Comparisons of clinical outcomes between newly diagnosed early- and late-onset T2DM: a real-world study from the Shanghai Hospital Link Database.

Objective: The aim of this study was to compare the differences in incident population, comorbidities, and glucose-lowering drug prescriptions between newly diagnosed patients with early-onset type 2 diabetes mellitus (T2DM) and those with late-onset T2DM to provide real-world evidence for clinical practice. Methods: This study was based on the Shanghai Hospital Link Database (SHLD). Anonymized electronic medical record (EHR) data from 2013 to 2021 were included in this study. Newly diagnosed patients with T2DM were defined as those without related diagnostic records or glucose-lowering medicine prescriptions in the past 3 years. Early-onset T2DM was defined as patients who were aged 18-40 years old at the first visit for T2DM to represent those who were born after the 1980s. And late-onset T2DM was defined as those aged 65-80 years old to represent those who were born in a relatively undeveloped period. Descriptive statistical analyses were performed to describe their incidence number, glucose-lowering drug prescriptions, and comorbidities at the first visit to the hospital between two T2DM groups. Results: There were a total of 35,457 newly diagnosed patients with early-onset T2DM and 149,108 newly diagnosed patients with late-onset T2DM included in this study. Patients with late-onset T2DM constituted the majority and their number increased by 2.5% on average by years, while the number of patients with early-onset T2DM remained stable each year. Compared with late-onset T2DM patients, more early-onset T2DM patients had dyslipidemia at the first visit to hospitals (9.5% vs 7.7%, P < 0.01) despite their significant age differences. Patients with early-onset T2DM were more likely to use metformin (74.8% vs 46.5, P < 0.01), dipeptidyl peptidase-4 inhibitors (DDP-4i) (16.7% vs 11.2%, P < 0.01), thiazolidinediones (TZD) (14.9% vs 8.4%, P < 0.01), sodium glucose cotransporter 2 inhibitors (SGLT2-i) (0.8% vs 0.3%, P < 0.01), and glucagon-like peptide 1 receptor agonists (GLP-1 RA) (3.7% vs 0.5%, P < 0.01) at their first visit to the hospital. Conclusions: Different characteristics were observed between patients with early-onset T2DM and those with late-onset T2DM. Compared with patients with late-onset T2DM, those with early-onset T2DM were more prone to dyslipidemia and had novel organ-protective drugs prescribed.

A network-based study reveals multimorbidity patterns in people with type 2 diabetes.

Patients with type 2 diabetes mellitus (T2DM) are at a heightened risk of living with multiple comorbidities. However, the comprehension of the multimorbidity characteristics of T2DM is still scarce. This study aims to illuminate T2DM's prevalent comorbidities and their interrelationships using network analysis. Using electronic medical records (EMRs) from 496,408 Chinese patients with T2DM, we constructed male and female global multimorbidity networks and age- and sex-specific networks. Employing diverse network metrics, we assessed the structural properties of these networks. Furthermore, we identified hub, root, and burst diseases within these networks while scrutinizing their temporal trends. Our findings uncover interconnected T2DM comorbidities manifesting as emergence in clusters or age-specific outbreaks and core diseases in each sex that necessitate timely detection and intervention. This data-driven methodology offers a comprehensive comprehension of T2DM's multimorbidity, providing hypotheses for clinical considerations in the prevention and therapeutic strategies.

Trends and Gaps in Statin Use for Cardiovascular Disease Prevention in Type 2 Diabetes: A Real-World Study in Shanghai, China.

BACKGROUND: Cardiovascular disease (CVD) is the major cause of death among persons with diabetes. As the preventative use of statin has been proved to reduce CVD risks, understanding the current status and the trend in statin use is crucial to improve clinical treatment strategies. OBJECTIVE: Our study aimed to answer the question of what were the status and trend of statin use in Shanghai, China. METHODS: Our study estimated statin use and trends from 2015 to 2021 among 702 727 patients with type 2 diabetes mellitus (T2DM) based on electronic health records from the Shanghai Hospital Link Database. Patients were grouped according to the presence of CVDs, tested separately for statin primary and secondary prevention use, and stratified by age and sex. RESULTS: In the study population, 221 127 patients (31.5%) received statin therapy, and among patients with CVD, 157 622 patients (51.62%) received statin therapy for secondary prevention, but only 15% of patients received statins for primary prevention. The trend in the use of statins was still on the rise from 28.3% in 2015. Statin use increased with age (18-39 years, 14.0%; 40-59 years, 26.8%; 60-74 years, 33.35%; and 75 and over, 36.1%), and women (29.7%, n = 93 977) were less likely to receive statin therapy compared to men (32.9%, n = 127 150). CONCLUSION: Despite the rise in statin use in T2DM in recent decades, a large proportion of subjects with T2DM did not receive statin therapy.

Insulin use and gout risk among patients with type 2 diabetes mellitus: a real-world cohort study in Shanghai, China.

OBJECTIVES: The effect of insulin use on gout risk remains unknown. This study aimed to investigate the association between insulin use and gout risk among patients with type 2 diabetes mellitus (T2DM). METHODS: Based on the Shanghai Link Healthcare Database, patients with newly diagnosed T2DM, with or without insulin exposure, were identified from January 1, 2014 to December 31, 2020, and followed until December 31, 2021. Apart from the original cohort, we also established a 1:2 propensity score-matched cohort. A time-dependent Cox proportional hazards model was used to estimate the hazard ratio (HR) and 95% confidence interval (CI) for gout incidence associated with insulin exposure. RESULTS: A total of 414,258 patients with T2DM, including 142,505 insulin users and 271,753 insulin non-users, were enrolled in this study. After a median follow-up of 4.08 years (interquartile range, 2.46-5.90 years), the incidence of gout was significantly higher in insulin users than in insulin non-users (319.35 versus 302.20 cases per 100,000 person-years; HR 1.09, 95% CI 1.03-1.16). The results were robust in propensity score-matched cohort, sensitivity analyses, and stratified analysis of aspirin. In other stratified analyses, the association between insulin use and increased gout risk was found only in patients who were female, or aged 40-69 years, or without hypertension, dyslipidemia, ischemic heart disease, chronic lung disease, kidney disease, or not using diuretic. CONCLUSIONS: Insulin use is associated with a significantly increased risk of gout among patients with T2DM. Key Points • The first real-world study to investigate the effect of insulin use on gout risk. • Insulin use is associated with a significantly increased risk of gout among patients with type 2 diabetes mellitus.

Developing a prediction model for all-cause mortality risk among patients with type 2 diabetes mellitus in Shanghai, China.

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.

Insulin therapy and biliary tract cancer: insights from real-world data.

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% 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 BTC is type-specific. Further studies are warranted to provide evidence on the identification of ECC risk groups among type 2 diabetic patients.