Assessing the Association of Pioglitazone Use and Bladder Cancer Through Drug Adverse Event Reporting

Abstract

OBJECTIVETo analyze the association between pioglitazone use and bladder cancer through a spontaneous adverse event reporting system for medications.RESEARCH DESIGN AND METHODSCase/noncase bladder cancer reports associated with antidiabetic drug use were retrieved from the U.S. Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) between 2004 and 2009 and analyzed by the reporting odds ratio (ROR).RESULTSNinety-three reports of bladder cancer were retrieved, corresponding to 138 drug-reaction pairs (pioglitazone, 31; insulin, 29; metformin, 25; glimepiride, 13; exenatide, 8; others, 22). ROR was indicative of a definite risk for pioglitazone (4.30 [95% CI 2.82–6.52]), and a much weaker risk for gliclazide and acarbose, with very few cases being treated with these two drugs (6 and 4, respectively).CONCLUSIONSIn agreement with preclinical and clinical studies, AERS analysis is consistent with an association between pioglitazone and bladder cancer. This issue needs constant epidemiologic surveillance and urgent definition by more specific studies.

Benefits and strengths of the disproportionality analysis for identification of adverse drug reactions in a pharmacovigilance database

“…Studies in rats exposed to PPAR agonists indicated that tumours occurred in several tissues, with a distribution similar to that of PPARs. Clinical data (clinical trials and case reports) suggested the same association.Finally,a recent case-noncase study in the Food and Drug Administration (FDA) Adverse Event Reporting System (AERS) between 2004 and 2009 found a significant risk for pioglitazone (ROR = 4.30; 95% confidence interval 2.82-6.52).The risk of bladder cancer was less consistent for other hypoglycaemic drugs [5].In this situation of a pharmacological hypothesis,the advantage of the dispro- Table 1 Two-by-two contingency table for a combination 'drug X' (or 'drug of interest') and 'ADR Y' (or 'ADR of interest') and framework for the calculation of the disproportionality…”

“…All disproportionality analysis in a pharmacovigilance database requires a clear pharmacodynamic hypothesis established on basic properties of drugs. Several examples are given in the present paper, such as the carcinogenic properties of pioglitazone on bladder [5], the thrombotic risk of coxibs [6] and the involvement of nonsteroidal anti-inflammatory drugs in necrotizing soft-tissue infections [7]. This case-noncase method cannot be used for investigating all risks of all drugs without a strong basic pharmacodynamic hypothesis.…”

Pioglitazone and bladder cancer risk: a multipopulation pooled, cumulative exposure analysis

“…Since these cautions, several studies and meta-analyses of published data have reported contradictory results [12][13][14][15][16][17][18][19][20][21][22][23][24]. This may result from issues associated with observational study design, including limited sample size and a lack of attention to potential biases such as cancer ascertainment bias, immortal time bias, and the effects of diabetes duration and glycaemic control [25,26].…”

Data Mining Techniques in Pharmacovigilance: Analysis of the Publicly Accessible FDA Adverse Event Reporting System (AERS)

“…This choice is mainly based on the fact that the FDA_AERS is a worldwide publicly available pharmacovigilance archive and, therefore, we believe that transparency may improve accuracy, allow comparison of results among researchers and foster implementation. By virtue of its large population coverage and free availability, the FDA_AERS is emerging as a cornerstone for signal detection in PhV and is progressively being exploited by US and European researchers [25,73,77,78]. In addition, a number of commercial tools, namely query engines are now available.…”