A data-driven approach to identify clusters of HbA1c longitudinal trajectories and associated outcomes in type 2 diabetes mellitus: a large population-based cohort study

Background We aimed to identify and characterize common patterns of HbA1c progression among type 2 diabetes mellitus patients who initiate a non-insulin antidiabetic drug (NIAD). Methods The IQVIA Medical Research Data incorporating data from THIN, a Cegedim database of anonymized electronic health records, was used to identify a cohort of patients with a first-ever prescription for a NIAD between 2006 and 2019. Trajectory clusters were identified using an Expectation-Maximization algorithm by iteratively fitting k thin-plate splines and reassigning each patient to the nearest cluster. Cox proportional hazards models calculated the hazard ratios (HR) and 95% confidence intervals (CI) for the estimated risk of microvascular (e.g., retinopathy, diabetic polyneuropathy [DPN]) and macrovascular events. Findings Among 116,251 new users of NIADs we found five distinct clusters of HbA1c progression, which were characterized as: optimally controlled ( OC ), adequately controlled ( AC ), sub-optimally controlled ( SOC ), poorly controlled ( PC ), and uncontrolled ( UC ). The UC and AC clusters had similar index HbA1C (>9%) but the AC cluster achieved HbA1c control (HbA1C <7.5%), while the UC cluster HbA1c remained >9.0%. Compared to the OC cluster, there was a 21% (HR: 1.21, 95% CI: 1.14-1.28) and 30% (HR: 1.30, 95% CI: 1.21-1.40) elevated risk of retinopathy in the AC and UC clusters, respectively. While the PC and UC clusters had a significant 23% (HR 1.23, 95% CI 1.12 – 1.35) and 45% (HR 1.45, 95% CI: 1.27 – 1.64) increased risk of DPN, respectively. Interpretation The five identified HbA1c trajectory clusters had different risk profiles. Despite achieving diabetic control, patients categorized in the AC cluster had similar outcomes to the UC cluster, suggesting baseline HbA1c is an important indicator of health outcomes. Funding The Swiss Data Science Centre ### Competing Interest Statement SW is a member of the Human Medicines Expert Committee (HMEC) board of Swissmedic. The views expressed in this article are the personal views of the authors and may not be understood or quoted as being made on behalf of or reflecting the position of Swissmedic or one of its committees or working parties. The professorship of AMB was partly endowed by the National Association of Pharmacists (PharmaSuisse) and the ETH Foundation, but funds are not provided for research and the current project was not funded. AMDlT, MLF, CM, and FPC have no conflicts of interest to declare regarding this research. ### Funding Statement This research was funded by a Swiss Data Science Centre Collaboration Grant (C19-09). ### Author Declarations I confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained. Yes The details of the IRB/oversight body that provided approval or exemption for the research described are given below: The protocol for this project was approved by the THIN scientific research council (reference number: 20SR062). I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals. Yes I understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance). Yes I have followed all appropriate research reporting guidelines and uploaded the relevant EQUATOR Network research reporting checklist(s) and other pertinent material as supplementary files, if applicable. Yes The IQVIA Medical Research Data (IMRD) were obtained from IQVIA, a Cegedim database of anonymized electronic health records. For further information on access to the database, please contact IQVIA (contact details can be found at ).