Causality Classification in Pharmacovigilance: Explained

This blog features:

1. List of categories with WHO-UMC
2. Characteristics of each classification
3. Key takeaways

Introduction

Every pharmacovigilance professional should understand the key parameters used to describe and assess causality in adverse drug reactions (ADRs). There are several methods available for causality assessment in pharmacovigilance, with the WHO-UMC classification being one of the most widely used. This blog explores the characteristics and criteria involved in these classifications.

Accurate assessment of Causality

Once an ADR is identified and appropriately coded, healthcare professionals are responsible for documenting all relevant information. This includes patient demographics, medical history, concomitant medications, and a detailed description of the adverse event. Such comprehensive data is essential for an accurate evaluation of both causality and severity.

It is important to note that causality assessment does not definitively prove or disprove a relationship between a drug and an adverse event. Instead, it provides a structured approach to evaluate the likelihood of an association.

Causality assessment is a systematic process used to determine how strongly an adverse event is related to a suspected drug. Below are the key criteria commonly applied in pharmacovigilance practice.

Basic Criteria for Causality Assessment

• Identification of the suspected drug
• Pharmacological properties and known ADR profile
• Temporal relationship between drug intake and adverse event
• Biological and medical plausibility
• Evaluation and exclusion of alternative causes
• Comprehensive analysis of available data, including missing information
• Strength of association between the drug and the event

Causality Classification

To assess the likelihood that an adverse reaction is related to a suspected medicine, the WHO-UMC system provides standardized criteria. These criteria help determine the strength of association between a drug and an adverse event.

Common Classifications

• Certain (Definitely related)
• Probable/Likely
• Possible
• Unlikely
• Unassessable/Unclassifiable

Alternatively, some organizations simplify this into:

• Related
• Not Related

Each organization may choose to adopt a specific system or a combination based on internal requirements.

Key Takeaways for Each Classification

Each company should decide which system they will use or a combination of both

Certain:

• Good timing, no other cause, withdrawal response plausible, rechallenge, “definitive”
• Clinical event, lab test abnormality with plausible time relationship to medicine intake
• Cannot be explained by concurrent disease or other medicines/ chemicals
• Response to dechallenge – positive?
• Event must be definitive pharmacologically/immunologically
• Positive rechallenge (if performed).

Probable/Likely:

• Good timing, other cause unlikely, withdrawal
• Clinical event, lab test abnormality with reasonable time relationship to medicine intake
• Unlikely to be explained by concurrent disease, medicines/chemicals
• Clinically reasonable response to withdrawal (Dechallenge)
• Rechallenge not required

Possible :

• Good timing, other causes possible
• Clinical event, lab test abnormality with reasonable time relationship to medicine intake
• Could also be explained by concurrent disease or other medicines or chemicals
• Information on drug withdrawal may be lacking or unclear

Unlikely:

• Poor timing, other causes more likely
• Clinical event, lab test with improbable time relationship to medicine intake
• Other medicines, chemicals and underlying disease provide plausible explanations

Inaccessible/Unclassifiable:

• Insufficient or contradictory information
• Insufficient/contradictory evidence, which cannot be supplemented or verified

Conditional/Unclassified:

• More data is essential for proper assessment or additional data are under examination. In most cases there is some level of uncertainty as to whether the drug is directly responsible for the reaction. Many of the questions above may remain unanswered or may be contradictory; however, this should not dissuade you from reporting the reaction to the national pharmacovigilance centre of the PBSL. A well-documented report, which includes information about all the above-mentioned questions, can provide us with the first signal of a previously unknown problem.

Important Note

Causality assessment often involves a degree of uncertainty. Even when information is incomplete or conflicting, adverse events should still be reported to the relevant pharmacovigilance authority. Well-documented reports can contribute to identifying new safety signals and improving patient safety.

Conclusion

Causality assessment is a fundamental component of pharmacovigilance, enabling professionals to systematically evaluate the relationship between a drug and an adverse event. While it may not provide absolute certainty, it offers a structured and scientific approach to support decision-making and ensure patient safety.

Understanding the key classifications and applying them consistently allows case processors and healthcare professionals to make informed judgments. Despite the challenges and occasional uncertainty in available data, every well-documented report contributes to the broader safety database and helps in early signal detection.

Ultimately, accurate causality assessment is not just a regulatory requirement—it is a responsibility that plays a critical role in safeguarding public health.

If you notice any gaps or missing information, we encourage you to write to us and share your valuable suggestions.