molecular subtypes among breast cancer histological subtypes (P < 0.001). Breast cancer is characterized by a distinct recurrence pattern. Sopik et al. demonstrated that the majority of recurrences and deaths occur within the first five years after diagnosis, with a particularly high risk in the first three years 42 . The risk of recurrence steeply declines after this initial period. Conversely, in another group of patients, the risk of recurrence is low within the first five years after diagnosis, but distant recurrences continue to accumulate for up to 17 years 43 . This study revealed that the majority of patients (more than 70% in all cancer subtypes) remained recurrence-free during the investigated time interval. Visceral organs and the brain are the most common sites of recurrence in breast cancer 44 . Chemotherapy has been demonstrated to improve survival outcomes for breast cancer patients, while the role of radiotherapy remains a subject of debate. In our study, postoperative chemotherapy was more frequently administered to patients with invasive ductal carcinoma (81.5%) and invasive carcinoma with medullary features (85.4%) subtypes. While multiple studies have confirmed the beneficial effects of radiotherapy on overall survival (OS) in breast cancer patients 45 , others have suggested that its benefits may be limited. For instance, Chua et al. found that radiotherapy effectively reduced local-regional recurrences but not distant recurrences 46 . Haque et al. proposed that mastectomy combined with radiotherapy was associated with improved OS only in high-risk patients (T3–4 or node-positive), whereas lumpectomy with radiotherapy was beneficial in both high- and low-risk cohorts (T1–2N0) 47 . Chest and axillary radiotherapy was performed in most breast cancer subtypes in our study. The majority of study participants received hormonal therapy, except for women with invasive carcinoma with medullary features (61.7% not treated with hormonal therapy). A 2011 meta-analysis revealed that 5-year adjuvant hormonal therapy (HT) effectively reduces the risk of breast cancer recurrence and mortality 48 . Non-compliance with and early cessation of HT are linked to elevated relapse and mortality rates 49 . BCS was the most prevalent surgical procedure across all breast cancer subtypes (P < 0.001). Mastectomy was the second most common treatment approach. Studies have documented an increase in the utilization of BCS following neoadjuvant treatment and the gradual expansion of treatment options to less toxic targeted therapies 50 . The conversion rate from mastectomy to BCS exceeded 50% after neoadjuvant chemotherapy (NACT) plus dual-target therapy in the Asian population 51 . This study revealed that invasive lobular carcinoma and invasive papillary carcinoma and mucinous tumors displayed exceptional 1, 3, and 5-year OS rates (100%), compared to other subtypes at stage 1. In stage 2, invasive lobular carcinoma and mucinous, and invasive papillary carcinoma demonstrated improved 1, 3, and 5-year OS. At stage 3, invasive lobular carcinoma tumor exhibited higher 1-year OS rates, and invasive carcinoma with medullary features displayed higher 1, 3, and 5-year OS rates. Statistically significant differences in OS were observed among breast cancer subtypes within TNM stages 2 and 3 (P value = 0.03 and 0.02, respectively). The current literature suggests an OS of 92% in target patients, implying higher OS rates in our study compared to the findings reported by Carey et al. 15 . Invasive carcinoma with medullary features achieved the highest 1-year, 3-year, and 5-year DFS rates (100%). Mucinous and invasive papillary carcinoma demonstrated the highest 1-year, 3-year, and 5-year DFS rates in TNM stage 1. Mucinous tumors exhibited the highest 1-year, 3-year, and 5-year DFS rates in TNM stage 2, followed by invasive carcinoma with medullary features. There is a paucity of studies investigating OS and DFS of breast tumors classified by histological subtypes according to TNM stages. However, some studies have explored OS and DFS of breast cancers categorized by molecular subtypes. One such study 52 examined the death rate among molecular subgroups in 24 breast cancer patients following a follow-up period of up to 92 months. Moreover, Zanguri et al. reported the 5-year OS and DFS rates in the Invasive papillary carcinoma group were better than those in the Invasive ductal carcinoma group 19 . Limitations of the study This study's limitations include its retrospective design and we had big sample size if all included patients completed their follow-up periods. Conclusion This study revealed that Invasive ductal carcinoma was the most common histological subtype, with the majority of cases being stage II that serves as a powerful prognostic factor for BC. Luminal A molecular subtype was widespread across all breast cancer histological subtypes, and luminal B was more prevalent among invasive ductal carcinoma than other subtypes (18.7%). The incidence of multifocal breast tumors was relatively low among patients with ICMF, Furthermore, the cases exhibited detectable differences in adjuvant therapy that chemotherapy has been demonstrated to improve survival outcomes for breast cancer patients. This study revealed that invasive lobular carcinoma and invasive papillary carcinoma and mucinous tumors displayed exceptional 1, 3, and 5-year OS rates (100%) at stage 1. In stage 2, invasive lobular carcinoma and mucinous, and invasive papillary carcinoma demonstrated improved 1, 3, and 5-year OS. At stage 3, invasive lobular carcinoma tumor exhibited higher 1-year OS rates, and invasive carcinoma with medullary features displayed higher 1, 3, and 5-year OS rates. Invasive carcinoma with medullary features has the highest DFS rate across all stages, while mucinous and invasive papillary carcinoma have the highest DFS rates in TNM stage 1. Mucinous tumors have the highest DFS rates in TNM stage 2, followed by invasive carcinoma with medullary features. Declarations 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. Author contributions: All authors contributed to the study's conception and design. Material preparation, data collection, and analysis were performed by Morteza Amestejani, Vahid Zangouri, Iman Deylami, and Souzan Soufizadeh Balaneji 3 . The first draft of the manuscript was written by Morteza Amestejani and Seyed Amin Mousavi. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Funding This project is financially supported by the vice chancellor of research, Shiraz University of Medical Sciences (Grant No.97-17376). Data availability The original contributions presented in the study are included in the article/ Supplementary Material, 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(No.: IR.SUMS.MED.REC.1397.226) . 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. 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Steenbruggen TG, van Ramshorst MS, Kok M, Linn SC, Smorenburg CH, Sonke GS. Neoadjuvant therapy for breast cancer: established concepts and emerging strategies. Drugs. 2017;77:1313-36. Chang Y-K, Co M, Kwong A. Conversion rate from mastectomy to breast conservation after neoadjuvant dual target therapy for HER2-positive breast cancer in the Asian population. Breast Cancer. 2020;27:456-63. Engstrøm MJ, Opdahl S, Hagen AI, Romundstad PR, Akslen LA, Haugen OA, et al. Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients. Breast cancer research and treatment. 2013;140:463-73. Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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subtypes at stage 1\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-3890579/v1/75381e48b11c1000a4bda2cf.png"},{"id":51134893,"identity":"4ec984e8-a175-453e-b8c7-fdbc2a2d7e80","added_by":"auto","created_at":"2024-02-14 18:27:13","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":66538,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times based patient’s tumor subtypes at stage 2\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-3890579/v1/05fbefe03614206262093735.png"},{"id":51134895,"identity":"26b03908-eb22-4daa-8662-49c246b5c86f","added_by":"auto","created_at":"2024-02-14 18:27:13","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":60026,"visible":true,"origin":"","legend":"\u003cp\u003eDFS times based patient’s tumor subtypes at stage 3\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-3890579/v1/446d154161cdc630b969ac59.png"},{"id":78727011,"identity":"efd98b24-bcf1-4204-a79d-0d3f274c7ba9","added_by":"auto","created_at":"2025-03-18 06:31:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1418851,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3890579/v1/bcb7525d-636e-4300-8b91-c17cc1bee53e.