Prognostic Analysis of Invasive Ductal Carcinoma of the Breast in Ethnic Minorities in Northeast China

Prognostic Analysis of Invasive Ductal Carcinoma of the Breast in Ethnic Minorities in Northeast China | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prognostic Analysis of Invasive Ductal Carcinoma of the Breast in Ethnic Minorities in Northeast China Xiaoming Li, Quan Yuan, Yupeng Sha, Yixin Liu, Yige Lu, Xianyu Zhang, and 2 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8297694/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 10 You are reading this latest preprint version Abstract Background Invasive ductal carcinoma (IDC) is the most common pathological subtype of breast cancer (BC). The prognosis of minority IDC in Northeast China has not been fully studied, which limits the demand for equal access to specific therapies among different ethnic groups. Methods Retrospective collection of cases from medical centers in Northeast China, gathering patients with primary IDC of ethnic minorities (aged ≥ 18 years) who visited between 2004 and 2024. Follow-up was conducted every six months. Data analysis was performed from October 2025 to November 2025. Results This study collected data from 847 relevant patients. The 5-year overall survival (OS) rate for all samples was 78.45%, and the 5-year event-free survival (EFS) rate was 64.84%. HR + HER2- cases were more likely to be diagnosed early (TNM Stage IA: 26.17%; IIA: 37.11%). HR-HER2- had the poorest overall prognosis, with a higher mean Ki-67 at diagnosis (HR-HER2-:42.81). In long-term survival, HR-HER2- and HR-HER + showed similar outcomes. Under different immunohistochemistry (IHC) conditions, the statistical significance for Manchu and Daur was not significant. The prognostic trend for Hui was no different from the overall trend. Conclusions The early detection rate of these ethnic minorities was lower than the average level of China, and the overall prognosis was worse compared to that of Chinese IDC patients. There were also significant differences in the prognostic outcomes among the five ethnic minority groups. China Ethnic and racial minorities Immunohistochemistry Invasive ductal carcinoma Prognosis Figures Figure 1 Figure 2 Figure 3 Background Breast cancer (BC) ranks fourth globally as a cause of cancer-related deaths and stands as the most prevalent cancer among women worldwide. International BC research often categorizes patients by ethnicity and geographic location.( 1 – 5 ) Even within the same BC subtype, significant variations in incidence, mortality rates, and various prognostic indicators are observed across different patient populations.( 6 , 7 ) Consequently, as research advances, there is a growing emphasis on more refined classification criteria and increased attention to minority groups. China is a multi-ethnic nation; while the majority of its population belongs to the East Asian ethnic group, distinct ethnic communities residing even within the same geographic area maintain unique lifestyles, dietary habits, and cultural practices. Invasive ductal carcinoma (IDC) represents the predominant pathological type, accounting for approximately 70% of all diagnosed invasive breast cancers.( 8 ) Originating from the epithelial cells lining the mammary ducts, IDC exhibits heightened invasiveness and a greater propensity for local or distant metastasis due to its ability to breach the mammary duct basement membrane and infiltrate surrounding stromal tissues. Its high clinical incidence and distinct prognostic outcomes compared to other pathological subtypes make IDC a focal point in BC research and clinical prognostic analyses.( 8 , 9 ) According to the 2020 national census, the northeastern region of China is home to all 55 ethnic minorities. Along the Songhua River basin, six ethnic groups have residential populations exceeding 3,000: the Manchu, Korean, Mongolian, Hui, Daur, and Hezhen, in descending order of population size. These are all indigenous ethnic minorities of the region. The Northeast serves as the cultural birthplace of the Manchu and Korean peoples in China, and the Daur constitutes a unique ethnic minority of Heilongjiang Province. This demographic composition provides an adequate sample size for investigating various aspects of BC in these ethnic minority patients and studying potential differences in BC subtype manifestations among China's diverse ethnic groups. To our knowledge, previous studies have typically focused on single ethnic minorities and have not incorporated data collection and evaluation across multiple ethnic groups within a specific geographic area. Therefore, we retrospectively collected data on IDC patients from five major ethnic minorities treated at a large academic medical center in Northeast China between 2004 and 2024. Through long-term follow-up, we analyzed the event-free survival (EFS) and overall survival (OS) of patients from each ethnic group following appropriate treatment and further evaluated potential differences in BC subtypes among these minority populations. Materials and Methods Patients This study enrolled 960 patients (≥ 18 years) with newly diagnosed primary IDC from Chinese ethnic minorities (non-Han) who attended the Affiliated Tumor Hospital of Harbin Medical University between January 1, 2004, and December 31, 2024. We collected available patient data, including blood test results, TNM staging (per the American Joint Committee on Cancer [AJCC] 8th Edition Staging System), and immunohistochemistry (IHC) findings. Patients were categorized into four subtypes based on initial IHC profiles: hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (ERBB2, also known as HER2)-negative, HR-positive/HER2-positive, HR-negative/HER2-positive, and triple-negative breast cancer (TNBC). HR positivity was defined as estrogen receptor (ER) or progesterone receptor (PR) expression ≥ 1%. HER2 status was determined by IHC scoring and FISH results: scores of 0, 1+, or 2 + with negative FISH indicated HER2 negativity; scores of 2 + with positive FISH or 3 + indicated HER2 positivity (in accordance with the Chinese Society of Clinical Oncology [CSCO] Breast Cancer Diagnosis and Treatment Guidelines).( 10 ) Exclusion criteria: Of the 960 Chinese ethnic minority patients, 113 were excluded for four reasons: ( 1 ) 15 with undetermined BC subtypes; ( 2 ) 26 from ethnic groups with extremely small sample sizes (e.g., Hezhen); ( 3 ) 62 with pathological types other than IDC; and ( 4 ) 10 lost to follow-up. Consequently, data from 847 patients were included in the study analysis (Fig. 1 ). Patients will undergo follow-up every six months after receiving appropriate treatment through telephone calls, medical records, and instant messaging platforms to collect data on EFS and OS for each patient. Following standardized treatment, EFS is defined as the time interval from treatment completion until the first occurrence of specific events, including tumor recurrence, tumor progression, or patient death. OS is defined as the time interval from treatment completion until death from any cause. All data in this retrospective study were anonymized, and thus informed consent was not obtained from patients. This study was conducted in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee of the Affiliated Tumor Hospital of Harbin Medical University (Ethical No. KY2022-52). Statistical Analysis Data analysis was conducted between October 15 and November 5, 2025. Categorical baseline characteristics across different subtypes were compared using the chi-square test, while continuous variables were analyzed via the t-test. Kaplan-Meier survival curves were constructed to estimate median EFS and OS, with statistical significance determined by 95% confidence interval (CI). Stratified analyses were further performed by ethnic minority subgroups to evaluate subtype-specific effects. All statistical computations were executed using R software (version 4.3.1). Results Among the 847 participants, the cohort was categorized into four molecular subtypes: 126 (15%) HR-HER2- cases, 83 (10%) HR-HER2 + cases, 512 (60%) HR + HER2- cases, and 126 (15%) HR + HER2 + cases (Table 1 ). Statistical analysis revealed no significant differences in most hematological parameters or ethnic distribution across the different IHC-defined BC subtypes. However, notable variations were observed in relation to tumor TNM staging characteristics. Table 1 Clinical characteristics of patients Variables Total HR-HER2- HR-HER2+ HR + HER2- HR + HER2+ P (n = 847) (n = 126) (n = 83) (n = 512) (n = 126) BMI(kg/m²) 24.08 ± 3.24 24.19 ± 3.21 23.96 ± 3.13 24.13 ± 3.30 23.84 ± 3.13 0.792 ALT(U/L) 23.84 ± 20.36 24.68 ± 18.52 23.77 ± 16.49 23.17 ± 16.52 25.77 ± 34.07 0.591 AST(U/L) 25.34 ± 25.38 25.32 ± 14.66 30.53 ± 52.45 24.18 ± 17.62 26.71 ± 32.33 0.178 Gtp(U/L) 38.36 ± 83.94 47.96 ± 111.83 41.91 ± 79.37 35.24 ± 74.56 39.06 ± 90.48 0.474 LDH(U/L) 184.69 ± 105.40 204.46 ± 114.62 187.82 ± 66.71 174.59 ± 42.65 203.91 ± 224.71 0.004 ALP(U/L) 90.86 ± 68.08 101.08 ± 106.35 91.25 ± 52.24 87.22 ± 50.00 95.19 ± 88.72 0.186 TBil(umol/L) 14.17 ± 25.59 14.62 ± 28.60 18.60 ± 42.85 13.73 ± 24.10 12.63 ± 6.07 0.381 DBil(umol/L) 4.25 ± 21.89 5.39 ± 27.82 5.83 ± 22.28 4.08 ± 22.83 2.73 ± 1.44 0.704 IBil(umol/L) 9.83 ± 7.73 9.15 ± 5.11 12.61 ± 20.31 9.53 ± 4.21 9.92 ± 5.36 0.006 TP(g/L) 74.72 ± 15.79 77.13 ± 39.07 74.85 ± 5.41 74.39 ± 5.36 73.64 ± 6.04 0.301 ALB(g/L) 44.37 ± 17.19 47.06 ± 38.32 43.66 ± 4.10 44.21 ± 11.04 42.84 ± 3.41 0.233 GLOB(g/L) 30.62 ± 4.74 29.99 ± 4.87 31.07 ± 5.02 30.65 ± 4.53 30.80 ± 5.21 0.363 A/G 1.48 ± 0.64 1.66 ± 1.51 1.45 ± 0.28 1.46 ± 0.28 1.43 ± 0.31 0.013 GLU(mmol/L) 5.53 ± 1.46 5.83 ± 1.98 5.51 ± 1.53 5.49 ± 1.36 5.41 ± 1.16 0.087 Urea(mmol/L) 5.09 ± 2.38 4.98 ± 1.41 5.28 ± 1.45 5.15 ± 2.83 4.84 ± 1.41 0.475 Crea(umol/L) 67.28 ± 12.47 68.46 ± 13.36 69.05 ± 10.77 66.83 ± 12.63 66.80 ± 11.90 0.301 UA(umol/L) 283.69 ± 99.90 293.02 ± 190.00 278.62 ± 65.39 284.37 ± 73.73 274.90 ± 78.97 0.511 TCO2(mmol/L) 26.64 ± 10.42 26.68 ± 2.90 27.14 ± 3.23 26.64 ± 13.16 26.29 ± 3.23 0.954 K(mmol/L) 4.38 ± 5.67 4.14 ± 0.49 4.20 ± 0.43 4.53 ± 7.28 4.12 ± 0.40 0.826 NA(mmol/L) 140.27 ± 7.22 139.43 ± 12.90 140.99 ± 2.88 140.29 ± 6.46 140.54 ± 3.08 0.439 CL(mmol/L) 103.82 ± 3.42 103.40 ± 3.08 103.66 ± 3.25 103.82 ± 3.23 104.37 ± 4.44 0.151 CA(mmol/L) 2.84 ± 9.12 2.35 ± 0.17 2.37 ± 0.22 2.69 ± 4.88 4.24 ± 21.53 0.295 P(mmol/L) 1.12 ± 0.18 1.15 ± 0.17 1.12 ± 0.18 1.12 ± 0.18 1.13 ± 0.22 0.41 MG(mmol/L) 0.94 ± 0.12 0.93 ± 0.13 0.93 ± 0.12 0.95 ± 0.11 0.92 ± 0.11 0.073 WBC(10^9/L) 7.23 ± 20.29 6.68 ± 2.45 6.70 ± 2.01 7.66 ± 26.04 6.38 ± 1.98 0.896 LYM(10^9/L) 2.19 ± 7.32 1.99 ± 0.77 2.05 ± 0.66 2.33 ± 9.40 1.91 ± 0.71 0.919 NEU(10^9/L) 4.15 ± 