A meta-epidemiological study found lack of transparency and poor reporting of disproportionality analyses for signal detection in pharmacovigilance databases
| Autor: | Amelle Mouffak, Jean-Luc Cracowski, Bruno Revol, Claire Bernardeau, Marion Lepelley, Antoine Pariente, Francesco Salvo, Matthieu Roustit, Charles Khouri |
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| Přispěvatelé: | Bordeaux population health (BPH), Université de Bordeaux (UB)-Institut de Santé Publique, d'Épidémiologie et de Développement (ISPED)-Institut National de la Santé et de la Recherche Médicale (INSERM) |
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Biomedical Research
Databases Factual Drug-Related Side Effects and Adverse Reactions Epidemiology Computer science Population MEDLINE Feature selection Transparency 030226 pharmacology & pharmacy 03 medical and health sciences Pharmacovigilance 0302 clinical medicine Statistics Adverse Drug Reaction Reporting Systems Humans 030212 general & internal medicine Disproportionality analyses education Selection (genetic algorithm) Protocol (science) education.field_of_study 3. Good health Data Accuracy Epidemiologic Studies Data extraction Reporting Transparency (graphic) [SDV.SPEE]Life Sciences [q-bio]/Santé publique et épidémiologie Periodicals as Topic Publication Bias Signal detection |
| Zdroj: | Journal of Clinical Epidemiology Journal of Clinical Epidemiology, Elsevier, 2021, ⟨10.1016/j.jclinepi.2021.07.014⟩ |
| ISSN: | 0895-4356 |
| Popis: | Objectives To review and appraise methods and reporting characteristics of pharmacovigilance disproportionality analyses. Study Design and Setting We randomly selected 100 disproportionality analyses indexed in Medline found during a systematic literature search. We then extracted and synthetized methodological and reporting characteristics using seven key items: (1) title transparency; (2) protocol pre-registration; (3) date of data extraction and analysis; (4) outcome, population, exposure and comparator definitions; (5) adjustment and stratification of results; (6) method and threshold for signal detection; (7) secondary and sensitivity analyses. Results We found that methods used to generate disproportionality signals were extremely heterogeneous; there were nearly as many unique analyses as studies. The authors used various populations, methods, signal detection thresholds, adjustment or stratification variables, generally without justification for their choice or pre-specification in protocols. Moreover, 78% of studies failed to report methods for case, adverse drug reactions or comparator selection and 32 studies did not define the threshold for signal generation. Conclusion Our survey raises major concerns regarding all aspects of disproportionality analyses that could lead to misleading results and generate unjustified alarms. We advocate for a strong and transparent rationale for variable selection, choice of population and comparators pre-specified in a protocol and assessed by sensitivity analyses. |
| Databáze: | OpenAIRE |
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