Diabetes and breast cancer in Taiwanese women: a detection bias?

The association between acute myocardial infarction and subsequent diagnosis of breast cancer: a nationwide, population-based cohort study

Coronary artery disease (CAD) such as acute myocardial infarction (MI) share several common risk factors with cancers, and each disease may influence the prognosis of the other. Recently, acute MI was demonstrated to accelerate the outgrowth of preexisting breast cancer cells but the risk of breast cancer after MI remains unclear. This study aimed to investigate the association between acute MI and a subsequent diagnosis of breast cancer. Female patients with and without a history of acute MI were identified from nationwide databases in Taiwan. Patients with a diagnosis of cancer, MI or CAD prior to the study period were excluded. After reducing confounding through inverse probability of treatment weighting, we compared the incidence of newly diagnosed breast cancer between patients with a history of acute MI and those without. As a result, a total of 66,445 female patients were obtained, including 15,263 patients with a history of acute MI and 51,182 patients without. The incidences of breast cancer during follow-up were 1.93 (95% confidence interval [CI] 1.78-2.09) and 1.80 (95% CI 1.67-1.93) per 1,000 person-years for patients with and without a history of acute MI, respectively. The hazard ratio (HR) was 1.05 (95% CI 0.78-1.41, P = 0.756). In subgroup analysis, breast cancer risk was significantly associated with acute MI in patients using antidiabetic drugs (HR 1.27; 95% CI 1.02-1.58) and in low to moderate urbanization levels (HR 1.28; 95% CI 1.06-1.53). In conclusion, the risk of newly diagnosed breast cancer was not increased in patients with acute MI when compared to general population without MI or CAD.

Predictive value of the Adult Comorbidity Evaluation 27 on adverse surgical outcomes and survival in elderly with advanced epithelial ovarian cancer undergoing cytoreductive surgery

OBJECTIVE

We aimed to evaluate the ability of Adult Comorbidity Evaluation 27 (ACE-27) to predict perioperative outcomes and survival in elderly women with advanced epithelial ovarian cancer (AEOC) undergoing cytoreductive surgery.

METHODS

We collected patients with AEOC in our hospital between January 1, 2012 and January 1, 2021. Patients younger than 65 years old or those with non-epithelial ovarian cancer were excluded. ACE-27 was applied retrospectively to assess comorbidities in the selected patients, who were then classified into two groups based on their ACE-27 scores: low ACE-27 score group (none to mild) and high ACE-27 score group (moderate to severe).

RESULTS

A total of 222 elderly women with AEOC were included, of whom 164 patients accepted debulking surgery. Among those who have undergone surgery, Clavien-Dindo grade III + perioperative complications or unintended intensive care unit (ICU) admission occurred more often in patients of high ACE-27 score group, with statistically significant difference (odds ratio [OR]: 4.21, 95% confidence interval [CI], 1.28-14.35, p = 0.018). Further stratified analyses by age, BMI, FIGO stage and pathology also prove that OS of patients graded severe was shorter than patients graded none to moderate in cohort of age < 70, BMI < 25 kg/m2, FIGO III stage and pathology of serous, respectively. Kaplan-Meier survival curves analyzed by log-rank test showed that the overall survival (OS) of patients with severe comorbidities were shorter than with none to moderate (HR 3.25, 95%CI 1.55-6.79, p = 0.002).

CONCLUSIONS

Our findings demonstrate the ability of ACE-27 to predict grade III + perioperative complications or unintended ICU admission and survival in elderly patients with AEOC. This highlights the possibility for ACE-27 to play an instrumental role in identifying AEOC patients who are more susceptible to adverse surgical outcomes and have a poor survival rate and assisting in decisions regarding treatment.