2.67 4.55 ± 4.00 4.10 ± 1.71 4.13 ± 2.57 3.87 ± 1.72 0.24 MONO(10^9/L) 0.42 ± 0.22 0.43 ± 0.22 0.43 ± 0.18 0.41 ± 0.23 0.42 ± 0.16 0.754 EOS(10^9/L) 0.11 ± 0.11 0.12 ± 0.12 0.11 ± 0.09 0.11 ± 0.12 0.10 ± 0.08 0.875 BASO(10^9/L) 0.03 ± 0.03 0.04 ± 0.05 0.03 ± 0.02 0.03 ± 0.02 0.03 ± 0.02 0.11 RBC(10^12/L) 4.45 ± 0.49 4.38 ± 0.54 4.46 ± 0.39 4.48 ± 0.49 4.42 ± 0.48 0.203 HGB(g/L) 134.04 ± 37.16 131.53 ± 15.93 135.02 ± 11.03 135.53 ± 46.07 129.87 ± 17.33 0.386 PLT(10^9/L) 263.09 ± 71.15 259.62 ± 74.09 251.45 ± 51.73 266.68 ± 71.97 259.63 ± 75.33 0.248 Ki-67 26.89 ± 19.88 42.81 ± 24.04 34.98 ± 17.65 19.98 ± 16.09 33.73 ± 17.06 < .001 Ethnicity, n(%) 0.798 Daur 44 (5.19) 7 (5.56) 2 (2.41) 28 (5.47) 7 (5.56) Hui 138 (16.29) 15 (11.90) 15 (18.07) 90 (17.58) 18 (14.29) Korean 128 (15.11) 22 (17.46) 10 (12.05) 80 (15.62) 16 (12.70) Manchu 411 (48.52) 66 (52.38) 43 (51.81) 235 (45.90) 67 (53.17) Mongolian 126 (14.88) 16 (12.70) 13 (15.66) 79 (15.43) 18 (14.29) N, n(%) < .001 0 414 (48.88) 57 (45.24) 26 (31.33) 284 (55.47) 47 (37.30) 1 222 (26.21) 35 (27.78) 23 (27.71) 132 (25.78) 32 (25.40) 2 132 (15.58) 21 (16.67) 20 (24.10) 62 (12.11) 29 (23.02) 3 79 (9.33) 13 (10.32) 14 (16.87) 34 (6.64) 18 (14.29) M, n(%) 0.149 0 825 (97.40) 120 (95.24) 81 (97.59) 503 (98.24) 121 (96.03) 1 22 (2.60) 6 (4.76) 2 (2.41) 9 (1.76) 5 (3.97) T, n(%) < .001 0 2 (0.24) 1 (0.79) 0 (0.00) 1 (0.20) 0 (0.00) 1 250 (29.52) 28 (22.22) 14 (16.87) 181 (35.35) 27 (21.43) 1mic 13 (1.53) 1 (0.79) 2 (2.41) 10 (1.95) 0 (0.00) 2 536 (63.28) 88 (69.84) 58 (69.88) 299 (58.40) 91 (72.22) 3 33 (3.90) 4 (3.17) 8 (9.64) 17 (3.32) 4 (3.17) 4 13 (1.53) 4 (3.17) 1 (1.20) 4 (0.78) 4 (3.17) Stage, n(%) < .001 IA 179 (21.13) 21 (16.67) 8 (9.64) 134 (26.17) 16 (12.70) IIA 287 (33.88) 40 (31.75) 22 (26.51) 190 (37.11) 35 (27.78) IIB 152 (17.95) 26 (20.63) 18 (21.69) 83 (16.21) 25 (19.84) IIIA 128 (15.11) 19 (15.08) 19 (22.89) 62 (12.11) 28 (22.22) IIIB 6 (0.71) 2 (1.59) 0 (0.00) 3 (0.59) 1 (0.79) IIIC 73 (8.62) 12 (9.52) 14 (16.87) 31 (6.05) 16 (12.70) IV 22 (2.60) 6 (4.76) 2 (2.41) 9 (1.76) 5 (3.97) A total of 414 patients (48.88%) presented with no lymph node involvement at diagnosis (N0). The HR + HER2- subtype showed the highest proportion of N0 cases (55.47%). Conversely, in BC cases with four or more positive lymph nodes (N2/N3), the HR + HER2- subtype was less frequently represented: for N2, the proportions were HR-HER2- (16.67%), HR-HER2+ (24.10%), HR + HER2+ (23.02%), and HR + HER2- (12.11%); for N3, the respective proportions were HR-HER2- (10.32%), HR-HER2+ (16.87%), HR + HER2+ (14.29%), and HR + HER2- (6.64%). No significant differences in distribution were observed among the four subtypes for N1 status. Regarding tumor size, T2 stage was the most commonly diagnosed n = 536, 63.28%. The HR + HER2- subtype demonstrated a higher detection rate at T1 stage compared to other subtypes, HR + HER2-: 35.35%; HR-HER2-: 22.22%; HR-HER2+: 16.87%; HR + HER2+: 21.43%, while showing lower frequencies in T2 and T4 stages. Clinically, HR + HER2- BC was more frequently diagnosed at early stages (TNM Stage IA: 26.17%; IIA: 37.11%). In contrast, HER2 + subtypes were more likely to present at Stage III HR-HER2+: 39.76%; HR + HER2+: 35.71%. Ki-67 proliferation index was significantly higher in TNBC and HER2 + subtypes compared to HR + HER2- BC (p < 0.001). TNBC (HR-HER2-) exhibited the highest mean Ki-67 value (42.81), which was 2.14 times that of HR + HER2- tumors (19.98). The HER2 + subtypes showed intermediate values, with HR-HER2+ (34.98) and HR + HER2+ (33.73) demonstrating 1.75-fold and 1.68-fold increases relative to HR + HER2- cases, respectively. Table 1 . Clinical characteristics of patients (At the end of the document text file) Survival outcomes were analyzed for all participants, with a maximum follow-up duration of 258 months from the time of initial diagnosis in early-stage patients. The entire cohort demonstrated a 5-year OS rate of 78.45% and a 5-year EFS rate of 64.84%. Statistically significant differences in prognosis were observed across molecular subtypes (Appendix Table 1). Specifically, HR + HER2- BC exhibited the most favorable median EFS (104.17 months; 95% CI, 97.53–117.73), whereas HR-HER2- BC showed the poorest prognosis (median EFS: 63.57 months; 95% CI, 48.53–88.53). Consistent with EFS data, HR + HER2- BC also had the longest median OS (121.83 months; 95% CI, 113.90–137.00), significantly outperforming HR-HER2- BC (median OS: 75.17 months; 95% CI, 62.23–94.80). HER2 + subtypes displayed intermediate prognostic outcomes, with HR-HER2 + BC showing marginally inferior survival compared to HR + HER2 + BC. As illustrated in Fig. 2 , HR + HER2- BC consistently demonstrated superior long-term survival. HR + HER2 + BC also conferred a statistically significant survival advantage over both HR-HER2- and HR-HER2 + subtypes, albeit with modest differences. Notably, the Kaplan-Meier curves for HR-HER2- and HR-HER2 + BC overlapped substantially, indicating comparable long-term survival trajectories between these two subtypes. To further investigate the impact of different ethnic backgrounds on the prognosis of breast cancer patients, we stratified the study subjects into single ethnic groups. Within the individual analyses of the Daur, Hui, Korean, Manchu, and Mongolian ethnicities, results revealed that although the Manchu group had the largest sample size n = 411, 48.52%, no significant correlations were observed in the median survival durations associated with molecular subtypes (Median EFS: p = 0.122; Median OS: p = 0.089) (Fig. 3 , Appendix Table 2). Contrary to the overall trend, Manchu patients with TNBC exhibited comparable prognostic outcomes to those with HER2 + breast cancer (p > 0.05), and demonstrated superior Median EFS when compared to HR-HER2 + subtype (HR-HER2-: 85.60 months; 95%CI, 48.53-116.13; HR-HER2+: 66.63 months; 95%CI, 54.30-97.27). Interestingly, the survival curves of the Manchu cohort indicated that the statistically significant advantage of HR + HER2- breast cancer over other subtypes was not as pronounced as observed in the overall assessment. Although the Hui, Mongolian, and Korean ethnic groups exhibited comparable sample sizes, their clinical outcomes differed substantially. Among the Korean and Hui populations, TNBC was associated with the shortest median EFS (Appendix Table 3). In contrast, Mongolian patients with HR-HER2- breast cancer demonstrated significantly better EFS outcomes (91.80 months; 95% CI, 34.77-NA) compared to those with HR-HER2 + subtype (65.60 months; 95% CI, 28.23-NA). Interestingly, no notable difference was observed in median OS between Mongolian HR-HER2- (75.17 months; 95% CI, 61.83-NA) and HR-HER2+ (75.70 months; 95% CI, 62.35-NA) subgroups (Appendix Table 4). Equally disappointing to the median OS of Korean TNBC (65.53 months; 95% CI, 29.93–94.63) was the HR + HER2 + breast cancer subtype, which showed a median OS of only 64.43 months (95%CI, 46.9-NA), whereas the HR-HER2 + subtype presented more favorable prognostic outcomes. Survival curve analyses of the remaining two ethnic groups indicated that the HR + HER2- subtype consistently conferred the optimal prognosis (Appendix Fig. 1). For the Daur population, statistical analysis revealed no significant differences in prognostic outcomes across different IHC subtypes for either median EFS (p = 0.304) or median OS (p = 0.400) (Appendix Table 5, Appendix Fig. 2). Discussion This study investigates the prognostic outcomes of invasive ductal carcinoma (IDC) among ethnic minorities in Northeast China. Among molecular subtypes, HR + tumors demonstrated the most favorable prognosis, while TNBC exhibited the poorest long-term outcomes, with HR-HER2 + showing comparable survival patterns to TNBC in extended follow-up. The overall cohort achieved a 5-year OS rate of 78.45% and 5-year EFS rate of 64.84%. Notably, Manchu patients, the largest subgroup, showed no significant differences in EFS or OS across subtypes. Hui patients displayed similar trends, whereas Korean HR-HER2 + tumors showed superior outcomes, contrasting with HR + HER2 + subtypes that exhibited OS rates comparable to TNBC. Mongolian HR-HER2 + tumors demonstrated the poorest EFS among this ethnic group. Minority subtype distributions aligned with national patterns, with Stage II tumors predominating (21.13% Stage I detection). This contrasts starkly with China's national Stage I detection rate (31.8%) and US figures (54.6%).( 11 ) While global 5-year OS ranges from 85–90% in developed countries to ~ 80% in East Asia,( 1 , 12 ) our cohort's 78.45% OS significantly trails. China's national IDC survival (92.9%), South Korea (88.8%), and US API populations (84.8%).( 13 – 15 ) These disparities highlight inadequate early screening and suboptimal treatment access among unscreened minority populations, necessitating improved screening initiatives, enhanced healthcare resources, and optimized treatment protocols. The Manchu population, genetically admixed with Han Chinese through centuries of cohabitation, showed no statistical survival differences across subtypes (P > 0.05). This may relate to unique cytochrome P-450 2D6 (CYP2D6) polymorphisms identified in Northeast Manchu populations,( 16 ) which impair tamoxifen metabolism to its active metabolite endoxifen. Reduced CYP2D6 activity.( 17 ) As demonstrated by Schroth et al., correlates with poorer EFS and DFS in tamoxifen-treated patients,( 18 ) potentially attenuating HR + prognostic advantages in this group. Genetically homologous to Korean Peninsula populations,( 19 – 21 ) Chinese Koreans displayed favorable outcomes in HR-HER2 + subtypes (10/128 patients), attributed to high pathologic complete response rates with chemotherapy/anti-HER2 targeting and superior treatment adherence. Conversely, HR + HER2 + subtypes exhibited TNBC-comparable OS, potentially due to dual endocrine/anti-HER2 resistance and limited benefit from HER2-targeted therapy in tumors with > 30% ER expression, hypothesized to result from signaling crosstalk despite insufficient corroborative evidence.