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Baseline differences in A1C explain apparent differences in efficacy of sitagliptin, rosiglitazone and pioglitazone
Author(s) -
Chapell R.,
Gould A. L.,
Alexander C. M.
Publication year - 2009
Publication title -
diabetes, obesity and metabolism
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.445
H-Index - 128
eISSN - 1463-1326
pISSN - 1462-8902
DOI - 10.1111/j.1463-1326.2009.01084.x
Subject(s) - sitagliptin , pioglitazone , rosiglitazone , medicine , confidence interval , baseline (sea) , meta analysis , diabetes mellitus , endocrinology , type 2 diabetes , metformin , insulin , oceanography , geology
Aim: Published studies of patients treated with rosiglitazone or pioglitazone have reported greater reductions in HbA1c (A1C) than studies of patients treated with sitagliptin. However, studies of thiazolidinediones tended to enroll patients with higher baseline A1C levels. This meta‐analysis investigates the relationship between baseline A1C and perceived efficacy of treatment. Methods: This report describes a Bayesian random effects analysis of 23 published studies. We constructed a random effects model including a factor adjusting for between‐study differences in baseline A1C levels. Results: The random effects model correctly predicts post‐treatment A1C levels from baseline A1C within a 95% confidence interval (CI) for each of the 23 studies included in the meta‐analysis. After applying the model to adjust for differences in baseline A1C, we found that the difference in efficacy between rosiglitazone and sitagliptin was not significantly different from zero (0.12; 95% CI −0.09 to 0.34). Similarly, no significant differences are observed between the effects of pioglitazone and sitagliptin (0.01; 95% CI −0.21 to 0.22) or between rosiglitazone and pioglitazone (0.11; 95% CI −0.37 to 0.146). When baseline values are omitted from the Bayesian model, the findings suggest that rosiglitazone is superior to pioglitazone or sitagliptin. Conclusions: These results illustrate the necessity for careful application of appropriate methodology when comparing results of different studies. When between‐study differences in treatment effects are adjusted for baseline differences, then the findings suggest that none of the treatments has an effect that is superior to any of the other treatments.