Background Diabetes outcomes are influenced by host factors, settings, and care processes. We examined the association of data-driven integrated care assisted by information and communications technology (ICT) with clinical outcomes in type 2 diabetes in public and private healthcare settings. Methods and findings The web-based Joint Asia Diabetes Evaluation (JADE) platform provides a protocol to guide data collection for issuing a personalized JADE report including risk categories (1-4, lowhigh), 5-year probabilities of cardiovascular-renal events, and trends and targets of 4 risk factors with tailored decision support. The JADE program is a prospective cohort study implemented in a naturalistic environment where patients underwent nurse-led structured

IMPORTANCEMany health care systems lack the efficiency, preparedness, or resources needed to address the increasing number of patients with type 2 diabetes, especially in low-and middle-income countries. OBJECTIVE To examine the effects of a quality improvement intervention comprising information and communications technology and contact with nonphysician personnel on the care and cardiometabolic risk factors of patients with type 2 diabetes in 8 Asia-Pacific countries.

This randomized clinical trial examines the use of a web portal combined with a physician-and-nurse care team approach in improving patient involvement and treatment outcomes for type 2 diabetes and diabetic kidney disease.

Aims/IntroductionBiosimilar insulin can reduce treatment costs, although the extent of its use is largely unknown. We examined biosimilar insulin use and its associations with the quality of glycemic control using the Joint Asia Diabetes Evaluation register.Materials and MethodsWe carried out a cross‐sectional analysis in 81,531 patients with type 1 and type 2 diabetes enrolled into the Joint Asia Diabetes Evaluation Program from 2007 to 2014. All insulin related terms are extracted from the Joint Asia Diabetes Evaluation portal, and compared clinical profiles between biosimilar and originator insulin users. Multivariate analysis was performed to assess the association of biosimilar insulin compared with originator insulin with dosage, glycated hemoglobin and hypoglycemia events.ResultsAmongst 81,531 patients, 20.5% (n = 16,738) were insulin‐treated. In four countries with high use of biosimilar insulin, 4.7% (n = 719) of insulin users (n = 10,197) were treated with biosimilar insulin (India n = 507, 70.3%; the Philippines n = 90, 12.5%; China n = 62, 8.6%; Vietnam n = 60, 8.3%). Biosimilar insulin users were younger and had higher body mass index, glycated hemoglobin, insulin dosage and more frequent hypoglycemia than originator insulin users. These associations were non‐significant after adjustment for confounders. Only age, college education, diabetes education, lipid control, physical activity and history of cardiovascular complications were independently associated with these quality measures.ConclusionsBiosimilar insulin use is not uncommon in Asia. Data exclusion due to incomplete capturing of brand names suggests possibly higher use. The multiple determinants of the quality of glycemic control call for establishment of prospective cohorts and diabetes registers to monitor the safety and efficacy of different brands of biosimilar insulin and their impacts on clinical outcomes.

Type 2 diabetes (T2D)-associated end-stage kidney disease (ESKD) is a global burden, while the renoprotective effects of metformin remain controversial. In a population-based cohort (2002–2018) including 96,643 patients with T2D observed for 0.7 million person-years, we estimated the risk association of metformin and its dose-relationship with ESKD in a propensity-score overlap-weighting (PS-OW) cohort by eGFR categories. Amongst 96,643, 83,881 (86.8%) had eGFR-G1/G2 (≥60 mL/min/1.73 m2), 8762 (9.1%) had eGFR-G3a (≥45–60 mL/min/1.73 m2), 3051 (3.2%) had eGFR-G3b (≥30–45 mL/min/1.73 m2), and 949 (1.0%) had eGFR-G4 (≥15–30 mL/min/1.73 m2). The respective proportions of metformin users in these eGFR categories were 95.1%, 81.9%, 53.8%, and 20.8%. In the PS-OW cohort with 88,771 new-metformin and 7872 other oral glucose-lowering-drugs (OGLDs) users, the respective incidence rates of ESKD were 2.8 versus 22.4/1000 person-years. Metformin use associated with reduced risk of ESKD (hazard ratio (HR) = 0.43 [95% CI: 0.35–0.52] in eGFR-G1/G2, 0.64 [0.52–0.79] in eGFR-G3a, 0.67 [0.56–0.80] in eGFR-G3b, and 0.63 [0.48–0.83] in eGFR-G4). Metformin use was associated with reduced or neutral risk of major adverse cardiovascular events (MACE) (7.2 versus 16.0/1000 person-years) and all-cause mortality (14.6 versus 65.1/1000 person-years). Time-weighted mean daily metformin dose was 1000 mg in eGFR-G1/G2, 850 mg in eGFR-G3a, 650 mg in eGFR-G3b, and 500 mg in eGFR-G4. In a subcohort of 14,766 patients observed for 0.1 million person-years, the respective incidence rates of lactic acidosis and HR in metformin users and non-users were 42.5 versus 226.4 events/100,000 person-years (p = 0.03) for eGFR-G1/G2 (HR = 0.57, 0.25–1.30) and 54.5 versus 300.6 events/100,000 person-years (p = 0.01) for eGFR-G3/G4 (HR = 0.49, 0.19–1.30). These real-world data underscore the major benefits and low risk of lactic acidosis with metformin use down to an eGFR of 30 mL/min/1.73 m2 and possibly even 15 mL/min/1.73 m2, while reinforcing the importance of dose adjustment and frequent monitoring of eGFR.

