Risk of Newly Incident Diabetes Mellitus and Treatment Risk Factors in Breast Cancer Survivors: Landmark Analyses of Nationwide Data

Risk of Newly Incident Diabetes Mellitus and Treatment Risk Factors in Breast Cancer Survivors: Landmark Analyses of Nationwide Data | 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 Risk of Newly Incident Diabetes Mellitus and Treatment Risk Factors in Breast Cancer Survivors: Landmark Analyses of Nationwide Data Hyeongjin Shim, Bong-seong Kim, Kyungdo Han, Hye Yeon Koo, Seonghye Kim, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6010947/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background While breast cancer increases the risk of diabetes mellitus (DM), its temporal relationships according to age group and treatment risk factors for DM have not been comprehensively investigated. In this study we explore temporal patterns of DM risk in breast cancer survivors, stratified by age and risk factors. Methods Using the National Health Insurance Service database in South Korea, this retrospective cohort study analyzed 65,982 breast cancer survivors and 168,214 age-matched controls, excluding those with prior DM or other cancers. Multivariable Fine-Gray models adjusted for sociodemographics, comorbidities, lifestyle behaviors, and cancer treatments assessed DM risk, with landmark analyses at 1, 3, and 5 years post-diagnosis and stratification by age (≤ 50 and > 50 years). Results In women ≤ 50, DM risk was highest in the first year post-diagnosis (sHR 3.74, 95% CI 3.08–4.55), decreased at 1 year (sHR 1.11, 95% CI 1.03–1.19), and showed no significant increase in 3-year and subsequent analyses. In women > 50, DM risk was also elevated in the first year (sHR 1.71, 95% CI 1.92–2.35) but not later. Significant risk factors included BMI ≥ 25 (sHR 1.45), smoking (sHR 1.72), hypertension (sHR 1.48), dyslipidemia (sHR 1.49), and taxane use (sHR 1.15). Tamoxifen was a risk factor in younger women (sHR 1.22, 95% CI 1.06–1.40). Conclusion Breast cancer survivors face the highest DM risk within the first year post-diagnosis, particularly younger women. Risk factors include obesity, smoking, hypertension, dyslipidemia, and treatments such as taxane and tamoxifen. Diabetes mellitus breast cancer survivor chemotherapy endocrine therapy Figures Figure 1 INTRODUCTION Breast cancer is the most commonly diagnosed cancer among women worldwide, and its incidence continues to rise.[1] Breast cancer patients are reported to be at higher risk of diabetes mellitus (DM) than the general population [2–7], mainly due to weight gain[8] and corticosteroid use.[9] DM is linked to various medical conditions and reduces life expectancy,[10] and is also associated with poor breast cancer prognosis.[11] Therefore, monitoring the development of DM in breast cancer patients is necessary for effective health management. The risk of DM in breast cancer survivors might differ according to time since diagnosis (i.e., short-term vs. long-term risk) or patient age (i.e., premenopausal vs. post-menopausal). However, most previous studies regarding the risk of DM and breast cancer did not consider time-related patterns [3, 5, 7]. A few studies reported temporal patterns but showed inconsistent results, with some reporting increased risk in the short-term only [12, 13] and others reporting increased risk with time.[2, 6, 14, 15] Menopausal status is an important factor determining the use of hormonal therapies, such as tamoxifen or aromatase inhibitors. In addition, there are interactions between menopausal status and obesity/central obesity that are relevant to the incidence of DM.[15, 16] However, most previous studies did not consider age or menopausal status in their assessments of DM risk [4, 5, 7, 14] or limited the analysis to specific age groups (e.g., older women only [2, 3, 6]) (Supplementary Table 1). Cancer treatment can also influence the risk of DM in breast cancer patients. Previous studies reported increased risk with chemotherapy [3, 6], tamoxifen use [4, 15–18], and aromatase inhibitor (AI) use [16, 17]. However, other studies found no associations between risk of DM and hormonal therapy [2, 13], or even decreased risk with AI treatment [15]. Moreover, many studies did not incorporate age stratification into their analysis [4, 14, 16] or included older women only [2, 3, 6, 13, 18] (Supplementary Table 2). Therefore, in this study we examined short-term and long-term risks of DM in breast cancer patients separately and analyzed risk by stratifying patients according to age into groups younger than and older than 50 years to account for the impact of menopause. Additionally, we extensively investigated the effects of cancer treatment on DM risk using nationwide cohort data and performed further age stratification to minimize the influence of menopause. METHODS Data and Study Setting In South Korea, the National Health Insurance Service (NHIS) ensures mandatory universal health coverage for 97% of the population. The NHIS database is comprehensive, containing sociodemographic information and healthcare claims data such as medical procedures, diagnoses, prescriptions, outpatient visits, and hospital admissions.[19, 20] Additionally, the NHIS administers biennial health screenings,[21] which gather information on past medical history, lifestyle behaviors (including smoking, drinking, and physical activity), anthropometric measurements, and laboratory test results. These screenings are provided for all employees regardless of age and for nonemployees aged 40 and older. The NHIS database is validated and widely used for epidemiological and clinical research.[22, 23] For this study, we utilized data from the NHIS database to analyze DM risk among breast cancer survivors. NHIS data provided a robust foundation for this study due to the comprehensive nature and reliability of epidemiological and clinical studies. This study was approved by the Samsung Medical Center Institutional Review Board (Seoul, South Korea; SMC 2020-03-108). All information used for analyses was anonymized and de-identified; therefore, informed consent was not required. The database is open to all researchers whose study protocols are approved by the official review committee. Study Population This study included 151,422 women who were newly diagnosed with invasive breast cancer and underwent surgery between January 1, 2010, and December 31, 2016. Newly diagnosed invasive breast cancer cases were identified using C50 and V193 codes. In Korea, the V193 code is assigned only after biopsy-confirmed diagnosis, enhancing the accuracy of cancer identification in NHIS data.[24] We excluded participants who did not receive surgery within one year of their breast cancer diagnosis (n = 24,856), had histories of other cancers prior to breast cancer (n = 5,514), were under 18 years old, had prior diagnoses of DM (n = 9,431), or had missing health screening data (n = 3,393). To construct the control group, breast cancer survivors were matched in a 1:3 ratio with controls based on age, with the index date for controls corresponding to the date of breast cancer diagnosis in the survivor group. To enhance comparability, we included only individuals who had undergone a general health examination within two years prior to the index date in both groups. By linking data from the national health screening program, we obtained detailed information on health behaviors, anthropometric measurements, and laboratory results, allowing us to include various covariates in the analysis. After applying these criteria, 67,938 breast cancer survivors and 171,250 controls were initially included. Subsequently, we excluded individuals with missing health screening data (n = 683 in the breast cancer group; n = 1,965 in the control group) and those with fasting glucose levels ≥ 126 mg/dL during screening (n = 1,273 and n = 3,036, respectively). As a result, the final analysis included 65,982 breast cancer survivors and 168,214 matched controls (Fig. 1). Outcomes The primary outcome of this study was the incidence of newly diagnosed DM, identified by the use of antidiabetic medications along with ICD-10 codes for DM (E11–E14).[8, 25, 26] Participants were followed from the date of breast cancer diagnosis until the occurrence of newly diagnosed DM, a censoring event (e.g., death or outmigration), or the end of the study on December 31, 2020, whichever came first. Covariates Breast cancer treatment information was based on patient data within 1 year after diagnosis of breast cancer.[27, 28] Participant comorbidities were determined using laboratory measures, insurance claims, and prescription data prior to the index date. Hypertension was identified by ICD-10 codes (I10.x-I13.x and I15.x), being treated with antihypertensive medication, or blood pressure readings of ≥ 140/90 mmHg. Dyslipidemia was defined by ICD-10 code E78.x, taking any prescribed lipid-lowering drug, or a total cholesterol level of ≥ 240 mg/dL. Chronic kidney disease was diagnosed as a glomerular filtration rate of < 60 mL/min/1.73 m², and estimations were performed using the Modification of Diet in Renal Disease equation. Income level was categorized based on health insurance premiums. Low-income status was defined as being in the lowest quartile of premiums or being registered in the Medical Aid program. Geographic residence was classified into rural and urban categories based on primary local authority districts (shi/gun/gu). Body mass index (BMI) was determined by dividing weight in kilograms by height in meters squared (kg/m²). Information regarding smoking status (current or non-smoker) and alcohol consumption (yes or no) was collected during the general health screening following cancer diagnosis. Regular exercise was defined as vigorous activity for more than 20 minutes per session ≥3 days per week or moderate-intensity activity for more than 30 minutes per session ≥5 days per week. Statistical Analysis Baseline characteristics are reported as means with standard deviations for continuous variables and numbers with percentages for categorical variables. Participants were followed from the date of diagnosis, considering the first year separately from the period beyond one year after baseline assessment, until the first occurrence of a DM diagnosis, death, or the study’s conclusion, whichever occurred first. Person-time was calculated starting one year after baseline, and the crude incidence rate of DM was expressed per 1,000 person-years by dividing the number of DM events by the total person-years of follow-up. The cumulative incidence of DM was estimated using a competing risk framework, treating death as a competing event.[29] The incidence of DM was compared between breast cancer survivors and the general population using the Gray-K test.[30] The Fine-Gray proportional sub-distribution hazards model was applied to evaluate the relative risk of DM in breast cancer survivors compared to the general population. This approach allowed for the calculation of sub-distribution hazard ratios (sHRs) and 95% confidence intervals (CIs), explicitly accounting for death as a competing risk.[16, 31] The analysis incorporated adjustments in a stepwise manner: the crude model was unadjusted, the second model was adjusted for sociodemographic factors (age, residential location, and household income), and the final model included further adjustment for comorbidities, BMI, smoking status, alcohol consumption, and regular exercise. Landmark analyses were performed to assess DM risk over distinct follow-up intervals, including 0–1 year, 1 year, 3 years, and 5 years post-breast cancer diagnosis.[32] Further stratified analyses were conducted by age group (≤ 50 and > 50 years) based on the median age of menopause in Korean women.