Using real-world healthcare data for pharmacovigilance signal detection – the experience of the EU-ADR project

References

• Council for International Organizations of Medical Sciences (CIOMS). Practical Aspects of Signal Detection in Pharmacovigilance. Working Group VIII. 2010
   Google Scholar
• Hauben M, Aronson JK. Defining signal and its subtypes in pharmacovigilance based on a systematic review of previous definitions. Drug Saf 2009;32(2):99-110
   PubMed Web of Science ®Google Scholar
• Szarfman A, Machado SG, O’Neill RT. Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the US FDA’s spontaneous reports database. Drug Saf 2002;25(6):381-92
   PubMed Web of Science ®Google Scholar
• The importance of pharmacovigilance - safety monitoring of medicinal products. 2002. Available from: http://apps.who.int/medicinedocs/en/d/Js4893e/ [Last accessed 10 August 2014]
   Google Scholar
• Arora R, Liebo M, Maldonado F. Statin-induced myopathy: the two faces of Janus. J Cardiovasc Pharmacol Ther 2006;11(2):105-12
   PubMedGoogle Scholar
• McNaughton R, Huet G, Shakir S. An investigation into drug products withdrawn from the EU market between 2002 and 2011 for safety reasons and the evidence used to support the decision-making. BMJ Open 2014;4(1):e004221
   PubMed Web of Science ®Google Scholar
• Rodriguez E, Staffa J, Graham D. The role of databases in drug postmarketing surveillance. Pharmacoepidemiol Drug Saf 2001;10:407-10
   PubMed Web of Science ®Google Scholar
• Ross JS, Madigan D, Hill KP, et al. Pooled analysis of rofecoxib placebo-controlled clinical trial data: lessons for postmarket pharmaceutical safety surveillance. Arch Intern Med 2009;169:1976-85
   PubMed Web of Science ®Google Scholar
• Wadman M. News feature: strong medicine. Nat Med 2005;11:465-6
   PubMedGoogle Scholar
• Schneeweiss S, Avorn J. A review of uses of health care utilization databases for epidemiologic research on therapeutics. J Clin Epidemiol 2005;58:323-37
   PubMed Web of Science ®Google Scholar
• Norén G, Hopstadius J, Bate A, et al. Temporal pattern discovery in longitudinal electronic patient records. Data Min Knowl Discov 2010;20:361-87
   Web of Science ®Google Scholar
• Zorych I, Madigan D, Ryan P, et al. Disproportionality methods for pharmacovigilance in longitudinal observational databases. Stat Methods Med Res 2013;22:39-56
   PubMed Web of Science ®Google Scholar
• Norén G, Hopstadius J, Bate A, et al. Safety surveillance of longitudinal databases: methodological considerations. Pharmacoepidemiol Drug Saf 2011;20:714-17
   PubMed Web of Science ®Google Scholar
• Schuemie M, Coloma P, Straatman H, et al. Using electronic health care records for drug safety signal detection: a comparative evaluation of statistical methods. Med Care 2012;10:890-7
   Google Scholar
• Hartzema A, Racoosin J, MaCurdy T, et al. Utilizing Medicare claims data for real-time drug safety evaluations: is it feasible? Pharmacoepidemiol Drug Saf 2011;20:684-8
   PubMedGoogle Scholar
• Stang PE, Ryan PB, Racoosin JA, et al. Advancing the science for active surveillance: rationale and design for the Observational Medical Outcomes Partnership. Ann Intern Med 2010;153:600-6
   PubMed Web of Science ®Google Scholar
• Ryan PB, Madigan D, Stang PE, et al. Empirical assessment of methods for risk identification in healthcare data: results from the experiments of the Observational Medical Outcomes Partnership. Stat Med 2012;31:4401-15
   PubMed Web of Science ®Google Scholar
• FDA’s Sentinel Initiative: transforming how we monitor the safety of FDA-regulated products 2014. Available from: www.fda.gov/Safety/FDAsSentinelInitiative/ucm2007250.htm [Last accessed 7 June 2014]