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Comparison of clinicopathologic characteristics and survival outcomes of various subtypes of breast cancer","fulltext":[{"header":"Introduction","content":"\u003cp\u003eBreast cancer is the most prevalent cancer among women globally \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. The incidence and mortality rates of breast cancer are influenced by various factors, including age, ethnicity, socioeconomic status, and tumor-related characteristics such as size, histological grade, and hormone receptor status \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Breast cancer incidence in women begins to rise after the age of 24 and persists as the most common cancer even after age 70 \u003csup\u003e3\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eBreast cancer is a complex and diverse disease composed of a spectrum of subtypes with varying pathological, prognostic, and molecular characteristics \u003csup\u003e\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u003c/sup\u003e. This heterogeneity manifests in diverse biological and pathological features, clinical presentations, treatment responses, clinical behavior, and outcomes \u003csup\u003e\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u003c/sup\u003e. Pathologists have long recognized the histological diversity of breast carcinomas. The World Health Organization (WHO) classification recognizes up to 21 distinct histological subtypes based on cell morphology, growth patterns, and architectural features \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e. However, in histopathological practice, tumor classification primarily relies on cell type characteristics, cell number, secretion type and location, immunohistochemical profile, and architectural features, rather than precise anatomical location within the mammary tissue \u003csup\u003e\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInvasive ductal carcinoma (IDC) is the most prevalent subtype of breast cancer, accounting for approximately 80% of all diagnosed cases in women of all ages and 85% of male breast cancers \u003csup\u003e\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e\u003c/sup\u003e, \u003csup\u003e\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e\u003c/sup\u003e. Invasive lobular carcinoma (ILC), the second most common subtype, accounts for 10\u0026ndash;15% of all breast cancers \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u003c/sup\u003e. Other subtypes include invasive papillary carcinoma (IPC), Characterized by a papillary architecture, IPC accounts for approximately 0.5% of all invasive breast cancers \u003csup\u003e\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e\u003c/sup\u003e, \u003csup\u003e\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e\u003c/sup\u003e; invasive carcinoma with medullary features (ICMF) Responsible for approximately 5% of all cases, ICMF is associated with better clinical outcomes and a lower risk of lymph node involvement \u003csup\u003e\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e; neuroendocrine breast cancer (NEBC) is a rare subtype comprising 2\u0026ndash;5% of all invasive breast cancers and typically exhibits positive hormone receptors and negative HER2 expressio \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u003c/sup\u003e; and mucinous breast cancer is a relatively uncommon subtype representing about 2% of all breast carcinomas, and is classified as a special type of breast cancer in the latest WHO classification \u003csup\u003e\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study aimed to comprehensively elucidate the histopathological features, prognostic indicators, and clinical outcomes of diverse breast cancer subtypes. By understanding these characteristics, we aim to illuminate treatment strategies and potentially improve patient outcomes for those with special histological breast cancers.\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 (No.: IR.SUMS.MED.REC.1397.226).\u003c/p\u003e \u003cp\u003eThis retrospective cohort study analyzed the medical records of 9310 breast cancer patients who sought treatment at Fagihi hospital in Shiraz, Iran between December 2015 and September 2018 and these data were studied in 2023. All included cases exhibited tumor components consistent with the morphological criteria outlined in the WHO histological classification of breast tumors \u003csup\u003e\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e\u003c/sup\u003e. Patient selection criteria were based on the confirmation of primary BC by histological examination following curative surgical intervention and the patient's age being over 18 years old. Exclusion criteria included patients with synchronous and metachronous cancers and patients with irregular follow-up.\u003c/p\u003e \u003cp\u003eA comprehensive analysis of histologic subtypes, including invasive ductal carcinoma, invasive papillary carcinoma, invasive lobular carcinoma, invasive carcinoma with medullary features, and mucinous carcinoma, was conducted. Clinicopathological characteristics, such as tumor size, lymph node (LN) metastasis, nuclear grade, histological grade, immunohistochemical markers (estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu status)), TNM staging, lymphovascular invasion (LVI), perineural invasion (PNI), and overall survival, were meticulously examined. Demographic information, including age, case number, and surgery types, was meticulously extracted using a dedicated data collection form. The tumor size and\u003c/p\u003e \u003cp\u003enodal status was determined using pathological samples.\u003c/p\u003e \u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003ePathology Analysis\u003c/h2\u003e \u003cp\u003eImmunohistochemical (IHC) staining was employed to assess the expression levels of estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu), following a standard operating procedure established by the Pathology Department at Shiraz University of Medical Sciences. Normal breast tissue served as a positive control for ER and PR and a negative control for HER2neu. A known case of HER2neu-amplified breast cancer was used as a positive control for HER2neu. Tumors exhibiting 1% or more positive nuclear staining for ER or PR were classified as ER-positive or PR-positive, respectively. Tumors with an IHC score of 3\u0026thinsp;+\u0026thinsp;based on circumferential membrane-bound staining (Dako Cytomation, Carpinteria, CA, US) or confirmed HER2neu amplification through fluorescent in situ hybridization were categorized as HER2-positive. The breast tumors were classified into four subgroups 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), adhering to the guidelines outlined by Carey \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eRigorous follow-up evaluations were conducted at the hospital every three months for the initial two years, every six months for the subsequent three years, and then annually thereafter. The HER2neu status was assessed on a scale ranging from 0 to 3+, determined by the intensity and proportion of positive cells, in accordance with the standardized guidelines set forth by the American Society of Clinical Oncology (ASCO) and the College of American Pathologists (CAP) \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e\u003c/sup\u003e For cases exhibiting intermediate (2+) immunohistochemical expression of HER2neu, subsequent fluorescent in situ hybridization (FISH) testing was employed to assess HER2neu gene amplification. FISH testing was conducted using the FDA-approved Path Vysion HER2neu DNA Probe kit and interpreted in adherence to CAP guidelines. Overall survival (OS) was defined as the time span from breast cancer diagnosis until death from any cause or the last follow-up visit. Disease-free survival (DFS) was calculated as the duration from surgery to the first occurrence of metastasis or recurrence. The TNM staging system for breast cancer was evaluated based on the American Joint Committee on Cancer (AJCC) seventh edition guidelines.\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\u003eOf the 9310 individuals diagnosed with breast cancer, a vast majority (99.4%) was females. The patients were classified into distinct groups based on their ER, PR, HER2 status: luminal A (42%), luminal B (19.2%), triple-negative (23.8%), and HER2-positive (15%). The mean age of the patients was 48.93\u0026thinsp;\u0026plusmn;\u0026thinsp;11.72 years (ranging from 22 to 85 years). A statistically significant difference in mean age at diagnosis was observed among breast cancer subtypes (P\u0026thinsp;\u0026gt;\u0026thinsp;0.003). Patients with invasive papillary carcinoma tumor subtypes presented with an older mean age (57.24\u0026thinsp;\u0026plusmn;\u0026thinsp;12.92 years).