[12] This definition was chosen due to the absence of menopausal status information in our current cohort data. Within the breast cancer survivor cohort, adjusted sub-distribution hazard ratios (sHRs) for DM incidence were calculated, accounting for age, residential location, income status, BMI, smoking status, alcohol consumption, regular exercise, hypertension, dyslipidemia, chronic kidney disease, and treatment-related factors, including anthracyclines, taxane, trastuzumab, endocrine therapies (tamoxifen or aromatase inhibitors), and radiation therapy. These analyses were also stratified by age (≤ 50 and > 50 years). All statistical analyses were conducted using SAS version 9.4, and statistical significance was determined according to a two-sided P-value of < 0.05. RESULTS Baseline Characteristics Table 1 shows the baseline characteristics of participants. The average age was older in the breast cancer group (51.08 ± 8.57 vs. 50.92 ± 8.52). Breast cancer survivors were more likely to have higher incomes (Q4, 33.29% vs. 31.26%). Breast cancer survivors were more likely to live in urban areas (50.07% vs. 46.86%). Breast cancer survivors were more likely to have hypertension (16.72% vs 16.34%) and chronic kidney disease (0.25% vs. 0.18%). Among breast cancer survivors, there were more current smokers (3.84% vs. 3.51%), and fewer individuals engaged in regular exercise (18.2% vs. 18.66%). Table 1 Baseline characteristics of the study population Breast Cancer p-value No (N = 169,214) Yes (N = 65,982) Age at baseline, mean (SD), years 50.92 (8.57) 50.08 (8.57) < .01 Comorbidity, Yes Hypertension 27,479 (16.34) 11,034 (16.72) 0.02 Dyslipidemia 21,204 (12.61) 8,499 (12.88) 0.07 Chronic kidney disease (GFR < 60 ) 1 6,441 (3.83) 2,544 (3.86) 0.76 Income status (Quartile) < .01 Q1 40,915 (24.32) 15,095 (22.88) Q2 36,043 (21.43) 13,757 (20.85) Q3 38,668 (22.99) 15,164 (22.98) Q4 52,588 (31.26) 21,966 (33.29) Residential location, Urban 78,827 (46.86) 33,036 (50.07) < .01 BMI ≥ 25 (kg/m²) 45,763 (27.21) 17,856 (27.06) 0.48 Glucose (mg/dL) 92.38 (10.45) 92.88 (10.49) < .01 Current smoker, Yes 5,912 (3.51) 2,537 (3.84) 0.01 Drinker, Yes 43,702 (25.98) 17,236 (26.12) 0.48 Regular exercise, Yes 31,383 (18.66) 12,012 (18.20) 0.01 Chemotherapy, Yes Anthracyclines 33,929 (51.42) Taxane 9,527 (14.44) Trastuzumab, Yes 33,408 (50.63) Endocrine therapy, Yes Tamoxifen 18,056 (27.37) Aromatase inhibitors 17,402 (26.37) Radiation therapy, Yes 47,731 (72.34) Data are expressed as number (%) or mean (standard deviation) unless otherwise noted. 1 GFR: Glomerular Filtration Rate (mL/min/1.73 m²) Among breast cancer survivors, the proportions of use in each treatment option were 51.42% for anthracycline therapy, 14.44% for taxane therapy, 50.6% for target therapy (trastuzumab) 27.37% for tamoxifen therapy, 26.37% for aromatase inhibitor therapy and 72.3% for radiation therapy. Risk of DM Among Breast Cancer Survivors Compared to the General Population According to Age Group Risk of DM in breast cancer survivors according to age group is shown in Table 2 . Breast cancer survivors were at significantly increased risk of developing DM compared to the general population. During the entire analysis period, the sHR for DM in breast cancer survivors was 1.10 (95% CI: 1.06–1.14). When stratified by age, the sHR for breast cancer survivors aged ≤ 50 was 1.27 (95% CI: 1.19–1.35), indicating substantially elevated risk in the younger age group. In contrast, for those > 50, the sHR was 1.03 (95% CI: 0.98–1.08), suggesting no significant difference in DM risk between breast cancer survivors and the general population in this older age group. The interaction term for age was statistically significant (P for interaction < 0.01), underscoring the age-dependent nature of DM risk in breast cancer survivors. Table 2 Adjusted sub-distribution hazard ratios for developing DM in breast cancer surgery survivors compared to the noncancer general population by age categories Age group Subjects (N) Case (n) IR per 1,000 person-years Model 1 (Crude) sHR (95% CI) Model 2 sHR (95% CI) Model 3 sHR (95% CI) Total period All ages Noncancer 168,214 9,535 7.97 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 65,982 4,269 9.33 1.14 (1.10–1.19) 1.16 (1.12–1.21) 1.10 (1.06–1.14) Age ≤ 50 Noncancer 84,407 2,862 4.72 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 34,039 1,439 6.01 1.25 (1.17–1.33) 1.25 (1.18–1.33) 1.27 (1.19–1.35) Age > 50 Noncancer 83,807 6,673 11.31 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 31,943 2,830 12.97 1.12 (1.07–1.17) 1.124 (1.08–1.18) 1.03 (0.98–1.08) P for interaction < .01 < .01 < .01 0–1 year All ages Noncancer 168,214 859 5.12 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 65,982 737 11.25 2.27 (2.05–2.51) 2.31 (2.09–2.55) 2.13 (1.92–2.35) Age ≤ 50 Noncancer 84,407 178 2.11 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 34,039 261 7.71 3.77 (3.10–4.58) 3.79 (3.11–4.60) 3.74 (3.08–4.55) Age > 50 Noncancer 83,807 681 8.16 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 31,943 476 15.04 1.90 (1.69–2.15) 1.91 (1.70–2.16) 1.71 (1.52–1.93) P for interaction < .01 < .01 < .01 1-year landmark analysis All ages Noncancer 167,340 8,669 8.42 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 65,050 3,531 9.01 1.04 (1-1.08) 1.06 (1.02–1.10) 1.01 (0.97–1.05) Age ≤ 50 Noncancer 84,228 2,684 5.14 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 33,679 1,178 5.74 1.08 (1.01–1.16) 1.09 (1.02–1.16) 1.11 (1.03–1.19) Age > 50 Noncancer 83,112 5,985 11.82 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 31,371 2,353 12.61 1.04 (0.99–1.09) 1.05 (1.00-1.10) 0.96 (0.92–1.01) P for interaction 0.36 0.36 0.01 3-year landmark analysis All ages Noncancer 165,144 6,603 9.48 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 62,997 2,575 9.76 1.01 (0.97–1.06) 1.03 (0.98–1.08) 0.987 (0.94–1.03) Age ≤ 50 Noncancer 83,660 2,142 6.04 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 32,849 858 6.18 1.00 (0.93–1.09) 1.01 (0.93–1.09) 1.03 (0.95–1.12) Age > 50 Noncancer 81,484 4,461 13.05 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 30,148 1,717 13.74 1.04 (0.98–1.10) 1.04 (0.99–1.10) 0.97 (0.91–1.02) P for interaction 0.53 0.51 0.20 5-year landmark analysis All ages Noncancer 143,730 3,954 10.51 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 54,121 1,487 10.44 0.98 (0.92–1.04) 1 (0.94–1.06) 0.97 (0.91–1.03) Age ≤ 50 Noncancer 73,409 1,354 7.06 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 28,542 501 6.66 0.94 (0.84–1.04) 0.94 (0.85–1.04) 0.96 (0.87–1.07) Age > 50 Noncancer 70,321 2,600 14.11 1 (ref.) 1 (ref.) 1 (ref.) Breast cancer 25,579 986 14.69 1.03 (0.95–1.11) 1.04 (0.96–1.12) 0.97 (0.90–1.05) P for interaction 0.15 0.13 0.89 IR, incidence rate; PYs, person-years; sHR, sub-distribution hazard ratio; CI, confidence interval. Model 2: adjusted for age, income status, and residential location. Model 3: adjusted for Model 2 + hypertension, dyslipidemia, chronic kidney disease, current smoking status, alcohol drinking status, regular exercise, BMI Within the first 1 year period, breast cancer survivors were at higher risk for the development of DM (sHR 2.13, 95% CI 1.92–2.35), with higher estimates in the group under 50 years of age (sHR 3.74, 95% CI 3.08–4.55) than in the group over 50 years of age (sHR 1.71, 95% CI 1.52–1.93) (P for interaction < 0.01). After applying a 1-year lag period to exclude individuals who either died or were diagnosed with DM within the first year following breast cancer diagnosis, patients under 50 years of age were at higher risk for DM (sHR 1.11, 95% CI 1.03–1.19), whereas no association was observed in patients over 50 years of age (sHR 0.96, 95% CI 0.92–1.01). When 3-year and 5-year lag periods were applied, no significant increase in DM risk was found in either age group. Risk of DM According to Clinical and Treatment-related Factors Risks of DM according to clinical and treatment-related factors are summarized in Table 3 . High BMI greater than 25(kg/m 2 ) (sHR 1.45, 95% CI 1.32–1.59), current smoking (sHR 1.72, 95% CI 1.49–1.97), hypertension (sHR 1.48, 95% CI 1.37–1.59), dyslipidemia (sHR 1.49, 95% CI 1.38–1.61) and taxane therapy (sHR 1.15, 95% CI 1.06–1.24) were associated with higher sHR for DM across all age group. Use of tamoxifen (sHR 1.1, 95% CI 1.01–1.20), AIs (sHR 1.1, 95% CI 1.01–1.20), or both (sHR 1.25, 95% CI 1.02–1.53) were associated with increased risk of DM in all participants. However, when stratified by age, increased sHR for DM was noted only in patients under 50 years old who were treated with tamoxifen (sHR 1.22, 95% CI 1.06–1.40). Alcohol drinking was associated with lower risk of DM development (sHR 0.89, 95% CI 0.83–0.97). Table 3 Adjusted sub-distribution hazard ratios for developing DM by attributable factors among breast cancer surgery survivors by age categories Factors sHR (95% CI) All age Age ≤ 50 Age > 50 BMI (kg/m²) < 25 1 (ref.) 1 (ref.) 1 (ref.) ≥ 25 1.45 (1.32–1.59) 1.66 (1.41–1.96) 1.39 (1.24–1.55) Current smoker No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.72 (1.49–1.97) 1.54 (1.22–1.94) 1.83 (1.53–2.18) Drinker No 1 (ref.) 1 (ref.) 1 (ref.) Yes 0.89 (0.83–0.97) 0.87 (0.78–0.98) 0.92 (0.83–1.02) Regular exercise No 1 (ref.) 1 (ref.) 1 (ref.) Yes 0.93 (0.86–1.01) 0.87 (0.75–1.01) 0.95 (0.86–1.04) Hypertension No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.48 (1.37–1.59) 1.76 (1.51–2.04) 1.42 (1.31–1.55) Dyslipidemia No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.49 (1.38–1.61) 2.01 (1.68–2.40) 1.40 (1.29–1.52) Chronic Kidney Disease No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.19 (0.72–1.95) 0.91 (0.40–2.09) 1.27 (0.72–2.25) Anthracyclines No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.00 (0.93–1.08) 1.13 (0.99–1.29) 0.93 (0.85–1.02) Taxane No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.15 (1.06–1.24) 1.17 (1.03–1.33) 1.12 (1.01–1.24) Trastuzumab No 1 (ref.) 1 (ref.) 1 (ref.) Yes 1.03 (0.94–1.12) 1.03 (0.88, 1.21) 1.02 (0.91–1.14) Endocrine therapy No 1 (ref.) 1 (ref.) 1 (ref.) Tamoxifen 1.10 (1.01–1.20) 1.22 (1.06–1.40) 1.06 (0.95–1.18) AIs 1.1 (1.01–1.20) 1.14 (0.90–1.46) 1.08 (0.98–1.18) Both 1.25 (1.02–1.53) 1.16 (0.77–1.76) 1.24 (0.97–1.58) Radiation therapy No 1 (ref.) 1 (ref.) 1 (ref.) Yes 0.95 (0.89–1.02) 0.93 (0.83–1.05) 0.94 (0.87–1.02) sHR, adjusted sub-distribution hazard ratio; CI, confidence interval; AIs, aromatase inhibitors; NA, Not applicable. Hazard ratios were adjusted for age, income status, residential location, hypertension, dyslipidemia, chronic kidney disease, and history of anthracyclines, taxane, trastuzumab, endocrine therapy, and radiation therapy. DISCUSSION In this study, breast cancer survivors were at higher risk of developing DM than the general population, especially those under 50 years of age. In the under-50 group, the risk of DM among breast cancer survivors was 3.7 times higher during the 0–1 year period. The risk diminished but remained higher than that of the matched control group for the first three years, with no additional increases in risk observed thereafter. In contrast, patients older than 50 demonstrated 1.7-fold increased risk of developing DM during the first year only, with no significant increase observed in subsequent years. These findings suggest that younger breast cancer survivors are more susceptible to developing DM during the initial three years following cancer treatment. This temporal pattern is consistent with a Taiwanese cohort study that reported DM risk peaked in the first year following diagnosis and then gradually declined over time, although it remained elevated even 15 years post-diagnosis.[2] However, the Taiwanese study did not compare risk between age groups and did not consider physical or behavioral factors such as BMI, smoking, or alcohol use. Previous Korean cohort studies further indicated that DM risk was highest during the initial three years after diagnosis but became statistically insignificant thereafter, but they did not compare age groups.[5, 12] However, a Canadian cohort study demonstrated that DM risk began to increase two years after breast cancer diagnosis and continued to rise beyond ten years for patients who did not receive chemotherapy, while for those who underwent chemotherapy, the risk increased immediately after diagnosis.[6] An American cohort study showed a persistently high cumulative incidence of DM from two years post-diagnosis up to ten years.