Background Family history (FamH) of type 2 diabetes might indicate shared genotypes, environments, and/or behaviors. We hypothesize that FamH interacts with unhealthy behaviors to increase the risk of early onset of diabetes and poor cardiometabolic control. Methods In a cross-sectional analysis of the prospective Joint Asia Diabetes Evaluation Register including patients from 427 clinics in 11 Asian countries/regions in 2007–2021, we defined positive FamH as affected parents/siblings and self-management as (1) healthy lifestyles (balanced diet, non-use of alcohol and tobacco, regular physical activity) and (2) regular self-monitoring of blood glucose (SMBG). Results Among 86,931 patients with type 2 diabetes (mean±SD age: 56.6±11.6 years; age at diagnosis of diabetes: 49.8±10.5 years), the prevalence of FamH ranged from 39.1% to 85.3% in different areas with FamH affecting mother being most common (32.5%). The FamH group (n=51,705; 59.5%) was diagnosed 4.6 years earlier than the non-FamH group [mean (95% CI): 47.9 (47.8–48.0) vs. 52.5 (52.4–52.6), logrank p<0.001]. In the FamH group, patients with both parents affected had the earliest age at diagnosis [44.6 (44.5–44.8)], followed by affected single parent [47.7 (47.6–47.8)] and affected siblings only [51.5 (51.3–51.7), logrank p<0.001]. The FamH plus ≥2 healthy lifestyle group had similar age at diagnosis [48.2 (48.1–48.3)] as the non-FamH plus <2 healthy lifestyle group [50.1 (49.8–50.5)]. The FamH group with affected parents had higher odds of hyperglycemia, hypertension, and dyslipidemia than the FamH group with affected siblings, with the lowest odds in the non-FamH group. Self-management (healthy lifestyles plus SMBG) was associated with higher odds of attaining HbA1c<7%, blood pressure<130/80mmHg, and LDL-C<2.6 mmol/L especially in the FamH group (FamH×self-management, pinteraction=0.050–0.001). Conclusions In Asia, FamH was common and associated with young age of diagnosis which might be delayed by healthy lifestyle while self management  was associated with better control of  cardiometabolic risk factors especially in those with FamH.

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DKD causes co-morbidities made preventable by attaining multiple targets. Patient empowerment, regular feedback and team-based care assisted by JADE Technology with risk stratification and decision support may improve targets attainment and clinical outcomes. In 2014-2018, 2435 patients1 with DKD2 (age:67.6±9.9 years, DM duration:16.5±9.7 years; BMI:26.9±4.7 kg/m2; A1c:7.9±1.6%; SBP:139±18 mmHg; LDL-C:2.35±1.05 mmol/L; TG:1.92±1.29 mmol/L; RASi:70.0%; statin:74.8%; CVD:32.0%, cancer:5.0%, heart failure:3.9%, ≥3 targets3:33.6%), were randomized to usual care (UC=809), empowered care (EC=819) and team-based empowered care (TEC=807) for 1 year with endpoints defined at year 1 and when study ends. After structured assessment, EC and TEC received JADE report, with EC receiving 3-monthly phone calls by nurses and TEC, additional 3-monthly review by a doctor-nurse team with JADE follow-up reports. Amongst 1837 returnees at 1 year, TEC had the lowest HbA1c and LDL-C and highest proportion with ≥3 targets (TMT)4. Non-returnees had worse risk profiles and were less likely to have familial DM and received prior DM education. At study end (2019)5, TMT group (27/408) had fewer CV-renal-cancer endpoints than non-TMT group (66/676) with RR of 0.678 (95% CI: 0.668-0.687). Empowerment, information support and continuing team-based care improve risk factor control and clinical outcomes in DKD. Disclosure J.C.N. Chan: Board Member; Self; Asia Diabetes Foundation. Consultant; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Lilly Diabetes, Medtronic, Merck Sharp & Dohme Corp., Sanofi-Aventis. Research Support; Self; Amgen Inc., AstraZeneca, Lee Powder, Lilly Diabetes, Pfizer Inc., Sanofi-Aventis. Speaker’s Bureau; Self; Ascensia Diabetes Care. Stock/Shareholder; Self; GemVCare. K.T. Nguyen: Advisory Panel; Self; Boehringer Ingelheim Pharmaceuticals, Inc. Speaker’s Bureau; Self; Abbott. Other Relationship; Self; AstraZeneca, Novo Nordisk A/S, Sanofi-Aventis. A. Tan: None. Y.C. Chia: None. C. Hwu: None. E. Hong: None. Y. Thewjitcharoen: None. J. Du: None. S. Yoo: None. R.C. Mirasol: None. E.S. Lau: None. V. Lau: None. A.W.C. Fu: None. M. Mohamed: None. K. Yoon: Advisory Panel; Self; AstraZeneca, Boehringer Ingelheim Pharmaceuticals, Inc., Merck Sharp & Dohme Corp., Novo Nordisk Inc. Speaker’s Bureau; Self; Takeda Pharmaceutical Company Limited. C. Tsang: None. A. Luk: None. Funding Asia Diabetes Foundation