( 22 ) Mongolian HR-HER2 + tumors (11 events among 13 patients) showed poorest outcomes, potentially linked to nomadic cultural influences delaying diagnosis and reducing adherence to HER2-directed therapies. Daur patients showed no prognostic differences across IHC subtypes, likely due to insufficient sample size. To our knowledge, this represents the first focused analysis of IDC disparities among Northeast China's ethnic minorities, addressing a critical research gap with significant clinical and preventive implications, supported by extensive follow-up. Limitations include inherent sample size constraints in minority populations despite prolonged (20 + year) follow-up, single-center recruitment introducing geographic bias, evolving HER2 testing standards (including FISH adoption) and trastuzumab insurance coverage (post-2017) potentially underestimating HER2 + incidence and treatment efficacy in earlier cohorts, and unmeasured confounding variables (socioeconomic status, education, lifestyle). Nevertheless, these findings underscore meaningful prognostic variations across ethnic minority IDC subtypes and guide future research directions. Conclusions This represents the first study investigating the prognosis of different IDC subtypes among multiple ethnic minorities in Northeast China. It reveals ethnic disparities in IHC profiles, along with lower early detection rates and poorer prognosis in minority IDC patients. Except for HR-HER2 + in Koreans, HR + HER2- consistently showed the most favorable prognosis across other ethnic groups. Among Manchus, no statistically significant prognostic differences were observed between the four molecular subtypes. The TNBC subtype was associated with poorer outcomes in most ethnicities; additionally, HR + HER2 + in Koreans and HR-HER2 + in Mongolians also demonstrated inferior OS. Abbreviations BC Breast Cancer CI Confidence Internal EFS Event-free Survival ER Estrogen Receptor HER2 Human epidermal growth factor receptor 2 HR Hormone Receptor IDC Invasive ductal carcinoma IHC Immunohistochemistry OS Overall Survival PR Progesterone Receptor TNBC Triple-negative breast cancer Declarations Ethics Statement This study has been granted approval by the Institutional Ethics Review Board of Harbin Medical University Cancer Hospital, under the ethic clearance number KY2022-52. All procedures involving human participants were performed in 1964 Helsinki Declaration and its later amendments or comparable ethical standards. Consent for publication Not applicable. Data Sharing Statement The data collected and analyzed in this study are available from the corresponding author and the first author upon reasonable request. Competing interests The authors declare no conflicts of interest. Author information Xiaoming Li, Quan Yuan and Yupeng Sha have contributed equally to this work and are co-first authors. Authors and Affiliations Department of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin 150000, Heilongjiang, China Xiaoming Li, Quan Yuan, Yupeng Sha, Yixin Liu, Yige Lu, Xianyu Zhang, Da Pang & Jiguang Han Corresponding authors Correspondence to Xianyu Zhang, Da Pang or Jiguang Han. Supplementary Information Supplementary material 1. Funding sources This research was funded by the Beijing Medical Award Foundation (Grant No. Yx7L-2023-0460-0199). Author Contribution XL: Writing–original draft, Investigation, Formal analysis, Visualization. QY: Writing–original draft, Investigation, Data curation. YS: Writing–original draft, Methodology, Validation. YXL: Resources, Data curation, Formal analysis. YGL: Resources, Software, Funding. XZ: Project administration, Supervision. DP: Validation, Funding acquisition, Writing–review & editing. JH: Conceptualization, Methodology, Writing–review & editing, Supervision, acquisition. Acknowledgement We convey our thanks to all the contributing authors for their significant contributions to the study. Our sincere gratitude is also due to the cancer patients who participated in this research, for their cooperation throughout follow-up. We are indebted to the Harbin Medical University Cancer Hospital for its support. Data Availability The data collected and analyzed in this study are available from the corresponding author and the first author upon reasonable request. References Bray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin. 2024;74(3):229–63. https://doi.org/10.3322/caac.21834 . Chotai N, Renganathan R, Uematsu T, Wang J, Zhu Q, Rahmat K, et al. 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Cancer Cell Int. 2025;25(1):77. https://doi.org/10.1186/s12935-025-03680-7 . Additional Declarations No competing interests reported. Supplementary Files Supplementarymaterial1.docx Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Mar, 2026 Reviews received at journal 22 Jan, 2026 Reviewers agreed at journal 22 Jan, 2026 Reviews received at journal 21 Dec, 2025 Reviewers agreed at journal 10 Dec, 2025 Reviewers invited by journal 10 Dec, 2025 Editor invited by journal 09 Dec, 2025 Editor assigned by journal 07 Dec, 2025 Submission checks completed at journal 07 Dec, 2025 First submitted to journal 06 Dec, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8297694","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":559622949,"identity":"b78d85b1-d7a4-4c57-98f7-43154af8e3f0","order_by":0,"name":"Xiaoming Li","email":"","orcid":"","institution":"Harbin Medical University Cancer Hospital","correspondingAuthor":false,"prefix":"","firstName":"Xiaoming","middleName":"","lastName":"Li","suffix":""},{"id":559622950,"identity":"96d73884-0fbf-4cca-9f3e-9564b413c4eb","order_by":1,"name":"Quan Yuan","email":"","orcid":"","institution":"Harbin Medical University Cancer 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2","display":"","copyAsset":false,"role":"figure","size":214449,"visible":true,"origin":"","legend":"\u003cp\u003eOverall Kaplan-Meier Survival Curve of Ethnic Minorities (A) EFS Kaplan-Meier Curve. (B) OS Kaplan-Meier Curve.\u003c/p\u003e","description":"","filename":"OnlineFigure2.png","url":"https://assets-eu.researchsquare.com/files/rs-8297694/v1/0628be6032ade07a3443cdb0.png"},{"id":98246009,"identity":"ab5018cf-a6f4-4db4-9377-ea2f6d1831e6","added_by":"auto","created_at":"2025-12-15 16:18:44","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":190038,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier Survival Curve of Manchu Ethnic Minorities (A) EFS Kaplan-Meier Curve. (B) OS Kaplan-Meier Curve.\u003c/p\u003e","description":"","filename":"OnlineFigure3.png","url":"https://assets-eu.researchsquare.com/files/rs-8297694/v1/106cfb2be1bb1e865e89082d.png"},{"id":98445062,"identity":"4225815d-1d69-4205-bdb0-79b1c5314746","added_by":"auto","created_at":"2025-12-17 17:18:49","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1489809,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8297694/v1/af52c718-111e-4a0e-a58c-62a2824e16ba.pdf"},{"id":98246225,"identity":"45394856-c6ff-4c91-90dd-9bc6decb5c41","added_by":"auto","created_at":"2025-12-15 16:18:52","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":838570,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial1.docx","url":"https://assets-eu.researchsquare.com/files/rs-8297694/v1/36f1c74a4794798052446484.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prognostic Analysis of Invasive Ductal Carcinoma of the Breast in Ethnic Minorities in Northeast China","fulltext":[{"header":"Background","content":"\u003cp\u003eBreast cancer (BC) ranks fourth globally as a cause of cancer-related deaths and stands as the most prevalent cancer among women worldwide. International BC research often categorizes patients by ethnicity and geographic location.(\u003cspan additionalcitationids=\"CR2 CR3 CR4\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e) Even within the same BC subtype, significant variations in incidence, mortality rates, and various prognostic indicators are observed across different patient populations.(\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e) Consequently, as research advances, there is a growing emphasis on more refined classification criteria and increased attention to minority groups. China is a multi-ethnic nation; while the majority of its population belongs to the East Asian ethnic group, distinct ethnic communities residing even within the same geographic area maintain unique lifestyles, dietary habits, and cultural practices.\u003c/p\u003e\u003cp\u003eInvasive ductal carcinoma (IDC) represents the predominant pathological type, accounting for approximately 70% of all diagnosed invasive breast cancers.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e) Originating from the epithelial cells lining the mammary ducts, IDC exhibits heightened invasiveness and a greater propensity for local or distant metastasis due to its ability to breach the mammary duct basement membrane and infiltrate surrounding stromal tissues. Its high clinical incidence and distinct prognostic outcomes compared to other pathological subtypes make IDC a focal point in BC research and clinical prognostic analyses.(\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eAccording to the 2020 national census, the northeastern region of China is home to all 55 ethnic minorities. Along the Songhua River basin, six ethnic groups have residential populations exceeding 3,000: the Manchu, Korean, Mongolian, Hui, Daur, and Hezhen, in descending order of population size. These are all indigenous ethnic minorities of the region. The Northeast serves as the cultural birthplace of the Manchu and Korean peoples in China, and the Daur constitutes a unique ethnic minority of Heilongjiang Province. This demographic composition provides an adequate sample size for investigating various aspects of BC in these ethnic minority patients and studying potential differences in BC subtype manifestations among China's diverse ethnic groups. To our knowledge, previous studies have typically focused on single ethnic minorities and have not incorporated data collection and evaluation across multiple ethnic groups within a specific geographic area.\u003c/p\u003e\u003cp\u003eTherefore, we retrospectively collected data on IDC patients from five major ethnic minorities treated at a large academic medical center in Northeast China between 2004 and 2024. Through long-term follow-up, we analyzed the event-free survival (EFS) and overall survival (OS) of patients from each ethnic group following appropriate treatment and further evaluated potential differences in BC subtypes among these minority populations.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003ePatients\u003c/h2\u003e\u003cp\u003eThis study enrolled 960 patients (\u0026ge;\u0026thinsp;18 years) with newly diagnosed primary IDC from Chinese ethnic minorities (non-Han) who attended the Affiliated Tumor Hospital of Harbin Medical University between January 1, 2004, and December 31, 2024. We collected available patient data, including blood test results, TNM staging (per the American Joint Committee on Cancer [AJCC] 8th Edition Staging System), and immunohistochemistry (IHC) findings. Patients were categorized into four subtypes based on initial IHC profiles: hormone receptor (HR)-positive/human epidermal growth factor receptor 2 (ERBB2, also known as HER2)-negative, HR-positive/HER2-positive, HR-negative/HER2-positive, and triple-negative breast cancer (TNBC). HR positivity was defined as estrogen receptor (ER) or progesterone receptor (PR) expression\u0026thinsp;\u0026ge;\u0026thinsp;1%. HER2 status was determined by IHC scoring and FISH results: scores of 0, 1+, or 2\u0026thinsp;+\u0026thinsp;with negative FISH indicated HER2 negativity; scores of 2\u0026thinsp;+\u0026thinsp;with positive FISH or 3\u0026thinsp;+\u0026thinsp;indicated HER2 positivity (in accordance with the Chinese Society of Clinical Oncology [CSCO] Breast Cancer Diagnosis and Treatment Guidelines).