Risk Factor Considerations in Statistical Signal Detection: Using Subgroup Disproportionality to Uncover Risk Groups for Adverse Drug Reactions in VigiBase

Abstract

Introduction In the treatment of the individual patient, a vision is to achieve the best possible balance between benefit and harm. Such tailored therapy relies upon the identification and characterisation of risk factors for adverse drug reactions. Information relevant to risk factor considerations can be captured in adverse event reports and could be utilised in statistical signal detection. Objective The aim of this study was to explore whether statistical screening of a broad range of risk factors within a global database of adverse event reports could uncover signals of risk groups for adverse drug reactions. Methods Subgroup disproportionality analysis was applied to 15.4 million reports entered in VigiBase, the World Health Organization (WHO) global database of individual case safety reports, up to August 2017. Disproportionality analyses for drug-adverse event pairs were performed (1) in the full database and (2) across a range of subgroups defined by the following covariates: patient age, sex, body mass index, pregnancy, underlying condition, reporting country, and geographical region. Drug-adverse event pairs disproportionately over-reported in such subgroups, but not in the full database, and with a substantial difference between the two observed-to-expected ratios, were highlighted as statistical signals. These were further prioritised, through filtering and sorting, for clinical assessment, whereafter clinically relevant signals were communicated to the pharmacovigilance community and the public. Results Assessments were performed for 354 prioritised statistical signals, resulting in seven communicated signals describing previously unrecognised potential risk groups related to age (elderly), sex (male and female), body mass index (underweight and obese), and geographical region (Asia), all except one for already established adverse drug reactions. Important aspects considered in the assessments included an evaluation of the disproportionate over-reporting in the subgroup by reviewing alternative explanations and reporting patterns for similar drugs/adverse events/subgroups, and a search for plausible mechanisms to support the risk hypothesis. Conclusions This study reveals that it is possible to uncover signals of risk groups for adverse drug reactions through incorporation of broad risk factor screening into statistical signal detection in a global database of adverse event reports. Our findings suggest the potential to use such statistical methodologies for risk characterisation in subpopulations of concern.

Adverse Event Reporting with Immune Checkpoint Inhibitors in Older Patients: Age Subgroup Disproportionality Analysis in VigiBase

“…By using a novel subgroup disproportionality approach [ 16 ], this study found that patient age was not a risk factor for adverse event reporting with ICIs as compared to other antineoplastic drugs. In VigiBase, there were not signals of disproportionate reporting with ICIs specifically detected in older patients (age ≥65 years) and not present in the disproportionality analysis over the entire dataset (i.e., regardless of patient age and with the inclusion of safety reports missing information on patient age).…”

“…Disproportionality analysis is a valuable methodological approach well consolidated and extensively used in pharmacovigilance studies on databases of spontaneous reporting to characterize ICI toxicity [ 19 ]. Recently, Sandeberg et al [ 16 ], proposed subgroup disproportionality analyses to take into account the diversity that underlines safety reports of different patients, the confounding factors and the potential distortions of disproportionate measurements computed regardless of risk groups for ADRs. Indeed, subgroup disproportionality analysis benefits from both high sensitivity and precision over crude analyses in large databases [ 26 ].…”

“…Information recorded within each safety report comprises administrative features (reporting year, country of origin, type of reporter); patient characteristics (age, sex), reaction (onset and end date, outcome), and drug details (role in ADR onset as attributed by reporter—suspected, interacting, or concomitant -; indication, start and end dates). Lastly, when a safety report is identified by reporters as serious, it is mandatory to select the seriousness criterion as defined by the WHO-UMC (i.e., serious for causing or prolonging hospitalization, leading to death, representing a life-threatening condition, disabling/incapacitating, or determining other clinically relevant conditions) [ 16 ].…”

“…To date, pharmacovigilance studies with databases of spontaneous reporting focused on older patients treated with ICIs are lacking. Recently, subgroup disproportionality analysis was applied in VigiBase, the World Health Organization (WHO) global database of spontaneously reported suspected adverse drug reactions (ADRs), to characterize signals of disproportionate reporting in groups of patients at higher risk of ADRs, including age subgroups [ 16 ].…”

Pre-Existing Cardiovascular Conditions as Clinical Predictors of Myocarditis Reporting with Immune Checkpoint Inhibitors: A VigiBase Study

“…Recent research published by the WHO-Uppsala Monitoring Centre in fact supports our definition of the independent variable using concomitant drugs to infer a patient’s underlying diseases. The researchers considered concomitant diseases among the patient risk factors for ADRs reported in VigiBase, defined subgroups of such diseases using concomitant drug indications as proxies, and proposed subgroup disproportionality analysis as a statistical methodology for risk characterization in the ensuing patient subpopulations for ADR onset [ 34 ].…”