Drug safety and pharmacovigilance

Causality: Known by Three Distinct Names

All about ICSR processing
March 28, 2025 Bala 6 min read 4 Comments
Table of Contents

    This blog covers:

    1. Various Names for Causality in Case Processing
    2. Definitions and Meanings of Each Term
    3. The Assessment Process for Identifying and Deriving Causality

    Introduction

    Causality is a well-known concept, and in pharmacovigilance, its assessment is fundamental—case processing simply cannot exist without it.

    However, within the pharmacovigilance domain, causality is often referred to using three distinct terms. If you’re experienced in the field, you’ve likely come across them, but for beginners, these variations might be unfamiliar.

    This blog explores these different terms, their meanings, and how to differentiate between them in case processing.

    Causality: In Context of Case Processing

    In real-world case processing, causality is typically assessed and referred to using three different terms:

    1. Reported Causality
    2. Determined Causality
    3. Overall Case Causality

    These variations play a crucial role in evaluating the relationship between a drug and an adverse event.

    📢 Recommendation: Before going in deeper in to this check out this recommendation as explains category and criteria of causality assessment in pharmacovigilance.

    Definitions

    Below are the precise definitions essential for understanding causality in case processing.

    Reported Causality

    Reported causality refers to the causality assessment provided in the report itself. In other words, it is derived directly from the information given by the reporter, indicating the relationship between the drug and the adverse event.

    However, causality is not always explicitly stated in reports. In such cases, it must be inferred based on the available details, and one of the following classifications can be assigned:

    1. Related
    2. Unrelated
    3. Unknown, &
    4. Not Reported

    Responsibilities: The case processing associate is solely responsible for evaluating and assigning causality in the database.

    ✍️ Note: Reported causality does not always have to be determined by a healthcare professional (HCP).

    “In pharmacovigilance, understanding causality isn’t just about classification—it’s about ensuring patient safety through precise assessment and informed decision-making.”

    Example:

    Here’s an example of reported causality in a pharmacovigilance case file:

    The patient experienced severe headaches and nausea after taking the medication. According to the treating physician, these adverse events were likely related to the drug administration.

    In this case, the report explicitly states the relationship between the drug and the adverse effects, making it a clear instance of reported causality.

    Determined Causality

    As the name suggests, determined causality is derived based on safety documents and a thorough analysis of the case scenario, leading to a clear medical conclusion.

    Responsibility: The Medical Reviewer is the final decision-maker responsible for evaluating and determining causality.

    ✍️ Note: Regardless of what the initial report states about causality, the final assessment must be carefully analyzed and concluded by medical professionals.

    What Defines Determined Causality?

    1. The report is not always provided by a healthcare professional (HCP).
    2. Even if an HCP is the reporter, they may not always be a final conclusion.
    3. Consumers generally lack the analytical expertise to accurately assess causality.
    4. HCPs acting as reporters are not necessarily medics at all times.
    📢 Recommendations: Check our receooomendations that explains the roles and responsibilities of medical reviewer and explaining what are spontaneous reports.

    Overall Case Causality

    Overall case causality represents the final causality assessment for the entire case, regardless of the number of events experienced by the patient. It reflects the overall weight of causality, taking into account all reported and determined causalities assigned to individual events.

    In most cases, the database automatically derives the overall causality based on the reported and determined causality assigned to each event.

    This causality always by approach of worst-case scenario of the case, ensuring the case’s suspected classification.

    Why is Overall Case Causality Important?

    1. Ensures a comprehensive assessment of the case.
    2. Helps in distinguishing suspected vs. non-suspected cases, facilitating expediting submission.

    Worst-Case Scenario: Overview

    The worst-case scenario in causality assessment is determined based on several factors, including:

    1. Number of events in the case
    2. Seriousness of the case
    3. Variations in causality assessments across different events
    4. Ratio of serious to non-serious events within the case

    Key Differences

    1. Reported Causality – The causality assessment as stated by the reporter in the case report.
    2. Determined Causality – The internally evaluated assessment made after thorough medical review.
    3. Overall Case Causality – The final, comprehensive conclusion considering all events and aspects of the case.

    Key Takeaways

    In spontaneous reports, if causality is not reported or unknown, it defaults to “related” as per guidelines, making it a suspected case.

    The reporter does not always have to be an HCP for causality to be considered.

    Only medical professionals (Medics) are responsible for deriving determined causality.

    Overall case causality plays a crucial role in assessing the case’s overall impact and significance.

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    Conclusion

    We hope this blog has provided you with valuable insights! For beginners, these concepts may seem complex, but we have aimed to explain them as simply as possible.

    Since causality is a critical aspect of pharmacovigilance case processing, understanding these differences is essential.

    If you found this content helpful or think we missed anything, feel free to drop a comment below. We welcome your feedback, suggestions, and constructive criticism.

    Keep sharing and spreading knowledge!

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    4 Comments

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