BACKGROUND: 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 noninsulin 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. CONCLUSION: 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.

Scotti, L., Romio, S., Ghirardi, A., Arfè, A., Casula, M., Hazell, L., et al. (2015). Should methods of correction for multiple comparisons be applied in pharmacovigilance? Reasoning around an investigation on safety of oral antidiabetic drugs. EPIDEMIOLOGY BIOSTATISTICS AND PUBLIC HEALTH, 12(4) [10.2427/11654].

Should methods of correction for multiple comparisons be applied in pharmacovigilance? Reasoning around an investigation on safety of oral antidiabetic drugs

SCOTTI, LORENZA
;
ROMIO, SILVANA ANTONIETTA
Secondo
;
GHIRARDI, ARIANNA;CORRAO, GIOVANNI
Ultimo
2015

Abstract

BACKGROUND: 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 noninsulin 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. CONCLUSION: 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.
Articolo in rivista - Articolo scientifico
Bladder safety; Cardiovascular safety; False discovery rate; Noninsulin blood glucose lowering drugs; Pancreatic safety; Pharmacovigilance; Spontaneous report database; Epidemiology; Health Policy; Public Health, Environmental and Occupational Health; Community and Home Care
English
7
Scotti, L., Romio, S., Ghirardi, A., Arfè, A., Casula, M., Hazell, L., et al. (2015). Should methods of correction for multiple comparisons be applied in pharmacovigilance? Reasoning around an investigation on safety of oral antidiabetic drugs. EPIDEMIOLOGY BIOSTATISTICS AND PUBLIC HEALTH, 12(4) [10.2427/11654].
Scotti, L; Romio, S; Ghirardi, A; Arfè, A; Casula, M; Hazell, L; Lapi, F; Catapano, A; Sturkenboom, M; Corrao, G
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10281/100165
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