Should methods of correction for multiple comparisons be applied in pharmacovigilance?

Authors

  • Lorenza Scotti University of Milano-Bicocca
  • Silvana Romio University of Milano-Bicocca
  • Arianna Ghirardi University of Milano-Bicocca
  • Andrea Arfè University of Milano-Bicocca
  • Manuela Casula University of Milano
  • Lorna Hazell University of Portsmouth
  • Francesco Lapi Italian College of General Practitioners, Florence
  • Alberico Catapano University of Milano
  • Miriam Sturkenboom Erasmus Medical Center, Rotterdam
  • Giovanni Corrao University of Milano-Bicocca

DOI:

https://doi.org/10.2427/11654

Abstract

Purpose. In pharmacovigilance, spontaneous reporting databases are devoted to the early detection of adverse event ‘signals’ of marketed drugs. A common limitation of these systems is the wide number of concurrently investigated associations, implying a high probability of generating positive signals simply by chance. However it is not clear if the application of methods aimed to adjust for the multiple testing problems are needed when at least some of the drug-outcome relationship under study are known. To this aim we applied a robust estimation method for the FDR (rFDR) particularly suitable in the pharmacovigilance context.

Methods. We exploited the data available for the SAFEGUARD project to apply the rFDR estimation methods to detect potential false positive signals of adverse reactions attributable to the use of non-insulin blood glucose lowering drugs. Specifically, the number of signals generated from the conventional disproportionality measures and after the application of the rFDR adjustment method was compared.

Results. Among the 311 evaluable pairs (i.e., drug-event pairs with at least one adverse event report), 106 (34%) signals were considered as significant from the conventional analysis. Among them 1 resulted in false positive signals according to rFDR method.

Conclusions. The results of this study seem to suggest that when a restricted number of drug-outcome pairs is considered and warnings about some of them are known, multiple comparisons methods for recognizing false positive signals are not so useful as suggested by theoretical considerations.

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Published

2022-04-26

Issue

Section

Statistical Methods