(\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e)\u003c/p\u003e\u003cp\u003eExclusion criteria: Of the 960 Chinese ethnic minority patients, 113 were excluded for four reasons: (\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e) 15 with undetermined BC subtypes; (\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e) 26 from ethnic groups with extremely small sample sizes (e.g., Hezhen); (\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e) 62 with pathological types other than IDC; and (\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e) 10 lost to follow-up. Consequently, data from 847 patients were included in the study analysis (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003ePatients will undergo follow-up every six months after receiving appropriate treatment through telephone calls, medical records, and instant messaging platforms to collect data on EFS and OS for each patient. Following standardized treatment, EFS is defined as the time interval from treatment completion until the first occurrence of specific events, including tumor recurrence, tumor progression, or patient death. OS is defined as the time interval from treatment completion until death from any cause. All data in this retrospective study were anonymized, and thus informed consent was not obtained from patients. This study was conducted in accordance with the Declaration of Helsinki and has been approved by the Ethics Committee of the Affiliated Tumor Hospital of Harbin Medical University (Ethical No. KY2022-52).\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec4\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eData analysis was conducted between October 15 and November 5, 2025. Categorical baseline characteristics across different subtypes were compared using the chi-square test, while continuous variables were analyzed via the t-test. Kaplan-Meier survival curves were constructed to estimate median EFS and OS, with statistical significance determined by 95% confidence interval (CI). Stratified analyses were further performed by ethnic minority subgroups to evaluate subtype-specific effects. All statistical computations were executed using R software (version 4.3.1).\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cp\u003eAmong the 847 participants, the cohort was categorized into four molecular subtypes: 126 (15%) HR-HER2- cases, 83 (10%) HR-HER2\u0026thinsp;+\u0026thinsp;cases, 512 (60%) HR\u0026thinsp;+\u0026thinsp;HER2- cases, and 126 (15%) HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;cases (Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). Statistical analysis revealed no significant differences in most hematological parameters or ethnic distribution across the different IHC-defined BC subtypes. However, notable variations were observed in relation to tumor TNM staging characteristics.\u003c/p\u003e\u003cp\u003e\u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e\u003ccaption language=\"En\"\u003e\u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e\u003cdiv class=\"CaptionContent\"\u003e\u003cp\u003eClinical characteristics of patients\u003c/p\u003e\u003c/div\u003e\u003c/caption\u003e\u003ccolgroup cols=\"7\"\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e\u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e\u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e\u003cthead\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eVariables\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003eTotal\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003eHR-HER2-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003eHR-HER2+\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003eHR\u0026thinsp;+\u0026thinsp;HER2-\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003eHR\u0026thinsp;+\u0026thinsp;HER2+\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c7\" morerows=\"1\" rowspan=\"2\"\u003e\u003cp\u003eP\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003ctr\u003e\u003cth align=\"left\" colname=\"c2\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;847)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c3\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;126)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c4\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;83)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c5\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;512)\u003c/p\u003e\u003c/th\u003e\u003cth align=\"left\" colname=\"c6\"\u003e\u003cp\u003e(n\u0026thinsp;=\u0026thinsp;126)\u003c/p\u003e\u003c/th\u003e\u003c/tr\u003e\u003c/thead\u003e\u003ctbody\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBMI(kg/m\u0026sup2;)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e24.08\u0026thinsp;\u0026plusmn;\u0026thinsp;3.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.19\u0026thinsp;\u0026plusmn;\u0026thinsp;3.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.96\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.13\u0026thinsp;\u0026plusmn;\u0026thinsp;3.30\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e23.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.792\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALT(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e23.84\u0026thinsp;\u0026plusmn;\u0026thinsp;20.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e24.68\u0026thinsp;\u0026plusmn;\u0026thinsp;18.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23.77\u0026thinsp;\u0026plusmn;\u0026thinsp;16.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e23.17\u0026thinsp;\u0026plusmn;\u0026thinsp;16.52\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25.77\u0026thinsp;\u0026plusmn;\u0026thinsp;34.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.591\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eAST(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e25.34\u0026thinsp;\u0026plusmn;\u0026thinsp;25.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e25.32\u0026thinsp;\u0026plusmn;\u0026thinsp;14.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e30.53\u0026thinsp;\u0026plusmn;\u0026thinsp;52.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e24.18\u0026thinsp;\u0026plusmn;\u0026thinsp;17.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.71\u0026thinsp;\u0026plusmn;\u0026thinsp;32.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.178\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGtp(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e38.36\u0026thinsp;\u0026plusmn;\u0026thinsp;83.94\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47.96\u0026thinsp;\u0026plusmn;\u0026thinsp;111.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e41.91\u0026thinsp;\u0026plusmn;\u0026thinsp;79.37\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e35.24\u0026thinsp;\u0026plusmn;\u0026thinsp;74.56\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e39.06\u0026thinsp;\u0026plusmn;\u0026thinsp;90.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.474\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLDH(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e184.69\u0026thinsp;\u0026plusmn;\u0026thinsp;105.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e204.46\u0026thinsp;\u0026plusmn;\u0026thinsp;114.62\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e187.82\u0026thinsp;\u0026plusmn;\u0026thinsp;66.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e174.59\u0026thinsp;\u0026plusmn;\u0026thinsp;42.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e203.91\u0026thinsp;\u0026plusmn;\u0026thinsp;224.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.004\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALP(U/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e90.86\u0026thinsp;\u0026plusmn;\u0026thinsp;68.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e101.08\u0026thinsp;\u0026plusmn;\u0026thinsp;106.35\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e91.25\u0026thinsp;\u0026plusmn;\u0026thinsp;52.24\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e87.22\u0026thinsp;\u0026plusmn;\u0026thinsp;50.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e95.19\u0026thinsp;\u0026plusmn;\u0026thinsp;88.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.186\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTBil(umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e14.17\u0026thinsp;\u0026plusmn;\u0026thinsp;25.59\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e14.62\u0026thinsp;\u0026plusmn;\u0026thinsp;28.60\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18.60\u0026thinsp;\u0026plusmn;\u0026thinsp;42.85\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e13.73\u0026thinsp;\u0026plusmn;\u0026thinsp;24.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e12.63\u0026thinsp;\u0026plusmn;\u0026thinsp;6.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.381\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDBil(umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.25\u0026thinsp;\u0026plusmn;\u0026thinsp;21.89\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.39\u0026thinsp;\u0026plusmn;\u0026thinsp;27.82\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;22.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.08\u0026thinsp;\u0026plusmn;\u0026thinsp;22.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e2.73\u0026thinsp;\u0026plusmn;\u0026thinsp;1.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.704\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIBil(umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e9.83\u0026thinsp;\u0026plusmn;\u0026thinsp;7.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e9.15\u0026thinsp;\u0026plusmn;\u0026thinsp;5.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e12.61\u0026thinsp;\u0026plusmn;\u0026thinsp;20.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9.53\u0026thinsp;\u0026plusmn;\u0026thinsp;4.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e9.92\u0026thinsp;\u0026plusmn;\u0026thinsp;5.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.006\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTP(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e74.72\u0026thinsp;\u0026plusmn;\u0026thinsp;15.79\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e77.13\u0026thinsp;\u0026plusmn;\u0026thinsp;39.