   Google Scholar
• Trifirò G, Pariente A, Coloma PM, 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
   PubMed Web of Science ®Google Scholar
• Trifiro G, Fourrier-Reglat A, Sturkenboom MCJM, et al. The EU-ADR project: preliminary results and perspective. Stud Health Tech Inform 2009;148:43-9
   PubMedGoogle Scholar
• Pharmacoepidemiological Research on Outcomes of Therapeutics by a European Consortium 2014. Available from: www.imi-protect.eu/ [Last accessed 7 June 2014]
   Google Scholar
• Trifirò G, Patadia V, Schuemie MJ, et al. EU-ADR healthcare database network vs. spontaneous reporting system database: preliminary comparison of signal detection. Stud Health Tech Inform 2011;166:25-30
   PubMedGoogle Scholar
• Coloma PM, Schuemie MJ, Trifirò G, et al. Combining electronic healthcare databases in Europe to allow for large-scale drug safety monitoring: the EU-ADR Project. Pharmacoepidemiol Drug Saf 2011;20:1-11
   PubMed Web of Science ®Google Scholar
• Coloma PM, Trifirò G, Schuemie MJ, et al. Electronic healthcare databases for active drug safety surveillance: is there enough leverage? Pharmacoepidemiol Drug Saf 2012;21:611-21
   PubMedGoogle Scholar
• FDA Adverse Event Reporting System (FAERS) (formerly AERS). Available from: www.fda.gov/Drugs/GuidanceComplianceRegulatoryInformation/Surveillance/AdverseDrugEffects/default.htm [Last accessed 27 June 2014]
   Google Scholar
• VigiBase Database. Available from: http://whoumc2010.phosdev.se/DynPage.aspx?id=98082&mn1=7347&mn2=7252&mn3=7322&mn4=7326 [Last accessed 27 June 2014]
   Google Scholar
• Avillach P, Joubert M, Thiessard F, et al. Design and evaluation of a semantic approach for the homogeneous identification of events in eight patient databases: a contribution to the European EU-ADR project. Stud Health Tech Inform 2010;160:1085-9
   PubMedGoogle Scholar
• Avillach P, Coloma PM, Gini R, et al. Harmonization process for the identification of medical events in eight European healthcare databases: the experience from the EU-ADR project. J Am Med Inform Assoc 2013;20:184-92
   PubMed Web of Science ®Google Scholar
• Schuemie MJ. Methods for drug safety signal detection in longitudinal observational databases: LGPS and LEOPARD. Pharmacoepidemiol Drug Saf 2011;20:292-9
   PubMed Web of Science ®Google Scholar
• Gerhard T. Bias: considerations for research practice. Am J Health Syst Pharm 2008;65:2159-68
   PubMed Web of Science ®Google Scholar
• DuMouchel W. Bayesian data mining in large frequency tables, with an application to the FDA Spontaneous Reporting System. Am Statist 1999;53:177-90
   Web of Science ®Google Scholar
• Byrt T, Bishop J, Carlin J. Bias, prevalence and kappa. J Clin Epidemiol 1993;46:423-9
   PubMed Web of Science ®Google Scholar
• Landis R, Koch G. The measurement of observer agreement for categorical data. Biometrics 1977;33:159-74
   PubMed Web of Science ®Google Scholar
• Perez-Lloret S, Rey MV, Crispo J, et al. Risk of heart failure following treatment with dopamine agonists in Parkinson’s disease patients. Expert Opin Drug Saf 2014;13:351-60
   PubMed Web of Science ®Google Scholar
• Holt RIG, Barnett AH, Bailey CJ. Bromocriptine: old drug, new formulation and new indication. Diabetes Obes Metab 2010;12:1048-57
   PubMed Web of Science ®Google Scholar
• Hofmann C, Penner U, Dorow R, et al. Lisuride, a dopamine receptor agonist with 5-HT2B receptor antagonist properties: absence of cardiac valvulopathy adverse drug reaction reports supports the concept of a crucial role for 5-HT2B receptor agonism in cardiac valvular fibrosis. Clin Neuropharmacol 2006;29:80-6
   PubMed Web of Science ®Google Scholar