A method for the minimization of competition bias in signal detection from spontaneous reporting databases

Drug Safety

Volumn 39, Issue 3, 2016, Pages 251-260

  Arnaud, Mickael ^a,b   Salvo, Francesco ^a,b,c   Ahmed, Ismaïl ^d,e,f   Robinson, Philip ^a,g   Moore, Nicholas ^a,b,c,g   Bégaud, Bernard ^a,b,c   Tubert Bitter, Pascale ^d,e,f   Pariente, Antoine ^a,b,c,g  

^a UNIVERSITÉ DE BORDEAUX   (France)

^b INSERM U657   (France)

^c BORDEAUX UNIVERSITY HOSPITAL   (France)

^d LABORATOIRE DES SCIENCES DU CLIMAT ET DE L ENVIRONNEMENT   (France)

^e University Versailles Saint Quentin UVSQ   (France)

^f INSTITUT PASTEUR   (France)

^g Centre of Clinical Investigation Clinical Epidemiology   (France)

Author keywords

[No Author keywords available]

Indexed keywords

ACUTE HEART INFARCTION; ACUTE PANCREATITIS; APLASTIC ANEMIA; ARTICLE; AUTOMATION; CONVULSION; DRUG SAFETY; DRUG SURVEILLANCE PROGRAM; FACTUAL DATABASE; GASTROINTESTINAL HEMORRHAGE; HUMAN; MASKING FACTOR; MASKING RATIO; MEDICAL DICTIONARY FOR REGULATORY ACTIVITIES; PILOT STUDY; PRIORITY JOURNAL; SIGNAL DETECTION; SIGNAL OF DISPROPORTIONATE REPORTING; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; STANDARDS; STATISTICAL BIAS; STATISTICS AND NUMERICAL DATA;

ADVERSE DRUG REACTION REPORTING SYSTEMS; BIAS (EPIDEMIOLOGY); DATABASES, FACTUAL; DRUG-RELATED SIDE EFFECTS AND ADVERSE REACTIONS; HUMANS; PILOT PROJECTS;

EID: 85006969593     PISSN: 01145916     EISSN: 11791942     Source Type: Journal    
DOI: 10.1007/s40264-015-0375-8     Document Type: Article

References (24)

1. Moore N. The past, present and perhaps future of pharmacovigilance: homage to Folke Sjoqvist. Eur J Clin Pharmacol. 2013;69:33–41.
2. Pariente A, Gregoire F, Fourrier-Reglat A, Haramburu F, Moore N. Impact of safety alerts on measures of disproportionality in spontaneous reporting databases: the notoriety bias. Drug Saf. 2007;30:891–8.
3. Gould A. Practical pharmacovigilance analysis strategies. Pharmacoepidemiol Drug Saf. 2003;12:559–74.
4. Hauben M, Madigan D, Gerrits CM, Walsh L, Van Puijenbroek EP. The role of data mining in pharmacovigilance. Expert Opin Drug Saf. 2005;4:929–48.
5. Pariente A, Didailler M, Avillach P, Miremont-Salamé G, Fourrier-Reglat A, Haramburu F, et al. A potential competition bias in the detection of safety signals from spontaneous reporting databases. Pharmacoepidemiol Drug Saf. 2010;19:1166–71.
6. Evans SJW, Waller PC, Davis S. Use of proportional reporting ratios (PRRs) for signal generation from spontaneous adverse drug reaction reports. Pharmacoepidemiol Drug Saf. 2001;10: 483–6.
7. Juhlin K, Ye X, Star K, Norén GN. Outlier removal to uncover patterns in adverse drug reaction surveillance—a simple unmasking strategy. Pharmacoepidemiol Drug Saf. 2013;22: 1119–29.
8. Maignen F, Hauben M, Hung E, Holle LV, Dogne J-M. A conceptual approach to the masking effect of measures of disproportionality. Pharmacoepidemiol Drug Saf. 2014;23:208–17.
9. Pariente A, Avillach P, Salvo F, Thiessard F, Miremont-Salamé G, Fourrier-Reglat A, et al. Effect of competition bias in safety signal generation. Drug Saf. 2012;35:855–64.
10. Salvo F, Raschi E, Moretti U, Chiarolanza A, Fourrier-Réglat A, Moore N, et al. Pharmacological prioritisation of signals of disproportionate reporting: proposal of an algorithm and pilot evaluation. Eur J Clin Pharmacol. 2014;70:617–25.
11. Maignen F, Hauben M, Hung E, Van Holle L, Dogne J-M. Assessing the extent and impact of the masking effect of disproportionality analyses on two spontaneous reporting systems databases. Pharmacoepidemiol Drug Saf. 2014;23:195–207.
12. Salvo F, Raschi E, Moretti U, Chiarolanza A, Fourrier-Réglat A, Moore N, et al. Pharmacological prioritisation of signals of disproportionate reporting: proposal of an algorithm and pilot evaluation. Eur J Clin Pharmacol. 2014;70:617–25.
13. Trifiro G, Pariente A, Coloma PM, Kors JA, Polimeni G, Miremont-Salamé G, et al. Data mining on electronic health record databases for signal detection in pharmacovigilance: which events to monitor? Pharmacoepidemiol Drug Saf. 2009;18:1176–84.
14. European Medicines Agency. Summary of product characteristics (EU). 2014. http://www.ema.europa.eu/ema/. Accessed 8 Sep 2015.
15. Vidal 2014: le dictionnaire. 90e ed. Issy-les-Moulineaux: Vidal; 2014.
16. Cantor SB, Kattan MW. Determining the area under the ROC curve for a binary diagnostic test. Med Decis Making. 2000;20:468–70.
17. Hanley JA, McNeil BJ. The meaning and use of the area under a receiver operating characteristic (ROC) curve. Radiology. 1982;143:29–36.
18. van Puijenbroek EP, Bate A, Leufkens HGM, Lindquist M, Orre R, Egberts ACG. A comparison of measures of disproportionality for signal detection in spontaneous reporting systems for adverse drug reactions. Pharmacoepidemiol Drug Saf. 2002;11:3–10.
19. Géniaux H, Assaf D, Miremont-Salamé G, Raspaud B, Gouverneur A, Robinson P, et al. Performance of the standardised MedDRA_ queries for case retrieval in the French spontaneous reporting database. Drug Saf. 2014;37:537–42.
20. Moore N, Kreft-Jais C, Haramburu F, Noblet C, Andrejak M, Ollagnier M, et al. Reports of hypoglycaemia associated with the use of ACE inhibitors and other drugs: a case/non-case study in the French pharmacovigilance system database. Br J Clin Pharmacol. 2003;44:513–8.
21. Bate A, Lindquist M, Edwards IR, Olsson S, Orre R, Lansner A, et al. A Bayesian neural network method for adverse drug reaction signal generation. Eur J Clin Pharmacol. 1998;54:315–21.
22. DuMouchel W. Bayesian data mining in large frequency tables, with an application to the FDA spontaneous reporting system. Am Stat. 1999;53:177–89.
23. Ahmed I, Thiessard F, Miremont-Salame G, Haramburu F, Kreft-Jais C, Bégaud B, et al. Early detection of pharmacovigilance signals with automated methods based on false discovery rates. Drug Saf. 2012;35:495–506.
24. Ryan PB, Schuemie MJ, Welebob E, Duke J, Valentine S, Hartzema AG. Defining a reference set to support methodological research in drug safety. Drug Saf. 2013;36:33–47.