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e74.85\u0026thinsp;\u0026plusmn;\u0026thinsp;5.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e74.39\u0026thinsp;\u0026plusmn;\u0026thinsp;5.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e73.64\u0026thinsp;\u0026plusmn;\u0026thinsp;6.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.301\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eALB(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44.37\u0026thinsp;\u0026plusmn;\u0026thinsp;17.19\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e47.06\u0026thinsp;\u0026plusmn;\u0026thinsp;38.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e43.66\u0026thinsp;\u0026plusmn;\u0026thinsp;4.10\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e44.21\u0026thinsp;\u0026plusmn;\u0026thinsp;11.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e42.84\u0026thinsp;\u0026plusmn;\u0026thinsp;3.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.233\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLOB(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e30.62\u0026thinsp;\u0026plusmn;\u0026thinsp;4.74\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e29.99\u0026thinsp;\u0026plusmn;\u0026thinsp;4.87\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e31.07\u0026thinsp;\u0026plusmn;\u0026thinsp;5.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e30.65\u0026thinsp;\u0026plusmn;\u0026thinsp;4.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e30.80\u0026thinsp;\u0026plusmn;\u0026thinsp;5.21\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.363\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eA/G\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.64\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.66\u0026thinsp;\u0026plusmn;\u0026thinsp;1.51\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.31\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.013\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eGLU(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.53\u0026thinsp;\u0026plusmn;\u0026thinsp;1.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e5.83\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.51\u0026thinsp;\u0026plusmn;\u0026thinsp;1.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.49\u0026thinsp;\u0026plusmn;\u0026thinsp;1.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5.41\u0026thinsp;\u0026plusmn;\u0026thinsp;1.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.087\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUrea(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e5.09\u0026thinsp;\u0026plusmn;\u0026thinsp;2.38\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.98\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e5.28\u0026thinsp;\u0026plusmn;\u0026thinsp;1.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e5.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.83\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.84\u0026thinsp;\u0026plusmn;\u0026thinsp;1.41\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.475\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCrea(umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e67.28\u0026thinsp;\u0026plusmn;\u0026thinsp;12.47\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e68.46\u0026thinsp;\u0026plusmn;\u0026thinsp;13.36\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e69.05\u0026thinsp;\u0026plusmn;\u0026thinsp;10.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e66.83\u0026thinsp;\u0026plusmn;\u0026thinsp;12.63\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e66.80\u0026thinsp;\u0026plusmn;\u0026thinsp;11.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.301\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eUA(umol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e283.69\u0026thinsp;\u0026plusmn;\u0026thinsp;99.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e293.02\u0026thinsp;\u0026plusmn;\u0026thinsp;190.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e278.62\u0026thinsp;\u0026plusmn;\u0026thinsp;65.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e284.37\u0026thinsp;\u0026plusmn;\u0026thinsp;73.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e274.90\u0026thinsp;\u0026plusmn;\u0026thinsp;78.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.511\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eTCO2(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.64\u0026thinsp;\u0026plusmn;\u0026thinsp;10.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26.68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e27.14\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e26.64\u0026thinsp;\u0026plusmn;\u0026thinsp;13.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e26.29\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.954\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eK(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;5.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.14\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.20\u0026thinsp;\u0026plusmn;\u0026thinsp;0.43\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.53\u0026thinsp;\u0026plusmn;\u0026thinsp;7.28\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.826\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNA(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e140.27\u0026thinsp;\u0026plusmn;\u0026thinsp;7.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e139.43\u0026thinsp;\u0026plusmn;\u0026thinsp;12.90\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e140.99\u0026thinsp;\u0026plusmn;\u0026thinsp;2.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e140.29\u0026thinsp;\u0026plusmn;\u0026thinsp;6.46\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e140.54\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.439\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCL(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e103.82\u0026thinsp;\u0026plusmn;\u0026thinsp;3.42\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e103.40\u0026thinsp;\u0026plusmn;\u0026thinsp;3.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e103.66\u0026thinsp;\u0026plusmn;\u0026thinsp;3.25\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e103.82\u0026thinsp;\u0026plusmn;\u0026thinsp;3.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e104.37\u0026thinsp;\u0026plusmn;\u0026thinsp;4.44\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.151\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eCA(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.84\u0026thinsp;\u0026plusmn;\u0026thinsp;9.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2.35\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.37\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.69\u0026thinsp;\u0026plusmn;\u0026thinsp;4.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.24\u0026thinsp;\u0026plusmn;\u0026thinsp;21.53\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.295\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eP(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.15\u0026thinsp;\u0026plusmn;\u0026thinsp;0.17\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.13\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.41\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMG(mmol/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.94\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.13\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.93\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.95\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.073\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eWBC(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e7.23\u0026thinsp;\u0026plusmn;\u0026thinsp;20.29\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6.68\u0026thinsp;\u0026plusmn;\u0026thinsp;2.45\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e6.70\u0026thinsp;\u0026plusmn;\u0026thinsp;2.01\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e7.66\u0026thinsp;\u0026plusmn;\u0026thinsp;26.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e6.38\u0026thinsp;\u0026plusmn;\u0026thinsp;1.98\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.896\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eLYM(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2.19\u0026thinsp;\u0026plusmn;\u0026thinsp;7.32\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1.99\u0026thinsp;\u0026plusmn;\u0026thinsp;0.77\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2.05\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e2.33\u0026thinsp;\u0026plusmn;\u0026thinsp;9.40\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1.91\u0026thinsp;\u0026plusmn;\u0026thinsp;0.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.919\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eNEU(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.15\u0026thinsp;\u0026plusmn;\u0026thinsp;2.67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.55\u0026thinsp;\u0026plusmn;\u0026thinsp;4.00\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.10\u0026thinsp;\u0026plusmn;\u0026thinsp;1.71\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.13\u0026thinsp;\u0026plusmn;\u0026thinsp;2.57\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e3.87\u0026thinsp;\u0026plusmn;\u0026thinsp;1.72\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.24\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMONO(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.22\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.43\u0026thinsp;\u0026plusmn;\u0026thinsp;0.18\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.41\u0026thinsp;\u0026plusmn;\u0026thinsp;0.23\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.754\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEOS(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.11\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.12\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.11\u0026thinsp;\u0026plusmn;\u0026thinsp;0.12\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.10\u0026thinsp;\u0026plusmn;\u0026thinsp;0.08\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.875\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eBASO(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e0.