Diabetes and incidence of breast cancer and its molecular subtypes: A systematic review and meta-analysis

Diabetes mellitus (DM) has been proposed to be positively associated with breast cancer (BCa) risk due to shared risk factors, metabolic dysfunction, and the use of antidiabetic medications. We conducted a systematic review and meta-analysis to evaluate the association between DM and BCa risk. We searched PubMed, Embase, and Web of Science for cohort and case-control studies assessing the association between DM and BCa published before 10 December 2021. Two reviewers independently screened the studies for inclusion, abstracted article data, and rated study quality. Random effects models were used to estimate summary risk ratios (RRs) and 95% confidence intervals (CIs). From 8396 articles identified in the initial search, 70 independent studies were included in the meta-analysis. DM was associated with an overall increased risk of BCa (RR = 1.20, 95% CI: 1.11-1.29). The 24 case-control studies demonstrated a stronger association (RR = 1.26, 95% CI: 1.13-1.40) than the 46 cohort studies (RR = 1.15, 95% CI: 1.05-1.27). Studies reporting risk by menopausal status found that postmenopausal women had an elevated risk of developing BCa (RR = 1.12, 95% CI: 1.07-1.17). No association between DM and BCa risk was observed among premenopausal women (RR = 0.95, 95% CI: 0.85-1.05). In addition, DM was associated with significantly increased risks of oestrogen receptor (ER)+ (RR = 1.09, 95% CI: 1.00-1.20), ER- (RR = 1.16, 95% CI: 1.04-1.30), and triple negative BCa (RR = 1.41, 95% CI: 1.01-1.96). The association estimate for human epidermal growth factor 2-positive BCa was also positive (RR = 1.21, 95% CI: 0.52-2.82), but the CI was wide and crossed the null. Our meta-analysis confirms a modest positive association between DM and BCa risk. In addition, our results suggest that the association between DM and BCa may be modified by menopausal status, and that DM may be differentially associated with BCa subtypes defined by receptor status. Additional studies are warranted to investigate the mechanisms underlying these associations and any influence of DM on BCa receptor expression.

Investigation of commonly used aortic aneurysm growth rate metrics: Comparing their suitability for clinical and research applications

An aneurysm is a pathological widening of a blood vessel. Aneurysms of the aorta are often asymptomatic until they rupture, killing approximately 10,000 Americans per year. Fortunately, rupture can be prevented through early detection and surgical repair. However, surgical risk outweighs rupture risk for small aortic aneurysms, necessitating a policy of surveillance. Understanding the growth rate of aneurysms is essential for determining appropriate surveillance windows. Further, identifying risk factors for fast growth can help identify potential interventions. However, studies in the literature have applied many different methods for defining the growth rate of abdominal aortic aneurysms. It is unclear which of these methods is most accurate and clinically meaningful, and whether these heterogeneous methodologies may have contributed to the varied results reported in the literature. To help future researchers best plan their studies and to help clinicians interpret existing studies, we compared five different models of aneurysmal growth rate. We examined their noise tolerance, temporal bias, predictive accuracy, and statistical power to detect risk factors. We found that hierarchical mixed effects models were more noise tolerant than traditional, unpooled models. We also found that linear models were sensitive to temporal bias, assigning lower growth rates to aneurysms that were detected earlier in their course. Our exponential mixed model was noise-tolerant, resistant to temporal bias, and detected the greatest number of clinical risk factors. We conclude that exponential mixed models may be optimal for large studies. Because our results suggest that choice of method can materially impact a study's findings, we recommend that future studies clearly state the method used and demonstrate its appropriateness.

Association between diabetes status and breast cancer in US adults: findings from the US National Health and Nutrition Examination Survey

Objectives

The aim of this study was to investigate the association between diabetes status and the risk of breast cancer among adult Americans, exploring the impact of BMI, age, and race on this relationship.

Methods

A cross-sectional analysis of 8,249 individuals from the National Health and Nutrition Examination Survey (NHANES) was conducted. Diabetes was categorized as type 2 diabetes and prediabetes, with both conditions diagnosed according to the ADA 2014 guidelines. The association between diabetes status and breast cancer risk was explored using multiple logistic regression analysis.

Results

Patients with diabetes had higher odds of breast cancer (OR: 1.51; 95% CI 1.00 to 2.28), Using the two-piecewise linear regression model, it was observed that there is a threshold effect in the risk of breast cancer occurrence at the age of 52 years. Specifically, the risk of breast cancer is relatively low before the age of 52 but increases significantly after this age.

Conclusions

This study identified a significant association between diabetes status and breast cancer risk among adult Americans. We also found a threshold effect in breast cancer occurrence at the age of 52. Age was significantly associated with breast cancer risk in both Non-Hispanic White and Non-Hispanic Black individuals. These findings underscore the importance of diabetes management, maintaining a healthy BMI, and age-related risk considerations in reducing breast cancer risk.