[14] Both studies analyzed only cumulative incidence, an approach that lacks the temporal precision of landmark analysis, and is therefore less effective for identifying dynamic changes in risk at specific time points. In the present study, our use of landmark analysis overcame the limitations of cumulative incidence by capturing dynamic changes in DM risk over defined intervals. This approach provides a clearer depiction of how DM risk evolves over time, particularly in the context of age-specific patterns. By incorporating physical and behavioral factors such as BMI, smoking, and alcohol use, our findings offer a more comprehensive understanding of DM risk in breast cancer survivors. These factors strengthen the validity and specificity of our results compared to prior studies. One plausible explanation for the short-term spike in DM risk that we observed is that previously undiagnosed DM may be detected shortly after breast cancer diagnosis due to increased medical surveillance. Many patients are unaware of their glycemic status until they are undergoing cancer-related medical evaluations. Additionally, treatments such as chemotherapy, hormonal therapy, and steroid use during the first year may accelerate the progression from prediabetes to DM. Chemotherapy-induced nausea and vomiting (CINV), one of the most distressing side effects of chemotherapy, is commonly managed with corticosteroids, which are highly effective but also to induces hyperglycemia as a side effect.[33, 34] Corticosteroids can promote insulin resistance by inhibiting insulin synthesis, reducing insulin sensitivity, and leading to hyperglycemia.[9, 18, 35] Studies have shown that taxane-based regimens, when combined with glucocorticoids, can exacerbate hyperglycemia.[36] Furthermore, in a study of hematologic malignancies, exposure to glucocorticoids during chemotherapy was associated with increased risk of new-onset hyperglycemia (HR 1.28) and DM (HR 1.29).[37] Such glucose dysregulation may persist beyond the treatment period, reflecting the lasting impact of corticosteroids on metabolism.[38] One possible explanation for the differences in the temporal patterns observed in East Asian [2, 5] and Western studies [6, 14] is differences in insulin secretion and metabolic responses, which influence DM risk patterns. East Asian samples typically include patients with lower BMI, and therefore exhibit reduced insulin secretory capacity compared to Western samples, in which obesity-related insulin resistance is the primary driver of gradual increase in DM risk.[39] This difference in β-cell function and metabolic response, combined with a higher proportion of visceral adiposity despite lower BMI, may predispose East Asian patients to more rapid changes in DM risk.[40] These findings suggest that the short-term elevation in DM risk observed in our study reflects pathophysiology and treatment effects specific to the Asian population. Tamoxifen also appears to significantly contribute to the observed risk of DM, particularly in younger breast cancer patients. Tamoxifen use is associated with weight gain, an effect often exacerbated by concurrent chemotherapy and that is more pronounced during the early phases of treatment.[41] Patients on tamoxifen report greater dissatisfaction with weight changes compared to those on AIs.[42] Preclinical studies suggest that tamoxifen may induce adipocyte hypertrophy and increase adipose tissue, particularly in individuals with obesity, leading to insulin resistance and impaired glucose metabolism.[43] These metabolic changes may be further aggravated by high-fat diets, contributing to ectopic lipid deposition and glucose intolerance.[43] Additionally, tamoxifen’s dual role as an estrogen antagonist in breast tissue and an agonist in other tissues such as the liver may disrupt insulin regulation and lipid metabolism, promoting early hepatic insulin resistance.[18, 44] Although some studies suggest that aromatase inhibitors (AIs) increase DM risk, [16, 17] the results remain inconsistent, particularly because elevated risk is observed in younger populations but no significant effects are observed in older patients. These differences may be due to variation in study designs, follow-up durations, or the metabolic profiles of specific AI agents. In the present study, we confirmed established risk factors for DM, including obesity, hypertension, and dyslipidemia. High BMI and weight gain are significant factors associated with increased DM risk among cancer survivors.[8] Hypertension and dyslipidemia frequently coexist with DM, forming key components of metabolic syndrome, which shares genetic and environmental risk factors with DM.[45] Smoking has also been associated with increased risk of progression from normal glucose tolerance to impaired glucose tolerance and type 2 DM.[46] Therefore, recognizing and managing these risk factors is essential to reduce DM risk in cancer survivors. However, this study has several limitations. First, information regarding stage and subtype of breast cancer was not available, which could influence treatment regimens and subsequently impact the risk of developing DM. Second, the influences of other unmeasured variables—such as dietary patterns or genetic predispositions—cannot be excluded. These factors may have affected the observed associations and warrant further investigation in future studies. Third, our findings may not be fully generalizable to other countries with different healthcare systems or ethnic compositions. Future research that includes more diverse population samples would enhance the applicability of the results beyond Korea. CONCLUSION Breast cancer survivors showed markedly increased risk of DM during the first year after diagnosis. The increased risk was more prominent and persisted longer in younger women. Elevated risk was also observed in patients treated with taxane or tamoxifen, as well as those with high BMI, current smokers, and those with hypertension or dyslipidemia. Careful monitoring of DM status is needed, especially in the early survivorship period, and for patients who are young, who receive chemotherapy or tamoxifen, and who have other established risk factors for DM. Declarations Ethics approval and consent to participate This study was approved by the Samsung Medical Center Institutional Review Board (Seoul, South Korea; SMC 2020-03-108). All data were anonymized and de-identified, making informed consent unnecessary according to the approved protocol. Consent for publication Not applicable as this study does not include any identifiable individual data. Competing interests The authors declare no competing interests. CONFLICT OF INTEREST STATEMENT The authors declare that they have no conflicts of interest to disclose. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Author Contribution • Hyeongjin Shim: Conceptualization, data curation, methodology design, writing—original draft preparation, and manuscript revision.• Bong-seong Kim: Statistical analysis, data processing, and interpretation of results.• Kyungdo Han: Validation of statistical models and critical review of statistical sections.• Hye Yeon Koo: Literature review, and review of clinical content.• Seonghye Kim, Dagyeong Lee, and In Young Cho: Review and editing of the entire manuscript, oversight of clinical relevance, and coordination of data acquisition.• Wonyoung Jung: Technical editing and supervision of cardiovascular-related implications.• Dong Wook Shin: Overall project supervision, final review, and approval of the manuscript. Acknowledgements The authors acknowledge the support of Samsung Medical Center and Soongsil University for their collaboration in data management and statistical analysis. Special thanks to the NHIS for providing access to their comprehensive healthcare database. Availability of data and materials The data supporting the findings of this study are derived from the National Health Insurance Service (NHIS) database of South Korea. Access to this database is restricted to researchers with approved study protocols. Further inquiries regarding data access can be made to the corresponding authors. References Sha, R., et al., Global burden of breast cancer and attributable risk factors in 204 countries and territories, from 1990 to 2021: results from the Global Burden of Disease Study 2021. Biomarker Research, 2024. 12 (1): p. 87. Wang, C.Y., S.R. Shih, and K.C. Huang, Increasing risk of diabetes mellitus in postmenopausal women with newly diagnosed primary breast cancer. J Diabetes Investig, 2020. 11 (2): p. 490-498. Accordino, M.K., et al., Incidence and Predictors of Diabetes Mellitus after a Diagnosis of Early-Stage Breast Cancer in the Elderly Using Real-World Data. Breast Cancer Res Treat, 2020. 183 (1): p. 201-211. Ng, H.S., et al., Incidence of comorbidities in women with breast cancer treated with tamoxifen or an aromatase inhibitor: an Australian population-based cohort study. J Comorb, 2018. 8 (1): p. 16-24. Hwangbo, Y., et al., Incidence of Diabetes After Cancer Development: A Korean National Cohort Study. JAMA Oncol, 2018. 4 (8): p. 1099-1105. Lipscombe, L.L., et al., Incidence of diabetes among postmenopausal breast cancer survivors. Diabetologia, 2013. 56 (3): p. 476-83. Ji, G.Y., et al., Incidences of diabetes and prediabetes among female adult breast cancer patients after systemic treatment. Med Oncol, 2013. 30 (3): p. 687. Koo, H.Y., et al., Weight Change After Cancer Diagnosis and Risk of Diabetes Mellitus: A Population-Based Nationwide Study. Cancer Res Treat, 2024. Clore, J.N. and L. Thurby-Hay, Glucocorticoid-induced hyperglycemia. Endocr Pract, 2009. 15 (5): p. 469-74. Rao Kondapally Seshasai, S., et al., Diabetes mellitus, fasting glucose, and risk of cause-specific death. N Engl J Med, 2011. 364 (9): p. 829-841. Tobe, A., et al., Impact of Diabetes on Patient Outcomes in Breast Cancer Patients. Breast Care, 2022. 17 (5): p. 480-485. Kang, D., et al., Temporal patterns of chronic disease incidence after breast cancer: a nationwide population-based cohort study. Sci Rep, 2022. 12 (1): p. 5489. Santorelli, M.L., et al., Hormonal therapy for breast cancer and diabetes incidence among postmenopausal women. Ann Epidemiol, 2016. 26 (6): p. 436-40. Kwan, M.L., et al., Risk of Cardiometabolic Risk Factors in Women With and Without a History of Breast Cancer: The Pathways Heart Study. J Clin Oncol, 2022. 40 (15): p. 1635-1646. Sun, L.M., et al., Association of tamoxifen use and increased diabetes among Asian women diagnosed with breast cancer. Br J Cancer, 2014. 111 (9): p. 1836-42. Hamood, R., et al., Diabetes After Hormone Therapy in Breast Cancer Survivors: A Case-Cohort Study. J Clin Oncol, 2018. 36 (20): p. 2061-2069. Kim, J.E., et al., Effects of Endocrine Therapy on Cardiovascular Diseases and Type 2 Diabetes Among Breast Cancer Survivors: The National Health Insurance Service Database of Korea. J Am Heart Assoc, 2022. 11 (20): p. e026743. Lipscombe, L.L., et al., Association between tamoxifen treatment and diabetes: a population-based study. Cancer, 2012. 118 (10): p. 2615-22. Lee, Y.H., et al., Data Analytic Process of a Nationwide Population-Based Study Using National Health Information Database Established by National Health Insurance Service. Diabetes Metab J, 2016. 40 (1): p. 79-82. Cheol Seong, S., et al., Data Resource Profile: The National Health Information Database of the National Health Insurance Service in South Korea. Int J Epidemiol, 2017. 46 (3): p. 799-800. Shin, D.W., et al., National General Health Screening Program in Korea: history, current status, and future direction. Precision and Future Medicine, 2022. 6 (1): p. 9-31. Seo, H.J., I.H. Oh, and S.J. Yoon, A comparison of the cancer incidence rates between the national cancer registry and insurance claims data in Korea. Asian Pac J Cancer Prev, 2012. 13 (12): p. 6163-8. Lee, C.K., et al., Nationwide validation study of diagnostic algorithms for inflammatory bowel disease in Korean National Health Insurance Service database. J Gastroenterol Hepatol, 2020. 35 (5): p. 760-768. Chung, I.Y., et al., Nationwide Analysis of Treatment Patterns for Korean Breast Cancer Survivors Using National Health Insurance Service Data. J Korean Med Sci, 2018. 33 (44): p. e276. Cho, E.B., et al., The risk of type 2 diabetes mellitus in multiple sclerosis and neuromyelitis optica spectrum disorder: A nationwide cohort study. Mult Scler Relat Disord, 2024. 