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.05\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0.03\u0026thinsp;\u0026plusmn;\u0026thinsp;0.02\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.11\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eRBC(10^12/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e4.45\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4.38\u0026thinsp;\u0026plusmn;\u0026thinsp;0.54\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e4.46\u0026thinsp;\u0026plusmn;\u0026thinsp;0.39\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4.48\u0026thinsp;\u0026plusmn;\u0026thinsp;0.49\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4.42\u0026thinsp;\u0026plusmn;\u0026thinsp;0.48\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.203\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHGB(g/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e134.04\u0026thinsp;\u0026plusmn;\u0026thinsp;37.16\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e131.53\u0026thinsp;\u0026plusmn;\u0026thinsp;15.93\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e135.02\u0026thinsp;\u0026plusmn;\u0026thinsp;11.03\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e135.53\u0026thinsp;\u0026plusmn;\u0026thinsp;46.07\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e129.87\u0026thinsp;\u0026plusmn;\u0026thinsp;17.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.386\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003ePLT(10^9/L)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e263.09\u0026thinsp;\u0026plusmn;\u0026thinsp;71.15\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e259.62\u0026thinsp;\u0026plusmn;\u0026thinsp;74.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e251.45\u0026thinsp;\u0026plusmn;\u0026thinsp;51.73\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e266.68\u0026thinsp;\u0026plusmn;\u0026thinsp;71.97\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e259.63\u0026thinsp;\u0026plusmn;\u0026thinsp;75.33\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.248\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKi-67\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e26.89\u0026thinsp;\u0026plusmn;\u0026thinsp;19.88\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e42.81\u0026thinsp;\u0026plusmn;\u0026thinsp;24.04\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e34.98\u0026thinsp;\u0026plusmn;\u0026thinsp;17.65\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e19.98\u0026thinsp;\u0026plusmn;\u0026thinsp;16.09\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e33.73\u0026thinsp;\u0026plusmn;\u0026thinsp;17.06\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eEthnicity, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.798\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eDaur\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e44 (5.19)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e7 (5.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e28 (5.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e7 (5.56)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eHui\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e138 (16.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e15 (11.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e15 (18.07)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e90 (17.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18 (14.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eKorean\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e128 (15.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e22 (17.46)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e10 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colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eMongolian\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e126 (14.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e16 (12.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e13 (15.66)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e79 (15.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18 (14.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eN, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e414 (48.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e57 (45.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e26 (31.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e284 (55.47)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e47 (37.30)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e222 (26.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e35 (27.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e23 (27.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e132 (25.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e32 (25.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e132 (15.58)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (16.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e20 (24.10)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62 (12.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e29 (23.02)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e79 (9.33)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e13 (10.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (16.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e34 (6.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e18 (14.29)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eM, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e0.149\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e825 (97.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e120 (95.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e81 (97.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e503 (98.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e121 (96.03)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (2.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (4.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (1.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (3.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eT, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e0\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e2 (0.24)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e1 (0.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e250 (29.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e28 (22.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (16.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e181 (35.35)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e27 (21.43)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e1mic\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (1.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e1 (0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e10 (1.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e2\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e536 (63.28)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e88 (69.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e58 (69.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e299 (58.40)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e91 (72.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e3\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e33 (3.90)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (3.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (9.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e17 (3.32)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (3.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003e4\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e13 (1.53)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e4 (3.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e1 (1.20)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e4 (0.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e4 (3.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eStage, n(%)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u0026nbsp;\u003c/td\u003e\u003ctd align=\"char\" char=\".\" colname=\"c7\"\u003e\u003cp\u003e\u0026lt;\u0026thinsp;.001\u003c/p\u003e\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e179 (21.13)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e21 (16.67)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e8 (9.64)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e134 (26.17)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (12.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e287 (33.88)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e40 (31.75)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e22 (26.51)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e190 (37.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e35 (27.78)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e152 (17.95)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e26 (20.63)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e18 (21.69)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e83 (16.21)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e25 (19.84)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIIA\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e128 (15.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e19 (15.08)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e19 (22.89)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e62 (12.11)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e28 (22.22)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIIB\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e6 (0.71)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e2 (1.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e0 (0.00)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e3 (0.59)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e1 (0.79)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIIIC\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e73 (8.62)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e12 (9.52)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e14 (16.87)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e31 (6.05)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e16 (12.70)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003ctr\u003e\u003ctd align=\"left\" colname=\"c1\"\u003e\u003cp\u003eIV\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c2\"\u003e\u003cp\u003e22 (2.60)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c3\"\u003e\u003cp\u003e6 (4.