\u003c/p\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e presents a comparative analysis of patient characteristics across different breast cancer subtypes. Male patients exhibited a higher prevalence of invasive ductal carcinoma (0.6%), mucinous (0.9%), and invasive papillary carcinoma (6.0%) breast cancer subtypes (P\u0026thinsp;=\u0026thinsp;0.005). Patients with invasive carcinoma with medullary features (53.0%) and invasive papillary carcinoma tumors (57.8%) displayed a greater likelihood of right-sided breast involvement. Conversely, patients with invasive ductal carcinoma (51.3%), invasive lobular carcinoma (55.9%), and mucinous tumors (54.4%) exhibited a higher proportion of left-sided breast involvement. Side of involved breast was found to be statistically associated with tumor types (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Across all subtypes, tumor size distribution predominantly fell within the 2 to 5 centimeter range. However, tumor size less than 2 centimeters was more frequent among patients with invasive papillary carcinoma tumors (37.5%). Tumor size greater than 5 centimeters was observed more frequently in patients with mucinous tumors (11.8%). A statistically significant difference in tumor size was evident between the subgroups (P\u0026thinsp;=\u0026thinsp;0.003).\u003c/p\u003e\n\u003cp\u003eA statistical analysis of tumor grade based on three defined categories revealed that 60.9% of invasive ductal carcinoma cases and 58.3% of invasive lobular carcinoma cases were classified as grade II. In contrast, the majority of patients with mucinous (75.8%) and invasive papillary carcinoma (52.0%) tumor subtypes were assigned to grade I. More than half of patients with invasive carcinoma with medullary features (57.1%) were categorized as grade III. Moreover, tumor size at the time of diagnosis exhibited a statistically significant correlation with tumor subtype (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eThe occurrence of multifocal breast tumors was more common in individuals with invasive ductal carcinoma (IDC) and invasive lobular carcinoma (ILC) subtypes, with respective frequencies of 6.1% and 7.9%. However, the incidence of multifocal breast tumors was relatively low among patients with ICMF, with an incidence of 1.6%. A statistically significant relationship was established between the presence of multifocal breast tumors and tumor subtype (P\u0026thinsp;=\u0026thinsp;0.01). In contrast, no statistically significant association was found between multicentric breast tumors and tumor subtype (P\u0026thinsp;=\u0026thinsp;0.12).\u003c/p\u003e\n\u003cp\u003eA substantial percentage of invasive ductal carcinoma cases (56.3%) exhibited in situ components, while invasive carcinoma with medullary features displayed a lower prevalence of in situ components (17.8%). In situ component was not significantly correlated with tumor subtype (P\u0026thinsp;=\u0026thinsp;0.12). Invasive ductal carcinoma demonstrated the highest incidence of tumor necrosis (45.6%), whereas invasive carcinoma with medullary features exhibited the lowest frequency of tumor necrosis (11.7%). Tumor necrosis exhibited a statistically significant association with tumor subtype (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eThe presence of vascular invasion was more common in patients with invasive ductal carcinoma (IDC), accounting for 27.1% of cases. Invasive papillary carcinoma tumors exhibited a significantly lower prevalence of vascular invasion (2.2%). Perineural invasion, on the other hand, was more prevalent in patients with invasive lobular carcinoma and IDC, with respective frequencies of 18.4% and 18.2%. A statistically significant correlation was observed between the occurrence of different invasion types and tumor subtypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eThe proportion of patients undergoing sentinel lymph node biopsy (SLNB) alone was higher in those with IDC, ILC, and ICMF subtypes, reaching 49.8%, 52.5%, and 56.6%, respectively. Mucinous and invasive papillary carcinoma tumors, however, displayed a higher frequency of SLNB followed by axillary lymph node dissection (ALND), with percentages of 54.1% and 62.2%, respectively. A statistically significant association was established between axillary staging and tumor subtypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eTNM stage 2 was the most prevalent stage across all breast cancer subtypes. TNM stage 3 was more frequently observed in invasive lobular carcinoma groups (18.1%) compared to other subtypes. Conversely, TNM stage 1 was more common in invasive lobular carcinoma (47.4%) compared to other subtypes. TNM staging exhibited a statistically significant association with breast cancer subtypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eLuminal A molecular subtype was common across all of the breast cancer histological tumor subtypes. Luminal B was more frequent among Invasive ductal carcinoma than other subtypes (18.7%). Triple negativity was more frequent among Invasive carcinoma with medullary features than other subtypes (35.4%). Her2neu positive was more frequent in Invasive carcinoma with medullary features than other subtypes (18.7%). The distribution of molecular subtypes among breast cancer histological tumor subtypes showed a statistically significant difference (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cp\u003eThe majority of patients remained recurrence-free during the study period (more than 70% in all cancer subtypes). The highest recurrence rate observed during the study period was among patients with invasive lobular carcinoma subtype, while the lowest recurrence rate was observed among patients with mucinous subtype. This observed recurrence distribution was statistically significant (P\u0026thinsp;=\u0026thinsp;0.01) (Table\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eThe population demographics, histological, and clinicopathological characteristics at baseline of study\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003cth align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003etumor Subtype\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eP value **\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003einvasive lobular carcinoma\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInvasive carcinoma with medullary features\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003emucinous\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eInvasive papillary carcinoma\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\u0026nbsp;\u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eGender\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8561(99.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e304(100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e253(100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105(99.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47(94.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e**0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49(0.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\n \u003cp\u003eMean of diagnose Age (SD) year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e49.04(11.55)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e52.01(10.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e46.21(10.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e54.65(16.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e57.24(12.92)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eInvolved Breast\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4189 (48.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e132(44.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e134(53.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47(45.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26 (57.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eleft\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4421 (51.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e167 (55.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e119 (47.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e56 (54.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(42.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eTumor size\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2300(29.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67(24.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(19.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e15(37.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u0026ndash;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4986(63.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e176(64.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e164(72.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e64(68.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e21(52.