85 : p. 105519. Jung, W., et al., Changes in physical activity and diabetes risk after cancer diagnosis: a nationwide cohort study. J Cancer Surviv, 2024. Chung, I.Y., et al., Nationwide Analysis of Treatment Patterns for Korean Breast Cancer Survivors Using National Health Insurance Service Data. J Korean Med Sci, 2018. 33 (44): p. e276. Lee, J., et al., Long-term risk of congestive heart failure in younger breast cancer survivors: A nationwide study by the SMARTSHIP group. Cancer, 2020. 126 (1): p. 181-188. Kim, H.T., Cumulative incidence in competing risks data and competing risks regression analysis. Clin Cancer Res, 2007. 13 (2 Pt 1): p. 559-65. Gray, R.J., A Class of K-Sample Tests for Comparing the Cumulative Incidence of a Competing Risk. The Annals of Statistics, 1988. 16 (3): p. 1141-1154. Fine, J.P. and R.J. Gray, A Proportional Hazards Model for the Subdistribution of a Competing Risk. Journal of the American Statistical Association, 1999. 94 (446): p. 496-509. Dafni, U., Landmark Analysis at the 25-Year Landmark Point. Circulation: Cardiovascular Quality and Outcomes, 2011. 4 (3): p. 363-371. Barbour, S.Y., Corticosteroids in the treatment of chemotherapy-induced nausea and vomiting. J Natl Compr Canc Netw, 2012. 10 (4): p. 493-9. de Boer-Dennert, M., et al., Patient perceptions of the side-effects of chemotherapy: the influence of 5HT3 antagonists. Br J Cancer, 1997. 76 (8): p. 1055-61. Bordeleau, L., et al., Diabetes and breast cancer among women with BRCA1 and BRCA2 mutations. Cancer, 2011. 117 (9): p. 1812-8. Mahin, D., et al., Hyperglycemia and Glycemic Variability Associated with Glucocorticoids in Women without Pre-Existing Diabetes Undergoing Neoadjuvant or Adjuvant Taxane Chemotherapy for Early-Stage Breast Cancer. J Clin Med, 2023. 12 (5). Moore-Vasram, S., et al., Determining the Associations Between Glucocorticoid Use During Hematologic Chemotherapy Treatment and New-onset Diabetes and Hyperglycemia and Mortality: A Population-based Cohort Study. Can J Diabetes, 2024. 48 (3): p. 195-203.e1. Dehghani, M., et al., Glucocorticoid induced diabetes and lipid profiles disorders amongst lymphoid malignancy survivors. Diabetes Metab Syndr, 2020. 14 (6): p. 1645-1649. Chiu, K.C., L.M. Chuang, and C. Yoon, Comparison of measured and estimated indices of insulin sensitivity and beta cell function: impact of ethnicity on insulin sensitivity and beta cell function in glucose-tolerant and normotensive subjects. J Clin Endocrinol Metab, 2001. 86 (4): p. 1620-5. Appropriate body-mass index for Asian populations and its implications for policy and intervention strategies. Lancet, 2004. 363 (9403): p. 157-63. Lima, M.T.M., et al., Temporal influence of endocrine therapy with tamoxifen and chemotherapy on nutritional risk and obesity in breast cancer patients. BMC Cancer, 2017. 17 (1): p. 578. McGowan, P., et al., Weight gain in breast cancer patients: Tamoxifen versus anastrazole. Journal of Clinical Oncology, 2006. 24 (18_suppl): p. 10544-10544. Scalzo, R.L., et al., Breast Cancer Endocrine Therapy Promotes Weight Gain With Distinct Adipose Tissue Effects in Lean and Obese Female Mice. Endocrinology, 2021. 162 (11). Klöting, N., et al., Tamoxifen treatment causes early hepatic insulin resistance. Acta Diabetol, 2020. 57 (4): p. 495-498. Cheung, B.M., The hypertension-diabetes continuum. J Cardiovasc Pharmacol, 2010. 55 (4): p. 333-9. Śliwińska-Mossoń, M. and H. Milnerowicz, The impact of smoking on the development of diabetes and its complications. Diab Vasc Dis Res, 2017. 14 (4): p. 265-276. Additional Declarations No competing interests reported. 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01:53:17","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6010947/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6010947/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":76496692,"identity":"f7e2fe5f-c241-48de-a5d4-5377d18f8d63","added_by":"auto","created_at":"2025-02-17 18:32:27","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":761278,"visible":true,"origin":"","legend":"\u003cp\u003eSee image above for figure legend.\u003c/p\u003e","description":"","filename":"floatimage2.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-6010947/v1/2a6d2fe00c2b184fae8ff8a4.jpeg"},{"id":76809305,"identity":"47f8d0db-da12-42a7-b888-f666e2088230","added_by":"auto","created_at":"2025-02-21 04:01:48","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2335079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6010947/v1/069d10b0-9da1-48ca-ac8a-6de6f7cbd5c2.pdf"},{"id":76496694,"identity":"988ce18b-bb26-4a3e-baff-ecf5e4245127","added_by":"auto","created_at":"2025-02-17 18:32:27","extension":"docx","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":27180,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementaryTablesvfinal250120SHJ.docx","url":"https://assets-eu.researchsquare.com/files/rs-6010947/v1/b3893666257fd6df7cdf4c2a.docx"}],"financialInterests":"No competing interests reported.","formattedTitle":"Risk of Newly Incident Diabetes Mellitus and Treatment Risk Factors in Breast Cancer Survivors: Landmark Analyses of Nationwide Data","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eBreast cancer is the most commonly diagnosed cancer among women worldwide, and its incidence continues to rise.[1] Breast cancer patients are reported to be at higher risk of diabetes mellitus (DM) than the general population [2\u0026ndash;7], mainly due to weight gain[8] and corticosteroid use.[9] DM is linked to various medical conditions and reduces life expectancy,[10] and is also associated with poor breast cancer prognosis.[11] Therefore, monitoring the development of DM in breast cancer patients is necessary for effective health management.\u003c/p\u003e \u003cp\u003eThe risk of DM in breast cancer survivors might differ according to time since diagnosis (i.e., short-term vs. long-term risk) or patient age (i.e., premenopausal vs. post-menopausal). However, most previous studies regarding the risk of DM and breast cancer did not consider time-related patterns [3, 5, 7]. A few studies reported temporal patterns but showed inconsistent results, with some reporting increased risk in the short-term only [12, 13] and others reporting increased risk with time.[2, 6, 14, 15]\u003c/p\u003e \u003cp\u003eMenopausal status is an important factor determining the use of hormonal therapies, such as tamoxifen or aromatase inhibitors. In addition, there are interactions between menopausal status and obesity/central obesity that are relevant to the incidence of DM.[15, 16] However, most previous studies did not consider age or menopausal status in their assessments of DM risk [4, 5, 7, 14] or limited the analysis to specific age groups (e.g., older women only [2, 3, 6]) (Supplementary Table\u0026nbsp;1).\u003c/p\u003e \u003cp\u003eCancer treatment can also influence the risk of DM in breast cancer patients. Previous studies reported increased risk with chemotherapy [3, 6], tamoxifen use [4, 15\u0026ndash;18], and aromatase inhibitor (AI) use [16, 17]. However, other studies found no associations between risk of DM and hormonal therapy [2, 13], or even decreased risk with AI treatment [15]. Moreover, many studies did not incorporate age stratification into their analysis [4, 14, 16] or included older women only [2, 3, 6, 13, 18] (Supplementary Table\u0026nbsp;2).\u003c/p\u003e \u003cp\u003eTherefore, in this study we examined short-term and long-term risks of DM in breast cancer patients separately and analyzed risk by stratifying patients according to age into groups younger than and older than 50 years to account for the impact of menopause. Additionally, we extensively investigated the effects of cancer treatment on DM risk using nationwide cohort data and performed further age stratification to minimize the influence of menopause.\u003c/p\u003e"},{"header":"METHODS","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eData and Study Setting\u003c/h2\u003e \u003cp\u003eIn South Korea, the National Health Insurance Service (NHIS) ensures mandatory universal health coverage for 97% of the population. The NHIS database is comprehensive, containing sociodemographic information and healthcare claims data such as medical procedures, diagnoses, prescriptions, outpatient visits, and hospital admissions.[19, 20] Additionally, the NHIS administers biennial health screenings,[21] which gather information on past medical history, lifestyle behaviors (including smoking, drinking, and physical activity), anthropometric measurements, and laboratory test results. These screenings are provided for all employees regardless of age and for nonemployees aged 40 and older. The NHIS database is validated and widely used for epidemiological and clinical research.[22, 23]\u003c/p\u003e \u003cp\u003eFor this study, we utilized data from the NHIS database to analyze DM risk among breast cancer survivors. NHIS data provided a robust foundation for this study due to the comprehensive nature and reliability of epidemiological and clinical studies. This study was approved by the Samsung Medical Center Institutional Review Board (Seoul, South Korea; SMC 2020-03-108). All information used for analyses was anonymized and de-identified; therefore, informed consent was not required. The database is open to all researchers whose study protocols are approved by the official review committee.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eStudy Population\u003c/h3\u003e\n\u003cp\u003eThis study included 151,422 women who were newly diagnosed with invasive breast cancer and underwent surgery between January 1, 2010, and December 31, 2016. Newly diagnosed invasive breast cancer cases were identified using C50 and V193 codes. In Korea, the V193 code is assigned only after biopsy-confirmed diagnosis, enhancing the accuracy of cancer identification in NHIS data.[24]\u003c/p\u003e \u003cp\u003eWe excluded participants who did not receive surgery within one year of their breast cancer diagnosis (n\u0026thinsp;=\u0026thinsp;24,856), had histories of other cancers prior to breast cancer (n\u0026thinsp;=\u0026thinsp;5,514), were under 18 years old, had prior diagnoses of DM (n\u0026thinsp;=\u0026thinsp;9,431), or had missing health screening data (n\u0026thinsp;=\u0026thinsp;3,393).\u003c/p\u003e \u003cp\u003eTo construct the control group, breast cancer survivors were matched in a 1:3 ratio with controls based on age, with the index date for controls corresponding to the date of breast cancer diagnosis in the survivor group. To enhance comparability, we included only individuals who had undergone a general health examination within two years prior to the index date in both groups. By linking data from the national health screening program, we obtained detailed information on health behaviors, anthropometric measurements, and laboratory results, allowing us to include various covariates in the analysis.\u003c/p\u003e \u003cp\u003eAfter applying these criteria, 67,938 breast cancer survivors and 171,250 controls were initially included. Subsequently, we excluded individuals with missing health screening data (n\u0026thinsp;=\u0026thinsp;683 in the breast cancer group; n\u0026thinsp;=\u0026thinsp;1,965 in the control group) and those with fasting glucose levels\u0026thinsp;\u0026ge;\u0026thinsp;126 mg/dL during screening (n\u0026thinsp;=\u0026thinsp;1,273 and n\u0026thinsp;=\u0026thinsp;3,036, respectively). As a result, the final analysis included 65,982 breast cancer survivors and 168,214 matched controls (Fig.\u0026nbsp;1).\u003c/p\u003e\n\u003ch3\u003eOutcomes\u003c/h3\u003e\n\u003cp\u003eThe primary outcome of this study was the incidence of newly diagnosed DM, identified by the use of antidiabetic medications along with ICD-10 codes for DM (E11\u0026ndash;E14).[8, 25, 26] Participants were followed from the date of breast cancer diagnosis until the occurrence of newly diagnosed DM, a censoring event (e.g., death or outmigration), or the end of the study on December 31, 2020, whichever came first.\u003c/p\u003e\n\u003ch3\u003eCovariates\u003c/h3\u003e\n\u003cp\u003eBreast cancer treatment information was based on patient data within 1 year after diagnosis of breast cancer.