Effect of consumer reporting on signal detection: using disproportionality analysis

被引:34
作者
Hammond, Isaac W. [1 ]
Rich, Donna S.
Gibbs, Trevor G.
机构
[1] GlaxoSmithKline, Global Clin Safety & Pharmacogvigilance, Collegeville, PA 19426 USA
[2] GlaxoSmithKline, Collegeville, PA USA
[3] GlaxoSmithKline, London, England
关键词
consumer reporting of adverse events; disproportionality analysis; pharmacovigilance; signal detection;
D O I
10.1517/14740338.6.6.705
中图分类号
R9 [药学];
学科分类号
1007 ;
摘要
Pharmacovigilance objectives and activities are designed to protect the health of consumers and are generally based on data acquisition from spontaneous adverse event reports (SADRs). SADRs come from different sources, including healthcare professionals, consumers, lawyers, other pharmaceutical companies, regulatory agencies and so on. Pharmacovigilance activities derived from SADRs include signal detection and description of the safety profile of the drug. Consumers are the most frequent source of most SADRs, even though the system was originally designed to receive reports from healthcare professionals. Most spontaneous adverse event reports are received from the US. GaxoSmithKline (GSK) conducts monthly signal detection on all marketed compounds in its global database using disproportionality analysis, the empirical Bayesian algorithm known as a multiple-item gamma-Poisson shrinker. There are no systematic survey data or reviews of actual experiences within existing safety surveillance databases of how pharmaceutical companies handle consumer reports. Thus, a study was undertaken to determine the impact of consumer reports on signal detection using MGPS disproportionality analysis. Two data sets were created for four randomly selected GSK marketed compounds; one data set included reports from both consumer and healthcare providers and the second included only reports from healthcare providers. Disproportionality analysis was then used to evaluate the two data sets. A total of 23 signals were identified with a mean difference in time to signal detection of 1.8 years. The difference was in the range of -8 - 10 years. In 52.2% of events (12/23), the signal was identified earlier when consumer reports were included in the data. In 34.8% of events (8/23), the signal was identified in the same year in both data sets and, in 13% of the events (3/23), the signal was identified later when consumer reports were included in the data. It was concluded from this study that adverse event reports submitted directly to pharmaceutical companies by consumers can help significantly in the early detection of safety signals.
引用
收藏
页码:705 / 712
页数:8
相关论文
共 34 条
[21]   A retrospective evaluation of a data mining approach to aid finding new adverse drug reaction signals in the WHO International Database [J].
Lindquist, M ;
Ståhl, M ;
Bate, A ;
Edwards, IR ;
Meyboom, RHB .
DRUG SAFETY, 2000, 23 (06) :533-542
[22]   PATIENTS AS A DIRECT SOURCE OF INFORMATION ON ADVERSE DRUG-REACTIONS [J].
MITCHELL, AS ;
HENRY, DA ;
SANSONFISHER, R ;
OCONNELL, DL .
BRITISH MEDICAL JOURNAL, 1988, 297 (6653) :891-893
[23]   Some US Food and Drug Administration perspectives on data mining for pediatric safety assessment [J].
O'Neill, RT ;
Szarfman, A .
CURRENT THERAPEUTIC RESEARCH-CLINICAL AND EXPERIMENTAL, 2001, 62 (09) :650-663
[24]   Bayesian neural networks with confidence estimations applied to data mining [J].
Orre, R ;
Lansner, A ;
Bate, A ;
Lindquist, M .
COMPUTATIONAL STATISTICS & DATA ANALYSIS, 2000, 34 (04) :473-493
[25]   Statistical techniques for signal generation - The Australian experience [J].
Purcell, P ;
Barty, S .
DRUG SAFETY, 2002, 25 (06) :415-421
[26]  
RAWLINS MD, 1995, J ROY COLL PHYS LOND, V29, P41
[27]   PHARMACOEPIDEMIOLOGY - CURRENT STATUS, PROSPECTS, AND PROBLEMS [J].
STROM, BL ;
TUGWELL, P .
ANNALS OF INTERNAL MEDICINE, 1990, 113 (03) :179-181
[28]   Use of screening algorithms and computer systems to efficiently signal higher-than-expected combinations of drugs and events in the USFDA's spontaneous reports database [J].
Szarfman, A ;
Machado, SG ;
O'Neill, RT .
DRUG SAFETY, 2002, 25 (06) :381-392
[29]   Consumer adverse drug reaction reporting - A new step in pharmacovigilance? [J].
van Grootheest, K ;
de Graaf, L ;
de Jong-van den Berg, LTW .
DRUG SAFETY, 2003, 26 (04) :211-217
[30]   Application of quantitative signal detection in the Dutch spontaneous reporting system for adverse drug reactions [J].
van Puijenbroek, EP ;
Diemont, WL ;
van Grootheest, K .
DRUG SAFETY, 2003, 26 (05) :293-301