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u0026gt;\u0026thinsp;5\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e584(7.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29(10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(8.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(11.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003ePermanent Pathology Tumor Grade\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1434(18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38(31.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e50(75.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13(52.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4723(60.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e70(58.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e19(24.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e14(21.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e11(44.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1603(20.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(10.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e44(57.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(3.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePermanent Pathology Multifocal\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8086(93.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e280(92.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e249(98.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e102(96.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e48(96.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e524(6.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24(7.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(1.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePermanent Pathology multicentric\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8583(99.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e302(99.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e253(100.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e105(99.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e49(98.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e27(0.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(0.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(0.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1(2.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePermanent Pathology In-situ Component\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3763(43.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e159(52.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e208(82.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e65(61.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32(64.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e*\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4847(56.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e145(47.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e45(17.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41(38.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e18(36.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePermanent Pathology Tumor necrosis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4686 (54.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e244 (81.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e140 (55.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e91 (88.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e32 (71.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e\u0026lt;*0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3924 (45.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e113 (44.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13 (28.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eInvasion\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNon\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3863 (44.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e140 (46%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e169 (66.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e75 (70.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e43 (87.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eVascular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2336 (27.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e57 (18.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e59 (23.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePreneural\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e622 (7.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (1.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBoth of them\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1568 (18.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e56 (18.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e13 (5.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4 (3.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (6.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLymphatc, Vascular\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e221 (2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4 (1.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (2.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3 (2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0 (0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eAxillary Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eOnly SLNB\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4184 (49.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e155 (52.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e142 (56.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39 (39.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e12 (26.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;*0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSlNB then ALND\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3012(35.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e103(34.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e87(34.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e53(54.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e26(62.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eALND as first\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1203 (14.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37(12.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e22 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (8.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5 (11.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eTNM Stage\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1485(28.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e35(21.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e23(21.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e8(17.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e9(47.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003e\u0026lt;*0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3195(60.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96(60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e79(73.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(83.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(52.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e576(11.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29(18.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(5.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0(0.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eMolecular subtype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLuminal A\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4899(56.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e247(81.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e77(30.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e84 (79.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e37(78.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003e\u0026lt;*0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eLuminal B\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1611(18.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e41(13.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e39(15.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e10(9.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3(6.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eHER2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1162(13.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e47(18.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e4(4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2(4.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eTriple negative\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e938(10.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8(2.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e90(35.