Aspirin and Risk of Specific Breast Cancer Subtype in Women with Diabetes

Purpose: Low-dose aspirin was associated with a reduced risk of breast cancer in women with diabetes. However, whether the protective effect of aspirin varies as a function of the hormone receptor status of breast cancer remained an unanswered question. This study aims to explore the association between aspirin use and the risk of specific breast cancer subtypes in women with diabetes. Methods: Population-based retrospective cohort study of women with diabetes, using the Taiwan National Health Insurance reimbursement database (year 1998 to 2011). Patients diagnosed to have diabetes with new low-dose aspirin use (75-165 mg per day) for at least 28 days of prescription were identified as the study population, while patients without low-dose aspirin use were selected as controls. The main outcome measure was breast cancer by aspirin use and hormone receptor status. Results: We studied a total of 148,739 patients with diabetes. Their mean (standard deviation) age was 63.3 (12.8) years. During follow-up, a total of 849 breast cancers occurred, including 329 hormone receptor-positive and 529 hormone receptor-negative tumors. A total of 27,378 patients were taking aspirin. The reduction in risk with aspirin use was seen among those with hormone receptor-positive breast cancer (Hazard ratio [HR]: 0.73; 95% confidence interval [CI]: 0.59-0.91) but not for women with hormone receptor-negative breast cancer (HR: 0.88; 95% CI: 0.74-1.05). A cumulative dose of aspirin use of more than 8,600 mg was found to reduce the risk of hormone receptor-positive breast cancer by 31% (HR: 0.69; 95% CI: 0.50-0.97). A cumulative dose of aspirin use of more than 88,900 mg was found to reduce both the risk of hormone receptor-positive and negative breast cancer. Conclusion: These data add to the growing evidence that supports the use of low-dose aspirin as a potential chemopreventive agent for specific subtypes of breast cancer. Further studies are necessary to confirm these findings.

Pioglitazone and breast cancer risk in female patients with type 2 diabetes mellitus: a retrospective cohort analysis

Background

Whether pioglitazone may affect breast cancer risk in female diabetes patients is not conclusive and has not been investigated in the Asian populations.

Methods

The reimbursement database of Taiwan’s National Health Insurance was used to enroll an unmatched cohort and a propensity score-matched cohort of ever users and never users of pioglitazone in female patients with newly diagnosed type 2 diabetes during 1999–2008. The patients were alive on January 1, 2009 and were followed up for breast cancer incidence until December 31, 2011. Cox regression was used to estimate hazard ratios for ever users and tertiles of cumulative duration of pioglitazone therapy versus never users, and for cumulative duration of pioglitazone therapy treated as a continuous variable. Three models were created for the unmatched cohort and the matched cohort, respectively: 1) without adjustment for covariates; 2) after adjustment for covariates that differed with statistical significance (P-value < 0.05) between ever users and never users; and 3) after adjustment for all covariates.

Results

There were 174,233 never users and 6926 ever users in the unmatched cohort; and 6926 never users and 6926 ever users in the matched cohort. After a median follow-up of 2.8 years, the numbers of incident breast cancer were 1044 in never users and 35 in ever users in the unmatched cohort and were 41 and 35, respectively, in the matched cohort. Hazard ratios suggested a null association between pioglitazone and breast cancer in all three models in either the unmatched cohort or the matched cohort. The overall hazard ratio after adjustment for all covariates was 0.758 (95% confidence interval: 0.539–1.065) in the unmatched cohort and was 0.824 (95% confidence interval: 0.524–1.296) in the matched cohort. None of the hazard ratios for the tertiles of cumulative duration of pioglitazone therapy and for the cumulative duration being treated as a continuous variable were statistically significant.

Conclusions

This study suggests a null association between pioglitazone and breast cancer risk in female patients with type 2 diabetes mellitus. However, because of the small breast cancer cases and the limited follow-up time, further studies are warranted to confirm our findings.