[27, 28] Participant comorbidities were determined using laboratory measures, insurance claims, and prescription data prior to the index date. Hypertension was identified by ICD-10 codes (I10.x-I13.x and I15.x), being treated with antihypertensive medication, or blood pressure readings of \u0026ge;\u0026thinsp;140/90 mmHg. Dyslipidemia was defined by ICD-10 code E78.x, taking any prescribed lipid-lowering drug, or a total cholesterol level of \u0026ge;\u0026thinsp;240 mg/dL. Chronic kidney disease was diagnosed as a glomerular filtration rate of \u0026lt;\u0026thinsp;60 mL/min/1.73 m\u0026sup2;, and estimations were performed using the Modification of Diet in Renal Disease equation.\u003c/p\u003e \u003cp\u003eIncome level was categorized based on health insurance premiums. Low-income status was defined as being in the lowest quartile of premiums or being registered in the Medical Aid program. Geographic residence was classified into rural and urban categories based on primary local authority districts (shi/gun/gu).\u003c/p\u003e \u003cp\u003eBody mass index (BMI) was determined by dividing weight in kilograms by height in meters squared (kg/m\u0026sup2;). Information regarding smoking status (current or non-smoker) and alcohol consumption (yes or no) was collected during the general health screening following cancer diagnosis. Regular exercise was defined as vigorous activity for more than 20 minutes per session \u0026ge;3 days per week or moderate-intensity activity for more than 30 minutes per session \u0026ge;5 days per week.\u003c/p\u003e \u003cdiv id=\"Sec7\" class=\"Section2\"\u003e \u003ch2\u003eStatistical Analysis\u003c/h2\u003e \u003cp\u003eBaseline characteristics are reported as means with standard deviations for continuous variables and numbers with percentages for categorical variables. Participants were followed from the date of diagnosis, considering the first year separately from the period beyond one year after baseline assessment, until the first occurrence of a DM diagnosis, death, or the study\u0026rsquo;s conclusion, whichever occurred first. Person-time was calculated starting one year after baseline, and the crude incidence rate of DM was expressed per 1,000 person-years by dividing the number of DM events by the total person-years of follow-up. The cumulative incidence of DM was estimated using a competing risk framework, treating death as a competing event.[29] The incidence of DM was compared between breast cancer survivors and the general population using the Gray-K test.[30]\u003c/p\u003e \u003cp\u003eThe Fine-Gray proportional sub-distribution hazards model was applied to evaluate the relative risk of DM in breast cancer survivors compared to the general population. This approach allowed for the calculation of sub-distribution hazard ratios (sHRs) and 95% confidence intervals (CIs), explicitly accounting for death as a competing risk.[16, 31] The analysis incorporated adjustments in a stepwise manner: the crude model was unadjusted, the second model was adjusted for sociodemographic factors (age, residential location, and household income), and the final model included further adjustment for comorbidities, BMI, smoking status, alcohol consumption, and regular exercise.\u003c/p\u003e \u003cp\u003eLandmark analyses were performed to assess DM risk over distinct follow-up intervals, including 0\u0026ndash;1 year, 1 year, 3 years, and 5 years post-breast cancer diagnosis.[32] Further stratified analyses were conducted by age group (\u0026le;\u0026thinsp;50 and \u0026gt;\u0026thinsp;50 years) based on the median age of menopause in Korean women.[12] This definition was chosen due to the absence of menopausal status information in our current cohort data.\u003c/p\u003e \u003cp\u003eWithin the breast cancer survivor cohort, adjusted sub-distribution hazard ratios (sHRs) for DM incidence were calculated, accounting for age, residential location, income status, BMI, smoking status, alcohol consumption, regular exercise, hypertension, dyslipidemia, chronic kidney disease, and treatment-related factors, including anthracyclines, taxane, trastuzumab, endocrine therapies (tamoxifen or aromatase inhibitors), and radiation therapy. These analyses were also stratified by age (\u0026le;\u0026thinsp;50 and \u0026gt;\u0026thinsp;50 years).\u003c/p\u003e \u003cp\u003eAll statistical analyses were conducted using SAS version 9.4, and statistical significance was determined according to a two-sided P-value of \u0026lt;\u0026thinsp;0.05.\u003c/p\u003e \u003c/div\u003e"},{"header":"RESULTS","content":"\u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003eBaseline Characteristics\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e shows the baseline characteristics of participants. The average age was older in the breast cancer group (51.08\u0026thinsp;\u0026plusmn;\u0026thinsp;8.57 vs. 50.92\u0026thinsp;\u0026plusmn;\u0026thinsp;8.52). Breast cancer survivors were more likely to have higher incomes (Q4, 33.29% vs. 31.26%). Breast cancer survivors were more likely to live in urban areas (50.07% vs. 46.86%). Breast cancer survivors were more likely to have hypertension (16.72% vs 16.34%) and chronic kidney disease (0.25% vs. 0.18%). Among breast cancer survivors, there were more current smokers (3.84% vs. 3.51%), and fewer individuals engaged in regular exercise (18.2% vs. 18.66%).\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\u003eBaseline characteristics of the study population\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"char\" char=\".\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eBreast Cancer\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003e\u003cem\u003ep-value\u003c/em\u003e\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;169,214)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003cp\u003e(N\u0026thinsp;=\u0026thinsp;65,982)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAge at baseline, mean (SD), years\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e50.92 (8.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e50.08 (8.57)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eComorbidity, Yes\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e27,479 (16.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e11,034 (16.72)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.02\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDyslipidemia\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e21,204 (12.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e8,499 (12.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.07\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic kidney disease (GFR\u0026thinsp;\u0026lt;\u0026thinsp;60 )\u003c/b\u003e\u003csup\u003e\u003cb\u003e1\u003c/b\u003e\u003c/sup\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e6,441 (3.83)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,544 (3.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.76\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eIncome status (Quartile)\u003c/b\u003e\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 \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQ1\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e40,915 (24.32)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15,095 (22.88)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQ2\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e36,043 (21.43)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e13,757 (20.85)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQ3\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e38,668 (22.99)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e15,164 (22.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eQ4\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e52,588 (31.26)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e21,966 (33.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eResidential location, Urban\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e78,827 (46.86)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33,036 (50.07)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u0026thinsp;\u0026ge;\u0026thinsp;25 (kg/m\u0026sup2;)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e45,763 (27.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17,856 (27.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eGlucose (mg/dL)\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e92.38 (10.45)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e92.88 (10.49)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent smoker, Yes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e5,912 (3.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e2,537 (3.84)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrinker, Yes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e43,702 (25.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17,236 (26.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.48\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegular exercise, Yes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c2\"\u003e \u003cp\u003e31,383 (18.66)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e12,012 (18.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChemotherapy, Yes\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthracyclines\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33,929 (51.42)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTaxane\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e9,527 (14.44)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrastuzumab, Yes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e33,408 (50.63)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEndocrine therapy, Yes\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTamoxifen\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e18,056 (27.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAromatase inhibitors\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e17,402 (26.37)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiation therapy, Yes\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"char\" char=\".\" colname=\"c3\"\u003e \u003cp\u003e47,731 (72.34)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e\u0026nbsp;\u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eData are expressed as number (%) or mean (standard deviation) unless otherwise noted.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003e\u003csup\u003e1\u003c/sup\u003eGFR: Glomerular Filtration Rate (mL/min/1.73 m\u0026sup2;)\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eAmong breast cancer survivors, the proportions of use in each treatment option were 51.42% for anthracycline therapy, 14.44% for taxane therapy, 50.6% for target therapy (trastuzumab) 27.37% for tamoxifen therapy, 26.37% for aromatase inhibitor therapy and 72.3% for radiation therapy.\u003c/p\u003e \u003cp\u003e \u003cb\u003eRisk of DM Among Breast Cancer Survivors Compared to the General Population According to Age Group\u003c/b\u003e \u003c/p\u003e \u003cp\u003eRisk of DM in breast cancer survivors according to age group is shown in Table\u0026nbsp;\u003cspan refid=\"Tab2\" class=\"InternalRef\"\u003e2\u003c/span\u003e. Breast cancer survivors were at significantly increased risk of developing DM compared to the general population. During the entire analysis period, the sHR for DM in breast cancer survivors was 1.10 (95% CI: 1.06\u0026ndash;1.14). When stratified by age, the sHR for breast cancer survivors aged\u0026thinsp;\u0026le;\u0026thinsp;50 was 1.27 (95% CI: 1.19\u0026ndash;1.35), indicating substantially elevated risk in the younger age group. In contrast, for those\u0026thinsp;\u0026gt;\u0026thinsp;50, the sHR was 1.03 (95% CI: 0.98\u0026ndash;1.08), suggesting no significant difference in DM risk between breast cancer survivors and the general population in this older age group. The interaction term for age was statistically significant (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.01), underscoring the age-dependent nature of DM risk in breast cancer survivors.