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e7(6.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5(10.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003erecurrence\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6864(81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e236(79.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e204 (83.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e98 (94.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (87.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1523(18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e62(20.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e41 (16.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6 (5.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e6(12.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"8\"\u003e*chi-square test, **Fisher exact test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan\u003e2\u003c/span\u003e summarizes the pattern of oncological treatment utilization across breast cancer subtypes among the cohort. Preoperative chemotherapy and intraoperative radiotherapy were uncommon treatments regardless of tumor subtype. Postoperative chemotherapy was more commonly administered to patients with invasive ductal carcinoma (81.5%) and invasive carcinoma with medullary features (85.4%) subtypes. Chest and axillary radiotherapy was applied to a substantial proportion of patients across all subtypes. Hormone therapy was administered to most patients, except for 61.7% of women with invasive carcinoma with medullary features subtype. A statistically significant association was observed between all investigated oncological treatments and breast cancer subtypes, with the exception of intraoperative radiotherapy (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001, P\u0026thinsp;=\u0026thinsp;0.08). Breast conservating surgery (BCS) was the most frequently performed surgical procedure across all subtypes. Mastectomy was the second most common treatment (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab2\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 2\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eOncological treatments process across breast cancer subtypes among cohort population\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"8\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\" rowspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"5\"\u003e\n \u003cp\u003eTumor subtype\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eP value**\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einvasive lobular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive carcinoma with medullary features\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive papillary carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003ePreoperative chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7327(85.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e260 (87.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e241 (95.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91 (88.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44 (97.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e*\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1283 (14.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e39 (13.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (4.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12 (11.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1 (2.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003epostoperative chemotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e1595 (16.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e67 (22.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e37 (14.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e38(36.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e27 (60.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e*\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e7015 (81.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e232 (77.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e216 (85.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65 (63.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e18 (40.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eChest and axilla radiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2469 (28.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e109 (35.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e68 (26.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e48 (45.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e24 (48.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e*\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6141 (71.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e195 (64.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e185 (73.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e58 (54.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e26 (52%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eIntraoperative radiotherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eNo\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e8267 (96.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e289 (96.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e251 (99.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98 (95.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e43 (95.6%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e*0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eYes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e343 (4.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10 (3.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (0.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5 (4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2 (4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eHormone therapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2500(29.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e44(14.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e156(61.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e12(11.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e16(32.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003e*\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e6110(71.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e260(85.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97(38.3%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e94(88.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e34(68.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"4\"\u003e\n \u003cp\u003eSurgery Type\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"6\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast-conservating surgery (BCS)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e4731(54.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e152(50.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e173(68.7%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e55(52.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e29(64.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"3\"\u003e\n \u003cp\u003eP\u0026thinsp;\u0026lt;\u0026thinsp;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eSimple Mastectomy at first\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3461 (40.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e140(46.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e74 (29.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e47 (44.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e14 (31.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eBreast-canservating surgery (BCS), then simple Mastectomy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e369(4.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e10(3.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e5(2.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e3(2.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e2(4.4%)\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cp\u003eTable\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e summarizes the 1-, 3-, and 5-year OS and DFS outcomes for breast cancer subtypes across TNM stages. Invasive lobular carcinoma and mucinous tumors exhibited remarkable 100% OS rates in stage I, while papillary tumors maintained 100% OS rates for 1 and 3 years (Fig.\u0026nbsp;\u003cspan\u003e1\u003c/span\u003e). In stage II, all three subtypes (invasive lobular carcinoma, mucinous, and papillary) maintained 100% OS rates for 1, 3, and 5 years (Fig.\u0026nbsp;2). In stage III, invasive lobular carcinoma demonstrated 100% 1-year OS and invasive carcinoma with medullary features maintained 100% OS rates for 1, 3, and 5 years. Nevertheless, other breast tumor subtypes exhibited less than 100% OS rates across all three stages (Fig.