Development and Internal Validation of A Prediction Tool To Assist Clinicians Selecting Second-Line Therapy Following Metformin Monotherapy For Type 2 Diabetes

ObjectiveAdults with type 2 diabetes (T2D) face increased risk of many long-term adverse outcomes. While managing patients with T2D, clinicians are challenged to stay informed regarding all new therapies and must consider potential risks and benefits resultant to their use. Metformin (MET) is typically prescribed as first-line therapy, but a second line is often needed, given MET can be insufficient for maintaining long-term glycemic control. Our objective was to develop a predictive decision-making tool to help clinicians use an outcome-based approach to select second-line therapies for patients when MET monotherapy is insufficient for glycemic control.MethodsElectronic health records of 19 277 adults with T2D on MET monotherapy and ≥3 months of either GLP-1RA, DPP-4i, Insulin, SGLT-2i, SFU, or TZD therapy were reviewed at Cleveland Clinic from patient visits occurring between 2005 and 2019. Separate models were developed to predict likelihood of each main outcome measure (stroke, myocardial infarction, worsening hypertension, renal failure, and death). Discrimination and calibration were assessed with bootstrapping.ResultsThe median follow-up time for those without an event was 3.6 years (interquartile range 1.9, 6.3). Model discrimination ability was evaluated by concordance indices (goodness of fit metric with values ranging between 0 and 1: 1 indicates perfect discrimination ability; 0.5 reflects same discrimination ability as chance) demonstrating strong discrimination ability, with concordance index values for outcomes as follows: myocardial infarction (0.786), stroke (0.805), worsening hypertension (0.855), renal failure (0.808), and death (0.827).ConclusionA decision-making tool has been developed that may afford clinicians a more objective and individualized approach to choosing a second-line therapy to control glycemia for persons with T2D.