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab2\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 2\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdjusted sub-distribution hazard ratios for developing DM in breast cancer surgery survivors compared to the noncancer general population by age categories\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"9\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c5\" colnum=\"5\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c6\" colnum=\"6\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c7\" colnum=\"7\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c8\" colnum=\"8\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c9\" colnum=\"9\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e\u0026nbsp;\u003c/th\u003e \u003cth align=\"left\" colspan=\"2\" nameend=\"c3\" namest=\"c2\"\u003e \u003cp\u003eAge group\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eSubjects (N)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c5\"\u003e \u003cp\u003eCase (n)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c6\"\u003e \u003cp\u003eIR per 1,000 person-years\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c7\"\u003e \u003cp\u003eModel 1 (Crude)\u003c/p\u003e \u003cp\u003esHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c8\"\u003e \u003cp\u003eModel 2\u003c/p\u003e \u003cp\u003esHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c9\"\u003e \u003cp\u003eModel 3\u003c/p\u003e \u003cp\u003esHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003eTotal period\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAll ages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168,214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e9,535\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65,982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,269\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.33\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.14 (1.10\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.16 (1.12\u0026ndash;1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.10 (1.06\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84,407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,862\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e4.72\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,439\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.25 (1.17\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.25 (1.18\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.27 (1.19\u0026ndash;1.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83,807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,673\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.31\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31,943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,830\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.97\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.12 (1.07\u0026ndash;1.17)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.124 (1.08\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.03 (0.98\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \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=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e0\u0026ndash;1 year\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAll ages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e168,214\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e859\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.12\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65,982\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e737\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e2.27 (2.05\u0026ndash;2.51)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e2.31 (2.09\u0026ndash;2.55)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e2.13 (1.92\u0026ndash;2.35)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84,407\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e2.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e34,039\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e261\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.71\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e3.77 (3.10\u0026ndash;4.58)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e3.79 (3.11\u0026ndash;4.60)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e3.74 (3.08\u0026ndash;4.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83,807\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e681\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.16\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31,943\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e476\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e15.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.90 (1.69\u0026ndash;2.15)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.91 (1.70\u0026ndash;2.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.71 (1.52\u0026ndash;1.93)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \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=\"left\" colname=\"c7\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e1-year landmark analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAll ages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e167,340\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e8,669\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e8.42\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e65,050\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,531\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.01\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 (1-1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.06 (1.02\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.01 (0.97\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e84,228\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,684\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.14\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e33,679\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,178\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e5.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.08 (1.01\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.09 (1.02\u0026ndash;1.16)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.11 (1.03\u0026ndash;1.19)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83,112\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e5,985\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e11.82\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e31,371\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,353\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e12.61\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 (0.99\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.05 (1.00-1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.96 (0.92\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \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=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.36\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.01\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e3-year landmark analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAll ages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e165,144\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e6,603\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.48\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e62,997\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,575\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e9.76\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.01 (0.97\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.03 (0.98\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.987 (0.94\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e83,660\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,142\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.04\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e32,849\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e858\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.18\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.00 (0.93\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.01 (0.93\u0026ndash;1.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1.03 (0.95\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e81,484\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e4,461\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.05\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e30,148\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,717\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e13.74\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.04 (0.98\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04 (0.99\u0026ndash;1.10)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.97 (0.91\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \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=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.53\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.20\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\" morerows=\"5\" rowspan=\"6\"\u003e \u003cp\u003e\u003cb\u003e5-year landmark analysis\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAll ages\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e143,730\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e3,954\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.51\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e54,121\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,487\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e10.44\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.98 (0.92\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (0.94\u0026ndash;1.06)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.97 (0.91\u0026ndash;1.03)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e73,409\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e1,354\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e7.06\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e28,542\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e501\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e6.66\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.94 (0.84\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.94 (0.85\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.96 (0.87\u0026ndash;1.07)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e\u003cb\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/b\u003e\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eNoncancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e70,321\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e2,600\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.11\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e\u0026nbsp;\u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eBreast cancer\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e25,579\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c5\"\u003e \u003cp\u003e986\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c6\"\u003e \u003cp\u003e14.69\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c7\"\u003e \u003cp\u003e1.03 (0.95\u0026ndash;1.11)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e1.04 (0.96\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.97 (0.90\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colspan=\"3\" nameend=\"c3\" namest=\"c1\"\u003e \u003cp\u003e\u003cem\u003eP\u003c/em\u003e for interaction\u003c/p\u003e \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=\"left\" colname=\"c7\"\u003e \u003cp\u003e0.15\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c8\"\u003e \u003cp\u003e0.13\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c9\"\u003e \u003cp\u003e0.89\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eIR, incidence rate; PYs, person-years; sHR, sub-distribution hazard ratio; CI, confidence interval.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 2: adjusted for age, income status, and residential location.