\u0026nbsp;3). A statistical analysis of OS in TNM stage I failed to reveal a significant association with breast cancer subtypes (P value\u0026thinsp;=\u0026thinsp;0.69). Conversely, OS rates in stages II and III were significantly different among breast cancer subtypes (P value\u0026thinsp;=\u0026thinsp;0.03 and 0.02, respectively). Patients with invasive carcinoma with medullary features tumor exhibited 100% DFS rates at 1 and 3 years of follow-up. Mucinous and papillary tumors demonstrated 100% DFS rates at 1, 3, and 5 years of follow-up in TNM stage 1 (Fig.\u0026nbsp;4). Mucinous tumors also maintained 100% DFS rates at 1, 3, and 5 years of follow-up in TNM stage 2 (Fig.\u0026nbsp;5), while invasive carcinoma with medullary features tumor displayed 100% DFS rates at 1, 3, and 5 years of follow-up in TNM stage 3 (Fig.\u0026nbsp;6). Other breast tumor subtypes exhibited DFS rates below 100% across the three stages. However, none of these differences were statistically significant (Table\u0026nbsp;\u003cspan\u003e3\u003c/span\u003e).\u003c/p\u003e\n\u003cdiv\u003e\n \u003ctable id=\"Tab3\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 3\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eOverall survival and Disease Survival rate according to breast cancer subtypes at each TNM Stage.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003ccolgroup cols=\"10\"\u003e\u003c/colgroup\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" colspan=\"2\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eOverall Survival times (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value*\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" colspan=\"3\"\u003e\n \u003cp\u003eDisease Survival times (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"2\"\u003e\n \u003cp\u003eP value*\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"6\"\u003e\n \u003cp\u003eStage1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e1\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e3\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e\u003cstrong\u003e5\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.69\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.32\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einvasive lobular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e84\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive carcinoma with medullary features\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive papillary carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eStage2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e91\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einvasive lobular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive carcinoma with medullary features\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e96\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive papillary carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e90\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003eStage 3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e95\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e92\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\" rowspan=\"5\"\u003e\n \u003cp\u003e0.02\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e81\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e76\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\" rowspan=\"5\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003einvasive lobular carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e93\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e82\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e71\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e65\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive carcinoma with medullary features\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e100\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003emucinous\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eInvasive papillary carcinoma\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003e-\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"10\"\u003e** Wilcoxon (Gehan) test\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003c/div\u003e\n\u003cdiv\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eBC is a multifaceted and heterogeneous disease influenced by a range of clinical, pathological, and biological factors that exhibit variability across different populations \u003csup\u003e\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u003c/sup\u003e. These prognostic factors play a crucial role in the management of breast cancer. Therefore, to gain a deeper understanding of breast cancer and its molecular subtypes, we conducted an analysis of 9310 breast cancer cases.\u003c/p\u003e \u003cp\u003eOur study determined that the age at breast cancer diagnosis ranged from 22 to 85 years, with a mean of 48.93\u0026thinsp;\u0026plusmn;\u0026thinsp;11.72 years. This finding is consistent with the results of earlier studies \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e, \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e\u003c/sup\u003e. However, in Western and Asian countries, breast cancer typically occurs at a later age \u003csup\u003e\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e\u003c/sup\u003e. The age at diagnosis is a crucial prognostic factor, as tumors diagnosed in younger individuals tend to be more aggressive and/or less responsive to treatment \u003csup\u003e\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e\u003c/sup\u003e. Several factors may influence the variation in age at diagnosis, including population characteristics, genetic predisposition, and environmental factors \u003csup\u003e\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e\u003c/sup\u003e. Our study also revealed a statistically significant difference in mean age at diagnosis among various breast cancer subtypes (P\u0026thinsp;\u0026gt;\u0026thinsp;0.003). Patients with Invasive papillary carcinoma subtypes were generally older than those with other subtypes (57.24\u0026thinsp;\u0026plusmn;\u0026thinsp;12.92) years. Invasive papillary carcinoma is classified as a low-grade carcinoma \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e. Owing to the rarity of the disease and the complexity of its histological classification, there is no universally accepted consensus on the management of patients with invasive papillary carcinoma \u003csup\u003e\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e\u003c/sup\u003e. Interestingly, invasive papillary carcinoma is relatively more prevalent among males \u003csup\u003e\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e\u003c/sup\u003e which is consistent with our observation of invasive papillary carcinoma breast cancer subtypes in male patients. Our study also reported a significantly higher female-to-male ratio (99.43%) compared to other studies \u003csup\u003e\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur study identified invasive ductal carcinoma as the predominant histological subtype, aligning with the findings of most previous studies on breast cancer \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Patients with invasive carcinoma with medullary features (53.0%) and invasive papillary carcinoma (57.8%) exhibited a greater tendency for right breast involvement. Conversely, patients with invasive ductal carcinoma (51.3%), invasive lobular carcinoma (55.9%), and mucinous tumor (54.4%) showed a higher prevalence of left breast involvement. A statistically significant correlation was established between the involved breast side and tumor type (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Numerous studies have delved into the possible reasons for the observed left-sided predominance in breast cancer \u003csup\u003e\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e\u003c/sup\u003e. Furthermore, a study reported that patients with left-sided breast cancer treated with radiation therapy were at an increased risk of cardiovascular complications and historically had worse outcomes \u003csup\u003e\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOver half of all tumor sizes across subtypes fell within the 2 to 5 centimeter range, with tumor size less than 2 centimeters being more prevalent among patients with invasive papillary carcinoma (37.5%). Tumor size greater than 5 centimeters was more common among patients with mucinous tumors (11.8%). A statistically significant difference in tumor size was observed between the subgroups (P\u0026thinsp;=\u0026thinsp;0.003). Moreover, tumor size at the time of diagnosis was significantly correlated with tumor subtype (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). According to the \"Size-Note\" hypothesis, tumor size and the