The Performance of Different Artificial Intelligence Models in Predicting Breast Cancer among Individuals Having Type 2 Diabetes Mellitus

Objective: Early reports indicate that individuals with type 2 diabetes mellitus (T2DM) may have a greater incidence of breast malignancy than patients without T2DM. The aim of this study was to investigate the effectiveness of three different models for predicting risk of breast cancer in patients with T2DM of different characteristics. Study design and methodology: From 2000 to 2012, data on 636,111 newly diagnosed female T2DM patients were available in the Taiwan’s National Health Insurance Research Database. By applying their data, a risk prediction model of breast cancer in patients with T2DM was created. We also collected data on potential predictors of breast cancer so that adjustments for their effect could be made in the analysis. Synthetic Minority Oversampling Technology (SMOTE) was utilized to increase data for small population samples. Each datum was randomly assigned based on a ratio of about 39:1 into the training and test sets. Logistic Regression (LR), Artificial Neural Network (ANN) and Random Forest (RF) models were determined using recall, accuracy, F₁ score and area under the receiver operating characteristic curve (AUC). Results: The AUC of the LR (0.834), ANN (0.865), and RF (0.959) models were found. The largest AUC among the three models was seen in the RF model. Conclusions: Although the LR, ANN, and RF models all showed high accuracy predicting the risk of breast cancer in Taiwanese with T2DM, the RF model performed best.

Perspectives on diabetes mortality as the result of residual confounding and reverse causality by common disease

Type 2 diabetes (T2D) is associated with major global health burdens, including 2 to 4 times increased rates of morbidity and mortality from cardiovascular disease. However, T2D remains an exclusion diagnosis in individuals with arbitrarily elevated blood-glucose levels. While it is well-established that diabetes is associated with an elevated risk of cardiovascular disease and cancer, it has recently been shown that heart failure and cancer may precede, and even contribute to, the development of T2D. In the present review, we have summarized these findings and discuss their potential implications for our understanding of the T2D disease entity, including its treatment and associated increased mortality. We suggest that the existence of a hitherto unrecognized distinct T2D subtype, secondary to heart failure and/or cancer, may substantially contribute to the excess mortality reported in T2D patients with mild disease. Treatment and clinical care of this subtype needs to be defined separately from the general T2D phenotype.

Retrospective database analysis of cancer risk in patients with type 2 diabetes mellitus in China

OBJECTIVE

To investigate the association between type 2 diabetes (T2D) and the risk of overall cancer and site-specific cancers in a Chinese population.

RESEARCH DESIGN AND METHODS

Tianjin Urban Employee Basic Medical Insurance database (2003-2014) was used to identify patients with newly onset T2D in 2009, patients with prevalent T2D prior to 2009, and general individuals without T2D. Overall and site-specific cancer incidence rates and incidence rate ratios relative to general population were calculated for both incident and prevalent T2D cohorts. Multivariate Cox proportional hazards models adjusting for baseline characteristics and potential bias were conducted. Subgroup analyses based on gender and age were further conducted.

RESULTS

For the year 2009, 21,208 patients with onset T2D (mean age 58.8 years; 48.1% female), 28,248 patients with prevalent T2D (mean age 63.7 years; 50.2% female) and 744,339 general individuals (mean age 43.2 years; 47.7% female) were identified. Controlling for confounders, diabetic patients had an overall 56%-59% higher risk of developing cancer, among which the highest risks by site were liver (adjusted hazard ratio [aHR] = 1.80-2.48), colorectal (aHR = 2.41-2.69) and stomach (aHR = 2.02-2.51) cancers (all p < .05). Patients with prevalent T2D had increased cancer risk in the pancreas (aHR = 4.52, p < .001). Female diabetic patients had increased risk in the kidneys (aHR = 3.22-3.31, p < .01). Patients aged between 50 and 59 years had the highest relative risk (90% higher), while the relative risk was the lowest among patients ≥70 (45% higher).

CONCLUSION

Type 2 diabetes was associated with increased overall cancer risk led by liver, colorectal and stomach cancers. Patients with longer diabetes duration were associated with higher pancreatic cancer risk and female diabetic patients had a higher risk of kidney cancer.