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"9\"\u003eModel 3: adjusted for Model 2\u0026thinsp;+\u0026thinsp;hypertension, dyslipidemia, chronic kidney disease, current smoking status, alcohol drinking status, regular exercise, BMI\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003cp\u003eWithin the first 1 year period, breast cancer survivors were at higher risk for the development of DM (sHR 2.13, 95% CI 1.92\u0026ndash;2.35), with higher estimates in the group under 50 years of age (sHR 3.74, 95% CI 3.08\u0026ndash;4.55) than in the group over 50 years of age (sHR 1.71, 95% CI 1.52\u0026ndash;1.93) (P for interaction\u0026thinsp;\u0026lt;\u0026thinsp;0.01).\u003c/p\u003e \u003cp\u003eAfter applying a 1-year lag period to exclude individuals who either died or were diagnosed with DM within the first year following breast cancer diagnosis, patients under 50 years of age were at higher risk for DM (sHR 1.11, 95% CI 1.03\u0026ndash;1.19), whereas no association was observed in patients over 50 years of age (sHR 0.96, 95% CI 0.92\u0026ndash;1.01). When 3-year and 5-year lag periods were applied, no significant increase in DM risk was found in either age group.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eRisk of DM According to Clinical and Treatment-related Factors\u003c/h3\u003e\n\u003cp\u003eRisks of DM according to clinical and treatment-related factors are summarized in Table\u0026nbsp;\u003cspan refid=\"Tab3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. High BMI greater than 25(kg/m\u003csup\u003e2\u003c/sup\u003e) (sHR 1.45, 95% CI 1.32\u0026ndash;1.59), current smoking (sHR 1.72, 95% CI 1.49\u0026ndash;1.97), hypertension (sHR 1.48, 95% CI 1.37\u0026ndash;1.59), dyslipidemia (sHR 1.49, 95% CI 1.38\u0026ndash;1.61) and taxane therapy (sHR 1.15, 95% CI 1.06\u0026ndash;1.24) were associated with higher sHR for DM across all age group. Use of tamoxifen (sHR 1.1, 95% CI 1.01\u0026ndash;1.20), AIs (sHR 1.1, 95% CI 1.01\u0026ndash;1.20), or both (sHR 1.25, 95% CI 1.02\u0026ndash;1.53) were associated with increased risk of DM in all participants. However, when stratified by age, increased sHR for DM was noted only in patients under 50 years old who were treated with tamoxifen (sHR 1.22, 95% CI 1.06\u0026ndash;1.40). Alcohol drinking was associated with lower risk of DM development (sHR 0.89, 95% CI 0.83\u0026ndash;0.97).\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab3\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 3\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eAdjusted sub-distribution hazard ratios for developing DM by attributable factors among breast cancer surgery survivors by age categories\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"4\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c4\" colnum=\"4\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\" morerows=\"1\" rowspan=\"2\"\u003e \u003cp\u003eFactors\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colspan=\"3\" nameend=\"c4\" namest=\"c2\"\u003e \u003cp\u003esHR (95% CI)\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eAll age\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026le;\u0026thinsp;50\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c4\"\u003e \u003cp\u003eAge\u0026thinsp;\u0026gt;\u0026thinsp;50\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eBMI\u003c/b\u003e (kg/m\u0026sup2;)\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026lt;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u0026ge;\u0026thinsp;25\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.45 (1.32\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.66 (1.41\u0026ndash;1.96)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.39 (1.24\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eCurrent smoker\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.72 (1.49\u0026ndash;1.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.54 (1.22\u0026ndash;1.94)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.83 (1.53\u0026ndash;2.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDrinker\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.89 (0.83\u0026ndash;0.97)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.78\u0026ndash;0.98)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.92 (0.83\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRegular exercise\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.93 (0.86\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.87 (0.75\u0026ndash;1.01)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.95 (0.86\u0026ndash;1.04)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eHypertension\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.48 (1.37\u0026ndash;1.59)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.76 (1.51\u0026ndash;2.04)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.42 (1.31\u0026ndash;1.55)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eDyslipidemia\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.49 (1.38\u0026ndash;1.61)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e2.01 (1.68\u0026ndash;2.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.40 (1.29\u0026ndash;1.52)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eChronic Kidney Disease\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.19 (0.72\u0026ndash;1.95)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.91 (0.40\u0026ndash;2.09)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.27 (0.72\u0026ndash;2.25)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eAnthracyclines\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.00 (0.93\u0026ndash;1.08)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.13 (0.99\u0026ndash;1.29)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.93 (0.85\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTaxane\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.15 (1.06\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.17 (1.03\u0026ndash;1.33)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.12 (1.01\u0026ndash;1.24)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eTrastuzumab\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.03 (0.94\u0026ndash;1.12)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.03 (0.88, 1.21)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.02 (0.91\u0026ndash;1.14)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eEndocrine therapy\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eTamoxifen\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.10 (1.01\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.22 (1.06\u0026ndash;1.40)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.06 (0.95\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eAIs\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.1 (1.01\u0026ndash;1.20)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.14 (0.90\u0026ndash;1.46)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.08 (0.98\u0026ndash;1.18)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eBoth\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1.25 (1.02\u0026ndash;1.53)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1.16 (0.77\u0026ndash;1.76)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1.24 (0.97\u0026ndash;1.58)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003e\u003cb\u003eRadiation therapy\u003c/b\u003e\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 \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eNo\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e1 (ref.)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eYes\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003e0.95 (0.89\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003e0.93 (0.83\u0026ndash;1.05)\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c4\"\u003e \u003cp\u003e0.94 (0.87\u0026ndash;1.02)\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003ctfoot\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003esHR, adjusted sub-distribution hazard ratio; CI, confidence interval; AIs, aromatase inhibitors; NA, Not applicable.\u003c/td\u003e\u003c/tr\u003e \u003ctr\u003e\u003ctd colspan=\"4\"\u003eHazard ratios were adjusted for age, income status, residential location, hypertension, dyslipidemia, chronic kidney disease, and history of anthracyclines, taxane, trastuzumab, endocrine therapy, and radiation therapy.\u003c/td\u003e\u003c/tr\u003e \u003c/tfoot\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn this study, breast cancer survivors were at higher risk of developing DM than the general population, especially those under 50 years of age. In the under-50 group, the risk of DM among breast cancer survivors was 3.7 times higher during the 0\u0026ndash;1 year period. The risk diminished but remained higher than that of the matched control group for the first three years, with no additional increases in risk observed thereafter. In contrast, patients older than 50 demonstrated 1.7-fold increased risk of developing DM during the first year only, with no significant increase observed in subsequent years. These findings suggest that younger breast cancer survivors are more susceptible to developing DM during the initial three years following cancer treatment.\u003c/p\u003e \u003cp\u003eThis temporal pattern is consistent with a Taiwanese cohort study that reported DM risk peaked in the first year following diagnosis and then gradually declined over time, although it remained elevated even 15 years post-diagnosis.[2] However, the Taiwanese study did not compare risk between age groups and did not consider physical or behavioral factors such as BMI, smoking, or alcohol use. Previous Korean cohort studies further indicated that DM risk was highest during the initial three years after diagnosis but became statistically insignificant thereafter, but they did not compare age groups.[5, 12]\u003c/p\u003e \u003cp\u003eHowever, a Canadian cohort study demonstrated that DM risk began to increase two years after breast cancer diagnosis and continued to rise beyond ten years for patients who did not receive chemotherapy, while for those who underwent chemotherapy, the risk increased immediately after diagnosis.[6] An American cohort study showed a persistently high cumulative incidence of DM from two years post-diagnosis up to ten years.[14] Both studies analyzed only cumulative incidence, an approach that lacks the temporal precision of landmark analysis, and is therefore less effective for identifying dynamic changes in risk at specific time points.\u003c/p\u003e \u003cp\u003eIn the present study, our use of landmark analysis overcame the limitations of cumulative incidence by capturing dynamic changes in DM risk over defined intervals. This approach provides a clearer depiction of how DM risk evolves over time, particularly in the context of age-specific patterns. By incorporating physical and behavioral factors such as BMI, smoking, and alcohol use, our findings offer a more comprehensive understanding of DM risk in breast cancer survivors. These factors strengthen the validity and specificity of our results compared to prior studies.\u003c/p\u003e \u003cp\u003eOne plausible explanation for the short-term spike in DM risk that we observed is that previously undiagnosed DM may be detected shortly after breast cancer diagnosis due to increased medical surveillance. Many patients are unaware of their glycemic status until they are undergoing cancer-related medical evaluations. Additionally, treatments such as chemotherapy, hormonal therapy, and steroid use during the first year may accelerate the progression from prediabetes to DM.\u003c/p\u003e \u003cp\u003eChemotherapy-induced nausea and vomiting (CINV), one of the most distressing side effects of chemotherapy, is commonly managed with corticosteroids, which are highly effective but also to induces hyperglycemia as a side effect.[33, 34] Corticosteroids can promote insulin resistance by inhibiting insulin synthesis, reducing insulin sensitivity, and leading to hyperglycemia.[9, 18, 35] Studies have shown that taxane-based regimens, when combined with glucocorticoids, can exacerbate hyperglycemia.[36] Furthermore, in a study of hematologic malignancies, exposure to glucocorticoids during chemotherapy was associated with increased risk of new-onset hyperglycemia (HR 1.28) and DM (HR 1.29).