The evolving role of disproportionality analysis in pharmacovigilance

ABSTRACT

Introduction

From 2009 to 2015, the IMI PROTECT conducted rigorous studies addressing questions about optimal implementation and significance of disproportionality analyses, leading to the development of Good Signal Detection Practices. The ensuing period witnessed the independent exploration of research paths proposed by IMI PROTECT, accumulating valuable experience and insights that have yet to be seamlessly integrated.

Areas covered

This state-of-the-art review integrates IMI PROTECT recommendations with recent acquisitions and evolving challenges. It deals with defining the object of study, disproportionality methods, subgrouping, masking, drug-drug interaction, duplication, expectedness, the debated use of disproportionality results as risk measures, integration with other types of data.

Expert opinion

Despite the ongoing skepticism regarding the usefulness of disproportionality analyses and individual case safety reports, their ability to timely detect safety signals regarding rare and unpredictable adverse reactions remains unparalleled. Moreover, recent exploration into their potential for characterizing safety signals revealed valuable insights concerning potential risk factors and the patient’s perspective. To fully realize their potential beyond hypothesis generation and achieve a comprehensive evidence synthesis with other kinds of data and studies, each with their unique limitations and contributions, we need to investigate methods for more transparently communicating disproportionality results and mapping and addressing pharmacovigilance biases.

KEYWORDS:

• Disproportionality analysis
• drug safety
• good signal detection practices
• individual case safety reports
• pharmacovigilance

Article highlights

• In 2016, IMI PROTECT published recommendations and future research directions for 11 key aspects in disproportionality analyses used in signal detection, which we reviewed in light of the latest advancements.

• Disproportionality analysis remains irreplaceable for quickly generating hypotheses regarding rare, unpredictable adverse drug reactions, but we can only achieve its full potential if we manage to better integrate it into the wider pharmacovigilance landscape.

• Future research should explore how to integrate disproportionality results with other observational and experimental evidence, expand its use to characterize safety signals, adapt causal inference tools to address its specific biases, ensure transparency, proper communication, and understanding of DPA findings.

Acknowledgments

We thank Eric Hung for help in the development of the manuscript.

Declaration of interest

MH has been a full-time employee of, and owns stock/stock options in, pharmaceutical companies that may manufacture/market drugs mentioned in this paper. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those disclosed.

Reviewer disclosures

Peer reviewers in this manuscript have no relevant financial or other relationships to disclose.

Author contributions

MF designed the study. MF, ER, EP, MH contributed to writing various sections of the initial manuscript draft, which were assembled and made homogeneous by MF. Subsequently, MF, ER, EP, MH reviewed the entire paper for critical intellectual content and endorsed the final version.

Notes

1. different from ‘external’ comparison (positive/negative controls to test the DPA performance) and one-on-one drug comparison (questionably restricting the population to two drugs to highlight differences between them).

Additional information

Funding

This paper was not funded.