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c4\"\u003e\u003cp\u003e2 (2.41)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c5\"\u003e\u003cp\u003e9 (1.76)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c6\"\u003e\u003cp\u003e5 (3.97)\u003c/p\u003e\u003c/td\u003e\u003ctd align=\"left\" colname=\"c7\"\u003e\u0026nbsp;\u003c/td\u003e\u003c/tr\u003e\u003c/tbody\u003e\u003c/colgroup\u003e\u003c/table\u003e\u003c/div\u003e\u003c/p\u003e\u003cp\u003eA total of 414 patients (48.88%) presented with no lymph node involvement at diagnosis (N0). The HR\u0026thinsp;+\u0026thinsp;HER2- subtype showed the highest proportion of N0 cases (55.47%). Conversely, in BC cases with four or more positive lymph nodes (N2/N3), the HR\u0026thinsp;+\u0026thinsp;HER2- subtype was less frequently represented: for N2, the proportions were HR-HER2- (16.67%), HR-HER2+ (24.10%), HR\u0026thinsp;+\u0026thinsp;HER2+ (23.02%), and HR\u0026thinsp;+\u0026thinsp;HER2- (12.11%); for N3, the respective proportions were HR-HER2- (10.32%), HR-HER2+ (16.87%), HR\u0026thinsp;+\u0026thinsp;HER2+ (14.29%), and HR\u0026thinsp;+\u0026thinsp;HER2- (6.64%). No significant differences in distribution were observed among the four subtypes for N1 status.\u003c/p\u003e\u003cp\u003eRegarding tumor size, T2 stage was the most commonly diagnosed n\u0026thinsp;=\u0026thinsp;536, 63.28%. The HR\u0026thinsp;+\u0026thinsp;HER2- subtype demonstrated a higher detection rate at T1 stage compared to other subtypes, HR\u0026thinsp;+\u0026thinsp;HER2-: 35.35%; HR-HER2-: 22.22%; HR-HER2+: 16.87%; HR\u0026thinsp;+\u0026thinsp;HER2+: 21.43%, while showing lower frequencies in T2 and T4 stages. Clinically, HR\u0026thinsp;+\u0026thinsp;HER2- BC was more frequently diagnosed at early stages (TNM Stage IA: 26.17%; IIA: 37.11%). In contrast, HER2\u0026thinsp;+\u0026thinsp;subtypes were more likely to present at Stage III HR-HER2+: 39.76%; HR\u0026thinsp;+\u0026thinsp;HER2+: 35.71%.\u003c/p\u003e\u003cp\u003eKi-67 proliferation index was significantly higher in TNBC and HER2\u0026thinsp;+\u0026thinsp;subtypes compared to HR\u0026thinsp;+\u0026thinsp;HER2- BC (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001). TNBC (HR-HER2-) exhibited the highest mean Ki-67 value (42.81), which was 2.14 times that of HR\u0026thinsp;+\u0026thinsp;HER2- tumors (19.98). The HER2\u0026thinsp;+\u0026thinsp;subtypes showed intermediate values, with HR-HER2+ (34.98) and HR\u0026thinsp;+\u0026thinsp;HER2+ (33.73) demonstrating 1.75-fold and 1.68-fold increases relative to HR\u0026thinsp;+\u0026thinsp;HER2- cases, respectively.\u003c/p\u003e\u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e. Clinical characteristics of patients \u003cb\u003e(At the end of the document text file)\u003c/b\u003e\u003c/p\u003e\u003cp\u003eSurvival outcomes were analyzed for all participants, with a maximum follow-up duration of 258 months from the time of initial diagnosis in early-stage patients. The entire cohort demonstrated a 5-year OS rate of 78.45% and a 5-year EFS rate of 64.84%. Statistically significant differences in prognosis were observed across molecular subtypes (Appendix Table\u0026nbsp;1). Specifically, HR\u0026thinsp;+\u0026thinsp;HER2- BC exhibited the most favorable median EFS (104.17 months; 95% CI, 97.53\u0026ndash;117.73), whereas HR-HER2- BC showed the poorest prognosis (median EFS: 63.57 months; 95% CI, 48.53\u0026ndash;88.53). Consistent with EFS data, HR\u0026thinsp;+\u0026thinsp;HER2- BC also had the longest median OS (121.83 months; 95% CI, 113.90\u0026ndash;137.00), significantly outperforming HR-HER2- BC (median OS: 75.17 months; 95% CI, 62.23\u0026ndash;94.80). HER2\u0026thinsp;+\u0026thinsp;subtypes displayed intermediate prognostic outcomes, with HR-HER2\u0026thinsp;+\u0026thinsp;BC showing marginally inferior survival compared to HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;BC. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e, HR\u0026thinsp;+\u0026thinsp;HER2- BC consistently demonstrated superior long-term survival. HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;BC also conferred a statistically significant survival advantage over both HR-HER2- and HR-HER2\u0026thinsp;+\u0026thinsp;subtypes, albeit with modest differences. Notably, the Kaplan-Meier curves for HR-HER2- and HR-HER2\u0026thinsp;+\u0026thinsp;BC overlapped substantially, indicating comparable long-term survival trajectories between these two subtypes.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eTo further investigate the impact of different ethnic backgrounds on the prognosis of breast cancer patients, we stratified the study subjects into single ethnic groups. Within the individual analyses of the Daur, Hui, Korean, Manchu, and Mongolian ethnicities, results revealed that although the Manchu group had the largest sample size n\u0026thinsp;=\u0026thinsp;411, 48.52%, no significant correlations were observed in the median survival durations associated with molecular subtypes (Median EFS: p\u0026thinsp;=\u0026thinsp;0.122; Median OS: p\u0026thinsp;=\u0026thinsp;0.089) (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e, Appendix Table\u0026nbsp;2). Contrary to the overall trend, Manchu patients with TNBC exhibited comparable prognostic outcomes to those with HER2\u0026thinsp;+\u0026thinsp;breast cancer (p\u0026thinsp;\u0026gt;\u0026thinsp;0.05), and demonstrated superior Median EFS when compared to HR-HER2\u0026thinsp;+\u0026thinsp;subtype (HR-HER2-: 85.60 months; 95%CI, 48.53-116.13; HR-HER2+: 66.63 months; 95%CI, 54.30-97.27). Interestingly, the survival curves of the Manchu cohort indicated that the statistically significant advantage of HR\u0026thinsp;+\u0026thinsp;HER2- breast cancer over other subtypes was not as pronounced as observed in the overall assessment.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\u003cp\u003eAlthough the Hui, Mongolian, and Korean ethnic groups exhibited comparable sample sizes, their clinical outcomes differed substantially. Among the Korean and Hui populations, TNBC was associated with the shortest median EFS (Appendix Table\u0026nbsp;3). In contrast, Mongolian patients with HR-HER2- breast cancer demonstrated significantly better EFS outcomes (91.80 months; 95% CI, 34.77-NA) compared to those with HR-HER2\u0026thinsp;+\u0026thinsp;subtype (65.60 months; 95% CI, 28.23-NA). Interestingly, no notable difference was observed in median OS between Mongolian HR-HER2- (75.17 months; 95% CI, 61.83-NA) and HR-HER2+ (75.70 months; 95% CI, 62.35-NA) subgroups (Appendix Table\u0026nbsp;4). Equally disappointing to the median OS of Korean TNBC (65.53 months; 95% CI, 29.93\u0026ndash;94.63) was the HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;breast cancer subtype, which showed a median OS of only 64.43 months (95%CI, 46.9-NA), whereas the HR-HER2\u0026thinsp;+\u0026thinsp;subtype presented more favorable prognostic outcomes. Survival curve analyses of the remaining two ethnic groups indicated that the HR\u0026thinsp;+\u0026thinsp;HER2- subtype consistently conferred the optimal prognosis (Appendix Fig.\u0026nbsp;1). For the Daur population, statistical analysis revealed no significant differences in prognostic outcomes across different IHC subtypes for either median EFS (p\u0026thinsp;=\u0026thinsp;0.304) or median OS (p\u0026thinsp;=\u0026thinsp;0.400) (Appendix Table\u0026nbsp;5, Appendix Fig.\u0026nbsp;2).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study investigates the prognostic outcomes of invasive ductal carcinoma (IDC) among ethnic minorities in Northeast China. Among molecular subtypes, HR\u0026thinsp;+\u0026thinsp;tumors demonstrated the most favorable prognosis, while TNBC exhibited the poorest long-term outcomes, with HR-HER2\u0026thinsp;+\u0026thinsp;showing comparable survival patterns to TNBC in extended follow-up. The overall cohort achieved a 5-year OS rate of 78.45% and 5-year EFS rate of 64.84%. Notably, Manchu patients, the largest subgroup, showed no significant differences in EFS or OS across subtypes. Hui patients displayed similar trends, whereas Korean HR-HER2\u0026thinsp;+\u0026thinsp;tumors showed superior outcomes, contrasting with HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;subtypes that exhibited OS rates comparable to TNBC. Mongolian HR-HER2\u0026thinsp;+\u0026thinsp;tumors demonstrated the poorest EFS among this ethnic group.\u003c/p\u003e\u003cp\u003eMinority subtype distributions aligned with national patterns, with Stage II tumors predominating (21.13% Stage I detection). This contrasts starkly with China's national Stage I detection rate (31.8%) and US figures (54.6%).(\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e) While global 5-year OS ranges from 85\u0026ndash;90% in developed countries to ~\u0026thinsp;80% in East Asia,(\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e) our cohort's 78.45% OS significantly trails. China's national IDC survival (92.9%), South Korea (88.8%), and US API populations (84.8%).(\u003cspan additionalcitationids=\"CR14\" citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e) These disparities highlight inadequate early screening and suboptimal treatment access among unscreened minority populations, necessitating improved screening initiatives, enhanced healthcare resources, and optimized treatment protocols.\u003c/p\u003e\u003cp\u003eThe Manchu population, genetically admixed with Han Chinese through centuries of cohabitation, showed no statistical survival differences across subtypes (P\u0026thinsp;\u0026gt;\u0026thinsp;0.05). This may relate to unique cytochrome P-450 2D6 (CYP2D6) polymorphisms identified in Northeast Manchu populations,(\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e) which impair tamoxifen metabolism to its active metabolite endoxifen. Reduced CYP2D6 activity.(\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e) As demonstrated by Schroth et al., correlates with poorer EFS and DFS in tamoxifen-treated patients,(\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e) potentially attenuating HR\u0026thinsp;+\u0026thinsp;prognostic advantages in this group.\u003c/p\u003e\u003cp\u003eGenetically homologous to Korean Peninsula populations,(\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e) Chinese Koreans displayed favorable outcomes in HR-HER2\u0026thinsp;+\u0026thinsp;subtypes (10/128 patients), attributed to high pathologic complete response rates with chemotherapy/anti-HER2 targeting and superior treatment adherence. Conversely, HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;subtypes exhibited TNBC-comparable OS, potentially due to dual endocrine/anti-HER2 resistance and limited benefit from HER2-targeted therapy in tumors with \u0026gt;\u0026thinsp;30% ER expression, hypothesized to result from signaling crosstalk despite insufficient corroborative evidence.(\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e) Mongolian HR-HER2\u0026thinsp;+\u0026thinsp;tumors (11 events among 13 patients) showed poorest outcomes, potentially linked to nomadic cultural influences delaying diagnosis and reducing adherence to HER2-directed therapies. Daur patients showed no prognostic differences across IHC subtypes, likely due to insufficient sample size.