[37] Such glucose dysregulation may persist beyond the treatment period, reflecting the lasting impact of corticosteroids on metabolism.[38]\u003c/p\u003e \u003cp\u003eOne possible explanation for the differences in the temporal patterns observed in East Asian [2, 5] and Western studies [6, 14] is differences in insulin secretion and metabolic responses, which influence DM risk patterns. East Asian samples typically include patients with lower BMI, and therefore exhibit reduced insulin secretory capacity compared to Western samples, in which obesity-related insulin resistance is the primary driver of gradual increase in DM risk.[39] This difference in β-cell function and metabolic response, combined with a higher proportion of visceral adiposity despite lower BMI, may predispose East Asian patients to more rapid changes in DM risk.[40] These findings suggest that the short-term elevation in DM risk observed in our study reflects pathophysiology and treatment effects specific to the Asian population.\u003c/p\u003e \u003cp\u003eTamoxifen also appears to significantly contribute to the observed risk of DM, particularly in younger breast cancer patients. Tamoxifen use is associated with weight gain, an effect often exacerbated by concurrent chemotherapy and that is more pronounced during the early phases of treatment.[41] Patients on tamoxifen report greater dissatisfaction with weight changes compared to those on AIs.[42] Preclinical studies suggest that tamoxifen may induce adipocyte hypertrophy and increase adipose tissue, particularly in individuals with obesity, leading to insulin resistance and impaired glucose metabolism.[43] These metabolic changes may be further aggravated by high-fat diets, contributing to ectopic lipid deposition and glucose intolerance.[43] Additionally, tamoxifen\u0026rsquo;s dual role as an estrogen antagonist in breast tissue and an agonist in other tissues such as the liver may disrupt insulin regulation and lipid metabolism, promoting early hepatic insulin resistance.[18, 44]\u003c/p\u003e \u003cp\u003eAlthough some studies suggest that aromatase inhibitors (AIs) increase DM risk, [16, 17] the results remain inconsistent, particularly because elevated risk is observed in younger populations but no significant effects are observed in older patients. These differences may be due to variation in study designs, follow-up durations, or the metabolic profiles of specific AI agents.\u003c/p\u003e \u003cp\u003eIn the present study, we confirmed established risk factors for DM, including obesity, hypertension, and dyslipidemia. High BMI and weight gain are significant factors associated with increased DM risk among cancer survivors.[8] Hypertension and dyslipidemia frequently coexist with DM, forming key components of metabolic syndrome, which shares genetic and environmental risk factors with DM.[45] Smoking has also been associated with increased risk of progression from normal glucose tolerance to impaired glucose tolerance and type 2 DM.[46] Therefore, recognizing and managing these risk factors is essential to reduce DM risk in cancer survivors.\u003c/p\u003e \u003cp\u003eHowever, this study has several limitations. First, information regarding stage and subtype of breast cancer was not available, which could influence treatment regimens and subsequently impact the risk of developing DM. Second, the influences of other unmeasured variables\u0026mdash;such as dietary patterns or genetic predispositions\u0026mdash;cannot be excluded. These factors may have affected the observed associations and warrant further investigation in future studies. Third, our findings may not be fully generalizable to other countries with different healthcare systems or ethnic compositions. Future research that includes more diverse population samples would enhance the applicability of the results beyond Korea.\u003c/p\u003e"},{"header":"CONCLUSION","content":"\u003cp\u003eBreast cancer survivors showed markedly increased risk of DM during the first year after diagnosis. The increased risk was more prominent and persisted longer in younger women. Elevated risk was also observed in patients treated with taxane or tamoxifen, as well as those with high BMI, current smokers, and those with hypertension or dyslipidemia. Careful monitoring of DM status is needed, especially in the early survivorship period, and for patients who are young, who receive chemotherapy or tamoxifen, and who have other established risk factors for DM.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThis study was approved by the \u003cb\u003eSamsung Medical Center Institutional Review Board\u003c/b\u003e (Seoul, South Korea; SMC 2020-03-108). All data were anonymized and de-identified, making informed consent unnecessary according to the approved protocol.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eConsent for publication\u003c/strong\u003e \u003cp\u003eNot applicable as this study does not include any identifiable individual data.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCompeting interests\u003c/h2\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e\u003cp\u003e \u003ch2\u003eCONFLICT OF INTEREST STATEMENT\u003c/h2\u003e \u003cp\u003eThe authors declare that they have no conflicts of interest to disclose.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003e\u0026bull; Hyeongjin Shim: Conceptualization, data curation, methodology design, writing\u0026mdash;original draft preparation, and manuscript revision.\u0026bull; Bong-seong Kim: Statistical analysis, data processing, and interpretation of results.\u0026bull; Kyungdo Han: Validation of statistical models and critical review of statistical sections.\u0026bull; Hye Yeon Koo: Literature review, and review of clinical content.\u0026bull; Seonghye Kim, Dagyeong Lee, and In Young Cho: Review and editing of the entire manuscript, oversight of clinical relevance, and coordination of data acquisition.\u0026bull; Wonyoung Jung: Technical editing and supervision of cardiovascular-related implications.\u0026bull; Dong Wook Shin: Overall project supervision, final review, and approval of the manuscript.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThe authors acknowledge the support of Samsung Medical Center and Soongsil University for their collaboration in data management and statistical analysis. Special thanks to the NHIS for providing access to their comprehensive healthcare database.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eThe data supporting the findings of this study are derived from the National Health Insurance Service (NHIS) database of South Korea. Access to this database is restricted to researchers with approved study protocols. Further inquiries regarding data access can be made to the corresponding authors.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eSha, R., et al., \u003cem\u003eGlobal burden of breast cancer and attributable risk factors in 204 countries and territories, from 1990 to 2021: results from the Global Burden of Disease Study 2021.\u003c/em\u003e Biomarker Research, 2024. \u003cstrong\u003e12\u003c/strong\u003e(1): p. 87.\u003c/li\u003e\n\u003cli\u003eWang, C.Y., S.R. Shih, and K.C. 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Chuang, and C. Yoon, \u003cem\u003eComparison of measured and estimated indices of insulin sensitivity and beta cell function: impact of ethnicity on insulin sensitivity and beta cell function in glucose-tolerant and normotensive subjects.\u003c/em\u003e J Clin Endocrinol Metab, 2001. \u003cstrong\u003e86\u003c/strong\u003e(4): p. 1620-5.\u003c/li\u003e\n\u003cli\u003e\u003cem\u003eAppropriate body-mass index for Asian populations and its implications for policy and intervention strategies.\u003c/em\u003e Lancet, 2004. \u003cstrong\u003e363\u003c/strong\u003e(9403): p. 157-63.\u003c/li\u003e\n\u003cli\u003eLima, M.T.M., et al., \u003cem\u003eTemporal influence of endocrine therapy with tamoxifen and chemotherapy on nutritional risk and obesity in breast cancer patients.\u003c/em\u003e BMC Cancer, 2017. \u003cstrong\u003e17\u003c/strong\u003e(1): p. 578.\u003c/li\u003e\n\u003cli\u003eMcGowan, P., et al., \u003cem\u003eWeight gain in breast cancer patients: Tamoxifen versus anastrazole.\u003c/em\u003e Journal of Clinical Oncology, 2006. \u003cstrong\u003e24\u003c/strong\u003e(18_suppl): p. 10544-10544.\u003c/li\u003e\n\u003cli\u003eScalzo, R.L., et al., \u003cem\u003eBreast Cancer Endocrine Therapy Promotes Weight Gain With Distinct Adipose Tissue Effects in Lean and Obese Female Mice.\u003c/em\u003e Endocrinology, 2021. \u003cstrong\u003e162\u003c/strong\u003e(11).\u003c/li\u003e\n\u003cli\u003eKl\u0026ouml;ting, N., et al., \u003cem\u003eTamoxifen treatment causes early hepatic insulin resistance.\u003c/em\u003e Acta Diabetol, 2020. \u003cstrong\u003e57\u003c/strong\u003e(4): p. 495-498.\u003c/li\u003e\n\u003cli\u003eCheung, B.M., \u003cem\u003eThe hypertension-diabetes continuum.\u003c/em\u003e J Cardiovasc Pharmacol, 2010. \u003cstrong\u003e55\u003c/strong\u003e(4): p. 333-9.\u003c/li\u003e\n\u003cli\u003eŚliwińska-Mossoń, M. and H. Milnerowicz, \u003cem\u003eThe impact of smoking on the development of diabetes and its complications.\u003c/em\u003e Diab Vasc Dis Res, 2017. \u003cstrong\u003e14\u003c/strong\u003e(4): p. 265-276.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Diabetes mellitus, breast cancer survivor, chemotherapy, endocrine therapy","lastPublishedDoi":"10.21203/rs.3.rs-6010947/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6010947/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eWhile breast cancer increases the risk of diabetes mellitus (DM), its temporal relationships according to age group and treatment risk factors for DM have not been comprehensively investigated. In this study we explore temporal patterns of DM risk in breast cancer survivors, stratified by age and risk factors.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eUsing the National Health Insurance Service database in South Korea, this retrospective cohort study analyzed 65,982 breast cancer survivors and 168,214 age-matched controls, excluding those with prior DM or other cancers. Multivariable Fine-Gray models adjusted for sociodemographics, comorbidities, lifestyle behaviors, and cancer treatments assessed DM risk, with landmark analyses at 1, 3, and 5 years post-diagnosis and stratification by age (\u0026le;\u0026thinsp;50 and \u0026gt;\u0026thinsp;50 years).\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIn women\u0026thinsp;\u0026le;\u0026thinsp;50, DM risk was highest in the first year post-diagnosis (sHR 3.74, 95% CI 3.08\u0026ndash;4.55), decreased at 1 year (sHR 1.11, 95% CI 1.03\u0026ndash;1.19), and showed no significant increase in 3-year and subsequent analyses. In women\u0026thinsp;\u0026gt;\u0026thinsp;50, DM risk was also elevated in the first year (sHR 1.71, 95% CI 1.92\u0026ndash;2.35) but not later. Significant risk factors included BMI\u0026thinsp;\u0026ge;\u0026thinsp;25 (sHR 1.45), smoking (sHR 1.72), hypertension (sHR 1.48), dyslipidemia (sHR 1.49), and taxane use (sHR 1.15). Tamoxifen was a risk factor in younger women (sHR 1.22, 95% CI 1.06\u0026ndash;1.40).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eBreast cancer survivors face the highest DM risk within the first year post-diagnosis, particularly younger women. Risk factors include obesity, smoking, hypertension, dyslipidemia, and treatments such as taxane and tamoxifen.\u003c/p\u003e","manuscriptTitle":"Risk of Newly Incident Diabetes Mellitus and Treatment Risk Factors in Breast Cancer Survivors: Landmark Analyses of Nationwide Data","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-02-17 18:32:22","doi":"10.21203/rs.3.rs-6010947/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"8097bb19-b1c6-4670-93b4-703a24a1e425","owner":[],"postedDate":"February 17th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-02-21T03:53:38+00:00","versionOfRecord":[],"versionCreatedAt":"2025-02-17 18:32:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6010947","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6010947","identity":"rs-6010947","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}