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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2015-12

AUTHORS

Jason P. Gordon, Marc Evans, Jorge Puelles, Philip C. McEwan

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. More... »

PAGES

495-507

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s13300-015-0134-y

DOI

http://dx.doi.org/10.1007/s13300-015-0134-y

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1002073574

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/26446552


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