Objective: The association between insulin therapy and the risk of biliary tract cancer (BTC) is uncertain, we aimed to assess this risk in type 2 diabetic patients. Methods: Using electronic medical data from the Shanghai Hospital Link database, 202,557 patients with type 2 diabetes (164,997 insulin never-users and 37,560 insulin ever-users) were identified in this study between January 1, 2013, and December 31, 2016, with follow-up until December 31, 2019. By propensity score matching, an ever-user was matched with a never-user. Cox proportional hazards regression analysis was used to estimate risk ratios (HRs) and 95% confidence intervals (CIs) for three subtypes of BTC (intrahepatic cholangiocarcinoma (ICC), extrahepatic cholangiocarcinoma (ECC), and gallbladder cancer (GBC)). Results: At a mean follow-up of 5.33 years, 143 cases of BTC were observed. The crude incidence rates (per 100,000 person-years) of ECC, ICC, and GBC in ever-users: never-users were 10.22: 3.63, 2.04: 2.04, and 8.17: 6.01, respectively. Insulin therapy was associated with an increased risk of ECC (HR, 4.10; 95% CI, 1.54-10.92; p = 0.005) compared to patients who never used insulin. No statistically significant results were observed for insulin and ICC/GBC. Consistent results were also found in the original cohort. Conclusions: The relationship between insulin therapy and biliary tract cancer is type-specific, further studies are warranted to provide evidence on the identification of ECC risk groups among type 2 diabetic patients.

Background All‐cause mortality risk prediction models for patients with type 2 diabetes mellitus (T2DM) in mainland China have not been established. This study aimed to fill this gap. Methods Based on the Shanghai Link Healthcare Database, patients diagnosed with T2DM and aged 40‐99 years were identified between January 1, 2013 and December 31, 2016 and followed until December 31, 2021. All the patients were randomly allocated into training and validation sets at a 2:1 ratio. Cox proportional hazards models were used to develop the all‐cause mortality risk prediction model. The model performance was evaluated by discrimination (Harrell C‐index) and calibration (calibration plots). Results A total of 399 784 patients with T2DM were eventually enrolled, with 68 318 deaths over a median follow‐up of 6.93 years. The final prediction model included age, sex, heart failure, cerebrovascular disease, moderate or severe kidney disease, moderate or severe liver disease, cancer, insulin use, glycosylated hemoglobin, and high‐density lipoprotein cholesterol. The model showed good discrimination and calibration in the validation sets: the mean C‐index value was 0.8113 (range 0.8110–0.8115) and the predicted risks closely matched the observed risks in the calibration plots. Conclusions This study constructed the first 5‐year all‐cause mortality risk prediction model for patients with T2DM in south China, with good predictive performance.

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