number of positive lymph nodes independently contribute to the lethality of invasive breast cancer \u003csup\u003e\u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e\u003c/sup\u003e. Smaller tumors (diameter less than 2 cm) exhibit a lower risk of axillary lymph node metastasis, and tumor size serves as an independent predictor of nodal positivity \u003csup\u003e\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e\u003c/sup\u003e. Therefore, we propose that tumor size can predict survival by influencing regional lymph node metastasis, as larger tumors tend to invade adjacent tissues more extensively, increasing the likelihood of lymph node involvement \u003csup\u003e\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u003c/sup\u003e. In Western countries, the majority of breast tumors are less than 2 cm in diameter, reflecting the early detection of the disease \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e\u003c/sup\u003e. However, the percentage of tumors larger than 2 cm in our study was higher compared to other studies \u003csup\u003e\u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e, \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eOur study revealed that 60.9% of invasive ductal carcinoma cases and 58.3% of invasive lobular carcinoma cases exhibited grade II histology. The majority of patients with mucinous (75.8%) and invasive papillary carcinoma (52.0%) tumors had grade I histology. Notably, more than half of patients with invasive carcinoma with medullary features (57.1%) had grade III histology. This finding contrasts with studies reporting a lower percentage of grade II tumors and a higher level of grade III histology \u003csup\u003e\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e\u003c/sup\u003e. Histological grading serves as a powerful prognostic factor and is an integral component of several clinical decision-making tools, such as the Nottingham prognostic index and Adjuvant online \u003csup\u003e\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e\u003c/sup\u003e. Interestingly, specific genetic and transcriptomic features of breast cancers were associated with distinct tumor grades \u003csup\u003e\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e\u003c/sup\u003e. However, a multicenter study indicated that only lymph node status and lymphovascular invasion influenced prognosis, not tumor size or histological grade \u003csup\u003e\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eTNM stage 2 was the most frequently observed stage across all breast cancer subtypes, and a statistically significant association was established between TNM stage and breast cancer tumor g staging which was devised to classify the extent of local, regional, and distant disease involvement at the time of initial treatment, providing objective and enduring descriptions of the disease \u003csup\u003e\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e\u003c/sup\u003e. Categories with similar prognostic significance can be combined to define the disease stages \u003csup\u003e\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e\u003c/sup\u003e. However, our findings contrast with those of other studies, which have reported an unclear relationship between tumor stage and clinical outcome across the breast cancer patient population \u003csup\u003e\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e\u003c/sup\u003e. This implies that TNM staging alone may not be an adequate predictor of therapeutic outcomes in breast cancer patients, not because of limitations in the staging system but rather due to the distinct biological characteristics of TNBC compared to other subtypes.\u003c/p\u003e \u003cp\u003eOur study determined that luminal A molecular subtype was widespread across all breast cancer histological subtypes, and luminal B was more prevalent among invasive ductal carcinoma than other subtypes (18.7%), consistent with the results of another study \u003csup\u003e\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e\u003c/sup\u003e. However, our findings differ from those of other studies, which reported luminal B tumors as the most common subtype \u003csup\u003e\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e\u003c/sup\u003e. Genetic, racial, and environmental factors may explain these inconsistencies, and variations in diagnostic facilities may also contribute. Our findings corroborate those of other studies \u003csup\u003e\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e\u003c/sup\u003e, in demonstrating a higher frequency of triple negativity among invasive carcinoma with medullary features than other subtypes (35.4%). A statistically significant difference was observed in the distribution of molecular subtypes among breast cancer histological subtypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e \u003cp\u003eBreast cancer is characterized by a distinct recurrence pattern. Sopik et al. demonstrated that the majority of recurrences and deaths occur within the first five years after diagnosis, with a particularly high risk in the first three years \u003csup\u003e\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e\u003c/sup\u003e. The risk of recurrence steeply declines after this initial period. Conversely, in another group of patients, the risk of recurrence is low within the first five years after diagnosis, but distant recurrences continue to accumulate for up to 17 years \u003csup\u003e\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e\u003c/sup\u003e. This study revealed that the majority of patients (more than 70% in all cancer subtypes) remained recurrence-free during the investigated time interval. Visceral organs and the brain are the most common sites of recurrence in breast cancer \u003csup\u003e\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eChemotherapy has been demonstrated to improve survival outcomes for breast cancer patients, while the role of radiotherapy remains a subject of debate. In our study, postoperative chemotherapy was more frequently administered to patients with invasive ductal carcinoma (81.5%) and invasive carcinoma with medullary features (85.4%) subtypes. While multiple studies have confirmed the beneficial effects of radiotherapy on overall survival (OS) in breast cancer patients \u003csup\u003e\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e\u003c/sup\u003e, others have suggested that its benefits may be limited. For instance, Chua et al. found that radiotherapy effectively reduced local-regional recurrences but not distant recurrences \u003csup\u003e\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e\u003c/sup\u003e. Haque et al. proposed that mastectomy combined with radiotherapy was associated with improved OS only in high-risk patients (T3\u0026ndash;4 or node-positive), whereas lumpectomy with radiotherapy was beneficial in both high- and low-risk cohorts (T1\u0026ndash;2N0) \u003csup\u003e\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e\u003c/sup\u003e. Chest and axillary radiotherapy was performed in most breast cancer subtypes in our study. The majority of study participants received hormonal therapy, except for women with invasive carcinoma with medullary features (61.7% not treated with hormonal therapy). A 2011 meta-analysis revealed that 5-year adjuvant hormonal therapy (HT) effectively reduces the risk of breast cancer recurrence and mortality \u003csup\u003e\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e\u003c/sup\u003e. Non-compliance with and early cessation of HT are linked to elevated relapse and mortality rates \u003csup\u003e\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e\u003c/sup\u003e. BCS was the most prevalent surgical procedure across all breast cancer subtypes (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Mastectomy was the second most common treatment approach. Studies have documented an increase in the utilization of BCS following neoadjuvant treatment and the gradual expansion of treatment options to less toxic targeted therapies \u003csup\u003e\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e\u003c/sup\u003e. The conversion rate from mastectomy to BCS exceeded 50% after neoadjuvant chemotherapy (NACT) plus dual-target therapy in the Asian population \u003csup\u003e\u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eThis study revealed that invasive lobular carcinoma and invasive papillary carcinoma and mucinous tumors displayed exceptional 1, 3, and 5-year OS rates (100%), compared to other subtypes at stage 1. In stage 2, invasive lobular carcinoma and mucinous, and invasive papillary carcinoma demonstrated improved 1, 3, and 5-year OS. At stage 3, invasive lobular carcinoma tumor exhibited higher 1-year OS rates, and invasive carcinoma with medullary features displayed higher 1, 3, and 5-year OS rates. Statistically significant differences in OS were observed among breast cancer subtypes within TNM stages 2 and 3 (P value\u0026thinsp;=\u0026thinsp;0.03 and 0.02, respectively). The current literature suggests an OS of 92% in target patients, implying higher OS rates in our study compared to the findings reported by Carey et al. \u003csup\u003e\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e \u003cp\u003eInvasive carcinoma with medullary features achieved the highest 1-year, 3-year, and 5-year DFS rates (100%). Mucinous and invasive papillary carcinoma demonstrated the highest 1-year, 3-year, and 5-year DFS rates in TNM stage 1. Mucinous tumors exhibited the highest 1-year, 3-year, and 5-year DFS rates in TNM stage 2, followed by invasive carcinoma with medullary features.