Factors Predictive of Weight Gain and Implications for Modeling in Type 2 Diabetes Patients Initiating Metformin and Sulfonylurea Combination Therapy

Diabetes Ther. 2015 Dec;6(4):495-507. doi: 10.1007/s13300-015-0134-y. Epub 2015 Oct 7.

Abstract

Introduction: The objectives of this study were to (a) assess the factors associated with weight gain in a population of type 2 diabetes patients escalating from metformin (M) to M+ sulfonylurea (M + S) and (b) evaluate whether healthcare resource utilization associated with being overweight or obese is underestimated in typical health economic evaluations.

Methods: The study was a retrospective cohort study using UK Clinical Practice Research Datalink linked to Hospital Episode Statistics (CPRD/HES) data. The association between baseline phenotypic factors and weight gain was assessed using logistic regression. Hospitalization incidence rates per 1000 person-years for major diabetes-related complications according to body mass index (BMI) at baseline were estimated from the data (observed) and compared to those obtained from a validated diabetes model (predicted).

Results: 11,071 patients were included in the analysis; approximately 40% gained weight in the first year following escalation to M + S. Baseline age, HbA1c and gender were found to be predictors of weight gain [odds ratios 0.99 (1-year increment), 1.11 (1% increment) and 0.81 (female vs male), respectively, p < 0.001]. Observed vs predicted incidence rates of hospitalization were 265 vs 13 (normal), 297 vs 31 (overweight), 223 vs 50 (obese) and 378 vs 41 (severe obese).

Conclusion: This analysis suggests there are identifiable patient characteristics predictive of weight gain that may be informative to clinical and economic decision making in the context of patients escalating from M to an M + S regimen. Hospital admissions in people with type 2 diabetes were generally under-predicted. A particular focus of future research should be the need for diabetes models to make the likelihood of experiencing an event conditional on BMI.

Funding: Takeda Development Centre Europe Ltd., UK.

Keywords: Diabetes modeling; Therapy escalation; Type 2 diabetes; Weight gain.