Demographic Characteristics, Survival and Prognostic Factors of Early Breast Cancer Patients with Type 2 Diabetes Mellitus: A Hospital-Based Cohort Study

Objective: With increasing prevalence of type 2 diabetes mellitus and breast cancer in Iran, we aimed to search hospital registries of breast cancer patients to investigate type 2 diabetes mellitus association with survival outcomes of early breast cancer after adjustment of confounding factors. Methods: In a retrospective cohort study conducted from July 2003 to Feb 2014 and followed up until death or December 2016, female patients with early breast cancer who have been treated for the first time at the Cancer Institute of Iran, were divided to diabetic and non-diabetic groups. Primary and secondary outcomes were relapse free survival (RFS) and overall survival (OS). SPSS version 23 was used for analysis of data. Other variables included age, tumor stage, hormone receptor status, tumor subtype, and patient’s body mass index (BMI). Result: From a total of 1021 patients, 218 (21.4%) had type 2 diabetes mellitus. Diabetic patients had a higher mean age (53.31 vs 47.00), higher mean BMI (31.13 vs 29.15), lower HER2 expression (20.8% vs 32.1%) and higher frequency of luminal A subtype (61.1% vs 51.0). Overall, after adjustment of other variables, diabetes status did not affect RFS or OS independently. However, in luminal A subgroup, patients with diabetes mellitus had significantly lower survival outcomes of OS (135.277 vs 154.701) and RFS (114.107 vs 133.612) as well as OS higher hazard ratio of 1.830 and RFS hazard ratio of 1.663 compared to non-diabetic patients. BMI, hormone receptor status and tumor stage significantly affected the survival of the patients. Conclusion: In the present study, in addition to known breast cancer risk factors, BMI and type 2 diabetes mellitus had an independent impact on survival of the patients, highlighting the importance of health issues such as obesity and diabetes suboptimal performance in the treatment outcomes of early breast cancer patients in Iran.

Type 2 diabetes, insulin treatment and prognosis of breast cancer

BACKGROUND

The aim of our study was to investigate whether pre-existing type 2 diabetes and insulin therapy have an impact on the prognosis of breast cancer patients.

METHODS

We performed a retrospective analysis of 462 type 2 diabetic breast cancer patients and 1644 non-diabetic breast cancer patients treated in our institute from January 2005 to August 2010. Patients were divided by diabetes status and insulin use. The clinicopathological characteristics and clinical outcomes of patients within 5 years following breast cancer diagnosed were analysed.

RESULTS

Diabetic patients tended to have higher body mass index and higher histological grade tumours. Five-year disease-free survival and overall survival were reduced in diabetic patients (P < 0.001), and diabetes was an independent predictor for an increased risk of breast cancer relapse and death within 5 years (P < 0.001). Insulin treatment was associated with reduced 5-year disease-free survival and overall survival (P < 0.05); the risk of 5-year relapse and breast cancer mortality in the insulin group increased compared to that of non-insulin group after adjusting for age, tumour size, histological grade, oestrogen receptor, progesterone receptor, chemotherapy and hormone therapy (P < 0.05). After adjusting for age and other factors, the risk of breast cancer relapse was also increased in the insulin subgroup, while the risk of breast cancer mortality did not increase statistically.

CONCLUSIONS

Type 2 diabetes and insulin treatment might be independently associated with poorer prognosis of breast cancer. However, caution is needed when interpreting our results, and further investigations are needed. Copyright © 2016 John Wiley & Sons, Ltd.

[Breast cancer and diabetes mellitus: Complex interactions]

The aim of this literature review was to quantify the incidence and mortality of breast cancer for women treated for a diabetes mellitus and to analyze the complex relationship between these two common diseases.

METHODS

The articles analyzed were extracted from the PubMed database from 2000 to 2015. A total of 22 case/control studies or cohorts were retained, allowing the realization of a meta-analysis.

RESULTS

The incidence of breast cancer for women with diabetes is significantly increased for cohorts (RR=1.32; 95% CI: 1.06 to 1.65) and not significantly for case/control studies (RR=1.46; 95% CI: 0.99 to 2.26). Overall, mortality of women with breast cancer is significantly increased for diabetic patients compared with non-diabetic patients (RR=1.53; 95% CI: 1.23 to 1.90). The links between diabetes and breast cancer are explained by common risk factors (overweight/obesity, qualitative and quantitative dietary errors, physical inactivity), biological changes and the impact of some anti-diabetic treatments or hormonotherapy.

CONCLUSION

Physicians facing a diabetic patient treated for breast cancer have a role in choosing the best anti-diabetic treatment and implementing lifestyle modifications. Diabetic women without breast cancer should participate in organized breast screening programs and have an annual breast clinical examination.