\u003c/p\u003e\u003cp\u003eTo our knowledge, this represents the first focused analysis of IDC disparities among Northeast China's ethnic minorities, addressing a critical research gap with significant clinical and preventive implications, supported by extensive follow-up. Limitations include inherent sample size constraints in minority populations despite prolonged (20\u0026thinsp;+\u0026thinsp;year) follow-up, single-center recruitment introducing geographic bias, evolving HER2 testing standards (including FISH adoption) and trastuzumab insurance coverage (post-2017) potentially underestimating HER2\u0026thinsp;+\u0026thinsp;incidence and treatment efficacy in earlier cohorts, and unmeasured confounding variables (socioeconomic status, education, lifestyle). Nevertheless, these findings underscore meaningful prognostic variations across ethnic minority IDC subtypes and guide future research directions.\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThis represents the first study investigating the prognosis of different IDC subtypes among multiple ethnic minorities in Northeast China. It reveals ethnic disparities in IHC profiles, along with lower early detection rates and poorer prognosis in minority IDC patients. Except for HR-HER2\u0026thinsp;+\u0026thinsp;in Koreans, HR\u0026thinsp;+\u0026thinsp;HER2- consistently showed the most favorable prognosis across other ethnic groups. Among Manchus, no statistically significant prognostic differences were observed between the four molecular subtypes. The TNBC subtype was associated with poorer outcomes in most ethnicities; additionally, HR\u0026thinsp;+\u0026thinsp;HER2\u0026thinsp;+\u0026thinsp;in Koreans and HR-HER2\u0026thinsp;+\u0026thinsp;in Mongolians also demonstrated inferior OS.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eBC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eBreast Cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eCI\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eConfidence Internal\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eEFS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEvent-free Survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eER\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eEstrogen Receptor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eHER2\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHuman epidermal growth factor receptor 2\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eHR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eHormone Receptor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eIDC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eInvasive ductal carcinoma\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eIHC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eImmunohistochemistry\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eOS\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eOverall Survival\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003ePR\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eProgesterone Receptor\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003cdiv class=\"DefinitionListEntry\"\u003e\u003cdiv class=\"Term\"\u003e\u003cb\u003eTNBC\u003c/b\u003e\u003c/div\u003e\u003cdiv class=\"Description\"\u003e\u003cp\u003eTriple-negative breast cancer\u003c/p\u003e\u003c/div\u003e\u003c/div\u003e\u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eEthics Statement\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis study has been granted approval by the Institutional Ethics Review Board of Harbin Medical University Cancer Hospital, under the ethic clearance number KY2022-52. All procedures involving human participants were performed in 1964 Helsinki Declaration and its later amendments or comparable ethical standards.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eNot applicable.\u003c/p\u003e\n\u003ch2\u003eData Sharing Statement\u003c/h2\u003e\n\u003cp\u003eThe data collected and analyzed in this study are available from the corresponding author and the first author upon reasonable request.\u003c/p\u003e\n\u003ch2\u003eCompeting interests\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eAuthor information\u003c/h2\u003e\n\u003cp\u003eXiaoming Li, Quan Yuan and Yupeng Sha have contributed equally to this work and are co-first authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors and Affiliations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eDepartment of Breast Surgery, Harbin Medical University Cancer Hospital, Harbin 150000, Heilongjiang, China\u003c/p\u003e\n\u003cp\u003eXiaoming Li, Quan Yuan, Yupeng Sha, Yixin Liu, Yige Lu, Xianyu Zhang, Da Pang \u0026amp; Jiguang Han\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCorresponding authors\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eCorrespondence to Xianyu Zhang, Da Pang or Jiguang Han.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSupplementary Information\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eSupplementary material 1.\u003c/p\u003e\n\u003ch2\u003eFunding sources\u003c/h2\u003e\n\u003cp\u003eThis research was funded by the Beijing Medical Award Foundation (Grant No. Yx7L-2023-0460-0199).\u003c/p\u003e\n\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\n\u003cp\u003eXL: Writing\u0026ndash;original draft, Investigation, Formal analysis, Visualization. QY: Writing\u0026ndash;original draft, Investigation, Data curation. YS: Writing\u0026ndash;original draft, Methodology, Validation. YXL: Resources, Data curation, Formal analysis. YGL: Resources, Software, Funding. XZ: Project administration, Supervision. DP: Validation, Funding acquisition, Writing\u0026ndash;review \u0026amp; editing. JH: Conceptualization, Methodology, Writing\u0026ndash;review \u0026amp; editing, Supervision, acquisition.\u003c/p\u003e\n\u003ch2\u003eAcknowledgement\u003c/h2\u003e\n\u003cp\u003eWe convey our thanks to all the contributing authors for their significant contributions to the study. Our sincere gratitude is also due to the cancer patients who participated in this research, for their cooperation throughout follow-up. We are indebted to the Harbin Medical University Cancer Hospital for its support.\u003c/p\u003e\n\u003ch2\u003eData Availability\u003c/h2\u003e\n\u003cp\u003eThe data collected and analyzed in this study are available from the corresponding author and the first author upon reasonable request.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eBray F, Laversanne M, Sung H, Ferlay J, Siegel RL, Soerjomataram I, et al. Global cancer statistics 2022: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. 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Triple-positive breast cancer: navigating heterogeneity and advancing multimodal therapies for improving patient outcomes. Cancer Cell Int. 2025;25(1):77. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1186/s12935-025-03680-7\u003c/span\u003e\u003cspan address=\"10.1186/s12935-025-03680-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"China, Ethnic and racial minorities, Immunohistochemistry, Invasive ductal carcinoma, Prognosis","lastPublishedDoi":"10.21203/rs.3.rs-8297694/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8297694/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e\u003cp\u003eInvasive ductal carcinoma (IDC) is the most common pathological subtype of breast cancer (BC). The prognosis of minority IDC in Northeast China has not been fully studied, which limits the demand for equal access to specific therapies among different ethnic groups.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eRetrospective collection of cases from medical centers in Northeast China, gathering patients with primary IDC of ethnic minorities (aged\u0026thinsp;\u0026ge;\u0026thinsp;18 years) who visited between 2004 and 2024. Follow-up was conducted every six months. Data analysis was performed from October 2025 to November 2025.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eThis study collected data from 847 relevant patients. The 5-year overall survival (OS) rate for all samples was 78.45%, and the 5-year event-free survival (EFS) rate was 64.84%. HR\u0026thinsp;+\u0026thinsp;HER2- cases were more likely to be diagnosed early (TNM Stage IA: 26.17%; IIA: 37.11%). HR-HER2- had the poorest overall prognosis, with a higher mean Ki-67 at diagnosis (HR-HER2-:42.81). In long-term survival, HR-HER2- and HR-HER\u0026thinsp;+\u0026thinsp;showed similar outcomes. Under different immunohistochemistry (IHC) conditions, the statistical significance for Manchu and Daur was not significant. The prognostic trend for Hui was no different from the overall trend.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e\u003cp\u003eThe early detection rate of these ethnic minorities was lower than the average level of China, and the overall prognosis was worse compared to that of Chinese IDC patients. There were also significant differences in the prognostic outcomes among the five ethnic minority groups.\u003c/p\u003e","manuscriptTitle":"Prognostic Analysis of Invasive Ductal Carcinoma of the Breast in Ethnic Minorities in Northeast China","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-12-15 16:15:47","doi":"10.21203/rs.3.rs-8297694/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-03-04T03:59:36+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-01-22T23:58:40+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"327641308074671322600092888208484429055","date":"2026-01-22T23:52:23+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2025-12-21T15:45:31+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"145775762290711553696010353467977009154","date":"2025-12-10T16:01:02+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2025-12-10T10:12:19+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2025-12-09T05:07:30+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2025-12-08T04:29:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2025-12-08T04:28:03+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Cancer","date":"2025-12-07T04:28:25+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-cancer","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bcan","sideBox":"Learn more about [BMC Cancer](http://bmccancer.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bcan/default.aspx","title":"BMC Cancer","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"a0cddd34-ed40-4185-bc1a-cce83712a3a3","owner":[],"postedDate":"December 15th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-05-20T17:53:51+00:00","versionOfRecord":[],"versionCreatedAt":"2025-12-15 16:15:47","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8297694","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8297694","identity":"rs-8297694","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}