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vigiRank for statistical signal detection in pharmacovigilance: First results from prospective real‐world use
Author(s) -
Caster Ola,
Sandberg Lovisa,
Bergvall Tomas,
Watson Sarah,
Norén G. Niklas
Publication year - 2017
Publication title -
pharmacoepidemiology and drug safety
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.023
H-Index - 96
eISSN - 1099-1557
pISSN - 1053-8569
DOI - 10.1002/pds.4247
Subject(s) - pharmacovigilance , medicine , metric (unit) , meddra , clinical endpoint , adverse effect , confidence interval , credibility , pharmacoepidemiology , data mining , statistics , clinical trial , pharmacology , computer science , operations management , political science , law , economics , mathematics , medical prescription
Purpose vigiRank is a data‐driven predictive model for emerging safety signals. In addition to disproportionate reporting patterns, it also accounts for the completeness, recency, and geographic spread of individual case reporting, as well as the availability of case narratives. Previous retrospective analysis suggested that vigiRank performed better than disproportionality analysis alone. The purpose of the present analysis was to evaluate its prospective performance. Methods The evaluation of vigiRank was based on real‐world signal detection in VigiBase. In May 2014, vigiRank scores were computed for pairs of new drugs and WHO Adverse Reaction Terminology critical terms with at most 30 reports from at least 2 countries. Initial manual assessments were performed in order of descending score, selecting a subset of drug‐adverse drug reaction pairs for in‐depth expert assessment. The primary performance metric was the proportion of initial assessments that were decided signals during in‐depth assessment. As comparator, the historical performance for disproportionality‐ guided signal detection in VigiBase was computed from a corresponding cohort of drug‐adverse drug reaction pairs assessed between 2009 and 2013. During this period, the requirement for initial manual assessment was a positive lower endpoint of the 95% credibility interval of the Information Component measure of disproportionality, observed for the first time. Results 194 initial assessments suggested by vigiRank's ordering eventually resulted in 6 (3.1%) signals. Disproportionality analysis yielded 19 signals from 1592 initial assessments (1.2%; P < .05). Conclusions Combining multiple strength‐of‐evidence aspects as in vigiRank significantly outperformed disproportionality analysis alone in real‐world pharmacovigilance signal detection, for VigiBase.