The Association between Treatment for Metabolic Disorders and Breast Cancer Characteristics

Purpose. To evaluate the associations between metformin, insulin, statins, and levothyroxine and breast cancer characteristics and outcome. Methods. Retrospective chart review of patients treated in our institute for early estrogen receptor (ER) positive, human epidermal growth factor receptor 2 negative breast cancer, whose tumors were sent to Oncotype DX (ODX) analysis. Patients were grouped according to medications usage during the time of breast cancer diagnosis. Each group was compared to the rest of the study population. Results. The study cohort included 671 patients. Sixty (9.1%) patients were treated with metformin, 9 (1.4%) with insulin, 208 (31.7%) with statins, and 62 (9.4%) with levothyroxine. Patients treated with metformin had more intense ER stain (p = 0.032) and a lower ODX recurrence score (RS) (p = 0.035). Diagnosis of diabetes mellitus was also associated with lower ODX RS (p = 0.014). Insulin usage was associated with a higher rate of angiolymphatic invasion (p = 0.041), but lower Ki67% (p = 0.017). Levothyroxine usage was associated with different histological subtype distribution (p = 0.02). Extended levothyroxine usage was associated with lower ODX RS (p = 0.005). Statin usage had no impact on tumor characteristics. Outcome was comparable in the studied subgroups. Conclusions. Common medications for metabolic disorders might be associated with breast cancer characteristics.

An updated review on cancer risk associated with incretin mimetics and enhancers

Incretin-based therapies, including the use of incretin mimetics of glucagon-like peptide-1 receptor (GLP-1R) agonists and incretin enhancers of dipeptidyl-peptidase 4 (DPP-4) inhibitors, are widely used by clinicians for glucose lowering in patients with type 2 diabetes mellitus. These agents have benefits of a lower risk of hypoglycemia, being neutral for body weight for DPP-4 inhibitors and having a potential for weight reduction with GLP-1R agonists. They may also have a neutral or beneficial cardiovascular effect. Despite these benefits, an increased risk of cancer (especially pancreatic cancer and thyroid cancer) associated with incretin-based therapies has been reported. In this article, we reviewed related literature of experimental animal and observational human studies, clinical trials, and meta-analyses published until December 15, 2014. Current studies suggested a probable role of GLP-1R activation on the development of pancreatic cancer and thyroid cancer in rodents, but such an effect in humans is not remarkable due to the lower or lack of expression of GLP-1R on human pancreatic ductal cells and thyroid tissues. Findings in human studies are controversial and inconclusive. In the analyses of the US Food and Drug Administration adverse events reporting system, a significantly higher risk of pancreatic cancer was observed for GLP-1R agonists and DPP-4 inhibitors, but a significantly higher risk of thyroid cancer was only observed for GLP-1R agonists. Such a higher risk of pancreatic cancer or thyroid cancer could not be similarly demonstrated in other human observational studies or analyses of data from clinical trials. With regards to cancers other than pancreatic cancer and thyroid cancer, available studies supported a neutral association in humans. Some preliminary studies even suggested a potentially beneficial effect on the development of other cancers with the use of incretins. Based on current evidence, continuous monitoring of the cancer issues related to incretin-based therapies is required, even though the benefits may outweigh the potential cancer risk in the general patients with type 2 diabetes mellitus.

Use of Insulin and Mortality from Breast Cancer among Taiwanese Women with Diabetes

Background. To evaluate whether insulin use was predictive for mortality from breast cancer in Taiwanese women with diabetes mellitus. Methods. A total of 48,880 diabetic women were followed up to determine the mortality from breast cancer during 1995-2006. Cox models were used, considering the following independent variables: age, sex, diabetes type, diabetes duration, body mass index, smoking, insulin use, and area of residence. Insulin use was also considered for its duration of use at cutoffs of 3 years and 5 years. Results. Age was a significant predictor in all analyses. The multivariable-adjusted hazard ratio (95% confidence interval, P value) for insulin use without considering the duration of use was not statistically significant (1.339 [0.782-2.293, P = 0.2878]). Compared with nonusers, insulin users showed the following adjusted hazard ratios for insulin use <3 years, ≥3 years, <5 years, and ≥5 years: 0.567 (0.179-1.791, P = 0.3333), 2.006 (1.102-3.653, P = 0.0228), 1.045 (0.505-2.162, P = 0.9048), and 1.899 (0.934-3.860, P = 0.0763). Conclusions. Insulin use (mainly human insulin) for ≥3 years may be associated with a higher risk of breast cancer mortality.