PMID- 31190237
OWN - NLM
STAT- MEDLINE
DCOM- 20200520
LR  - 20231013
IS  - 1179-1942 (Electronic)
IS  - 0114-5916 (Print)
IS  - 0114-5916 (Linking)
VI  - 42
IP  - 10
DP  - 2019 Oct
TI  - Pooling Different Safety Data Sources: Impact of Combining Solicited and 
      Spontaneous Reports on Signal Detection In Pharmacovigilance.
PG  - 1191-1198
LID - 10.1007/s40264-019-00843-0 [doi]
AB  - INTRODUCTION: The volume of adverse events (AEs) collected, analysed, and 
      reported has been increasing at a rapid rate for over the past 10 years, largely 
      due to the growth of solicited programmes. The proportion of various forms of 
      solicited case data has evolved over time, with the main relative volume increase 
      coming from Patient Support Programmes. In this study, we sought to examine the 
      impact of the pooling of AE report data from solicited sources with data from 
      spontaneous sources to safety signal detection using disproportionality analysis 
      methods. METHODS: Two conditions were explored in which disproportionality scores 
      from hypothetical drugs were evaluated in a simulated safety database. The first 
      condition held occurrence of events constant and varied solicited case volume, 
      while the second condition varied both proportion of occurrence of events and 
      solicited case volume. RESULTS: In the first setting, where all AE terms have the 
      same probability to occur with any drug, increasing volumes of solicited cases 
      while keeping occurrence of events constant leads to reduced variability in 
      disproportionality scores, consequently reducing or eliminating identified 
      signals of disproportionate reporting. In the second setting, varying both case 
      volume and reporting rates can mask true safety signals and falsely identify 
      signals where there are none. CONCLUSIONS: This analysis of simulated data 
      suggests that pooling AE data from solicited sources with spontaneous case data 
      may impact the results of disproportionality analyses, masking true safety 
      signals and identifying false positives. Therefore, increased volumes of safety 
      data do not necessarily correlate with improved safety signal detection.
FAU - Jokinen, Jeremy D
AU  - Jokinen JD
AUID- ORCID: 0000-0001-8484-5788
AD  - AbbVie Inc., North Chicago, IL, USA.
FAU - Walley, Rosalind J
AU  - Walley RJ
AD  - UCB Pharma, Slough, UK.
FAU - Colopy, Michael W
AU  - Colopy MW
AD  - UCB Pharma, Raleigh, NC, USA.
FAU - Hilzinger, Thomas S
AU  - Hilzinger TS
AD  - PricewaterhouseCoopers, Chicago, IL, USA.
FAU - Verdru, Peter
AU  - Verdru P
AUID- ORCID: 0000-0002-0964-5740
AD  - UCB Pharma, Brussels, Belgium. pverdru@gmail.com.
LA  - eng
PT  - Journal Article
PL  - New Zealand
TA  - Drug Saf
JT  - Drug safety
JID - 9002928
SB  - IM
MH  - *Adverse Drug Reaction Reporting Systems
MH  - Drug-Related Side Effects and Adverse Reactions
MH  - Humans
MH  - *Patient Safety
MH  - *Pharmacovigilance
MH  - Risk Factors
PMC - PMC6739274
COIS- Jeremy Jokinen is an employee and shareholder of Abbvie, Inc.; Thomas S. 
      Hilzinger is an employee of PricewaterhouseCoopers, LLP; Rosalind J. Walley is an 
      employee and shareholder of UCB Pharma; Peter Verdru is an employee and 
      shareholder of UCB BioPharma SPRL; and Michael W. Colopy is an employee and 
      shareholder of UCB Biosciences.
EDAT- 2019/06/14 06:00
MHDA- 2020/05/21 06:00
PMCR- 2019/06/12
CRDT- 2019/06/14 06:00
PHST- 2019/06/14 06:00 [pubmed]
PHST- 2020/05/21 06:00 [medline]
PHST- 2019/06/14 06:00 [entrez]
PHST- 2019/06/12 00:00 [pmc-release]
AID - 10.1007/s40264-019-00843-0 [pii]
AID - 843 [pii]
AID - 10.1007/s40264-019-00843-0 [doi]
PST - ppublish
SO  - Drug Saf. 2019 Oct;42(10):1191-1198. doi: 10.1007/s40264-019-00843-0.