\u003c/p\u003e \u003cp\u003eThere is a paucity of studies investigating OS and DFS of breast tumors classified by histological subtypes according to TNM stages. However, some studies have explored OS and DFS of breast cancers categorized by molecular subtypes. One such study \u003csup\u003e\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e\u003c/sup\u003e examined the death rate among molecular subgroups in 24 breast cancer patients following a follow-up period of up to 92 months. Moreover, Zanguri et al. reported the 5-year OS and DFS rates in the Invasive papillary carcinoma group were better than those in the Invasive ductal carcinoma group \u003csup\u003e\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u003c/sup\u003e.\u003c/p\u003e"},{"header":"Limitations of the study","content":"\u003cp\u003eThis study's limitations include its retrospective design and we had big sample size if all included patients completed their follow-up periods.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study revealed that Invasive ductal carcinoma was the most common histological subtype, with the majority of cases being stage II that serves as a powerful prognostic factor for BC. Luminal A molecular subtype was widespread across all breast cancer histological subtypes, and luminal B was more prevalent among invasive ductal carcinoma than other subtypes (18.7%). The incidence of multifocal breast tumors was relatively low among patients with ICMF, Furthermore, the cases exhibited detectable differences in adjuvant therapy that chemotherapy has been demonstrated to improve survival outcomes for breast cancer patients. This study revealed that invasive lobular carcinoma and invasive papillary carcinoma and mucinous tumors displayed exceptional 1, 3, and 5-year OS rates (100%) at stage 1. In stage 2, invasive lobular carcinoma and mucinous, and invasive papillary carcinoma demonstrated improved 1, 3, and 5-year OS. At stage 3, invasive lobular carcinoma tumor exhibited higher 1-year OS rates, and invasive carcinoma with medullary features displayed higher 1, 3, and 5-year OS rates. Invasive carcinoma with medullary features has the highest DFS rate across all stages, while mucinous and invasive papillary carcinoma have the highest DFS rates in TNM stage 1. Mucinous tumors have the highest DFS rates in TNM stage 2, followed by invasive carcinoma with medullary features.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgment:\u003c/strong\u003e\u003c/p\u003e\n\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\n\u003cp\u003e\u003cstrong\u003eAuthor contributions:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll authors contributed to the study\u0026apos;s conception and design. Material preparation, data collection, and analysis were performed by Morteza Amestejani, Vahid Zangouri, Iman Deylami, and Souzan Soufizadeh Balaneji\u003csup\u003e3\u003c/sup\u003e. The first draft of the manuscript was written by Morteza Amestejani and Seyed Amin Mousavi. All authors commented on previous versions of the manuscript. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis project is financially supported by the vice chancellor of research, Shiraz University of Medical Sciences (Grant No.97-17376).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe original contributions presented in the study are included in the article/ Supplementary Material,\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval and consent to participate\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis 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(No.: IR.SUMS.MED.REC.1397.226)\u003cstrong\u003e.\u0026nbsp;\u003c/strong\u003eThe 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\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no conflict of interest.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFerlay J, Colombet M, Soerjomataram I, Mathers C, Parkin DM, Pi\u0026ntilde;eros M, et al. Estimating the global cancer incidence and mortality in 2018: GLOBOCAN sources and methods. International journal of cancer. 2019;144(8):1941-53.\u003c/li\u003e\n\u003cli\u003eŁukasiewicz S, Czeczelewski M, Forma A, Baj J, Sitarz R, Stanisławek A. 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Drugs. 2017;77:1313-36.\u003c/li\u003e\n\u003cli\u003eChang Y-K, Co M, Kwong A. Conversion rate from mastectomy to breast conservation after neoadjuvant dual target therapy for HER2-positive breast cancer in the Asian population. Breast Cancer. 2020;27:456-63.\u003c/li\u003e\n\u003cli\u003eEngstr\u0026oslash;m MJ, Opdahl S, Hagen AI, Romundstad PR, Akslen LA, Haugen OA, et al. Molecular subtypes, histopathological grade and survival in a historic cohort of breast cancer patients. Breast cancer research and treatment. 2013;140:463-73.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Breast cancer, Tumor size, Lymph node, Histological grade, Immunohistochemical markers","lastPublishedDoi":"10.21203/rs.3.rs-3890579/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3890579/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eBreast cancer is often classified into subtypes using immunohistochemical markers. This study aimed to compare the histopathological features, prognostic indicators, and clinical outcomes of diverse breast cancer subtypes.\u003c/p\u003e\u003ch2\u003ePatients and methods:\u003c/h2\u003e \u003cp\u003eA retrospective study was undertaken and all patients of various subtype of breast cancer over a 5 year period were included. Clinicopathological characteristics, including tumor size, lymph node (LN) metastasis, histological grade, immunohistochemical markers (estrogen receptor (ER), progesterone receptor (PR), and human epidermal growth factor receptor 2 (HER2neu status), TNM staging, lymphovascular invasion (LVI), perineural invasion (PNI), and overall survival (OS),and Disease free survival(DFS) were comprehensively evaluated.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eOf the 9310 individuals diagnosed with breast cancer, a vast majority (99.4%) was females. Patients with invasive papillary carcinoma tumor subtypes presented with an older mean age (57.24\u0026thinsp;\u0026plusmn;\u0026thinsp;12.92) years. Tumor grade exhibited a statistically significant correlation with tumor subtype (P\u0026thinsp;\u0026lt;\u0026thinsp;0.001). Invasive lobular carcinoma (94.8%), IPC (94.3%), and mucinous carcinoma (93.6%) demonstrated excellent OS rates in stages I, II, and III. However, ICMP (94.6%) exhibited superior OS in stages II and III. In terms of DFS, IPC (94.2%), mucinous carcinoma (94.5%), and ICMP (93.6%) showed favorable DFS rates in TNM stages 1 and 2, with ICMP maintaining exceptional DFS rates in stage 3.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eInvasive carcinoma with medullary features has the highest DFS rate across all stages, while mucinous and invasive papillary carcinoma have the highest DFS rates in TNM stage 1. Mucinous tumors have the highest DFS rates in TNM stage 2, followed by invasive carcinoma with medullary features. Invasive lobular carcinoma, invasive papillary carcinoma, and mucinous tumors had excellent overall survival (OS) rates in stages I, II, and III. Invasive carcinoma with medullary features had superior OS in stages II and III.\u003c/p\u003e","manuscriptTitle":"Comparison of clinicopathologic characteristics and survival outcomes of various subtypes of breast cancer","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-14 18:27:08","doi":"10.21203/rs.3.rs-3890579/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"562c8506-5766-4177-ab5f-bc1d56d0f20c","owner":[],"postedDate":"February 14th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-03-18T06:23:39+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-14 18:27:08","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3890579","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3890579","identity":"rs-3890579","version":["v1"]},"buildId":"pf3fE39SIOqb-0xH_OWvX","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}