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Causality Assessment of Suspected Adverse Reactions

Term Description Comments
CERTAIN A clinical event, including laboratory test abnormality, occurring in a plausible time relationship to drug administration, and which cannot be explained by concurrent disease or other drugs or chemicals. The response to withdrawal of the drug (dechallenge) should be clinically plausible. The event must be definitive pharmacologically or phenomenologically, using a satisfactory rechallenge procedure if necessary. It is recognized that this stringent definition will lead to very few reports meeting the criteria, but this is useful because of the special value of such reports. It is considered that time relationships between drug administration and the onset and course of the adverse event are important in causality analysis. So also is the consideration of confounding features, but due weight must placed on the known pharmacological and other characteristics of the drug product being considered. Sometimes the clinical phenomena described will also be sufficiently specific to allow a confident causality assessment in the absence of confounding features and with appropriate time relationships, e.g. penicillin anaphylaxis.
PROBABLE/ LIKELY A clinical event, including laboratory test abnormality, with a reasonable time sequence to administration of the drug, unlikely to be attributed to concurrent disease or other drugs or chemicals, and which follows a clinically reasonable response on withdrawal (dechallenge). Rechallenge information is not required to fulfil this definition. This definition has less stringent wording than for "certain" and does not necessitate prior knowledge of drug characteristics or clinical adverse reaction phenomena. As stated no rechallenge information is needed, but confounding drug administration underlying disease must be absent.
POSSIBLE A clinical event, including laboratory test abnormality, with a reasonable time sequence to administration of the drug, but which could also be explained by concurrent disease or other drugs or chemicals. Information on drug withdrawal may be lacking or unclear. This is the definition to be used when drug causality is one of other possible causes for the described clinical event.
UNLIKELY A clinical event, including laboratory test abnormality, with a temporal relationship to drug administration which makes a causal relationship improbable, and in which other drugs, chemicals or underlying disease provide plausible explanations. This definition is intended to be used when the exclusion of drug causality of a clinical event seems most plausible.
CONDITIONAL/ UNCLASSIFIED A clinical event, including laboratory test abnormality, reported as an adverse reaction, about which more data is essential for a proper assessment or the additional data are under examination.
UNASSESSIBLE/ UNCLASSIFIABLE A report suggesting an adverse reaction which cannot be judged because information is insufficient or contradictory, and which cannot be supplemented or verified.

Causality Assessment - comments

Various causality terms are in use but the above are used most widely. Some people, however, do not use all the terms. For instance, many do not believe that a "certain" classification is possible for a single report and others make no distinction between "probable" and "possible". These definitions are however acceptable to Programme members who do use the terms. Where only "possible" or "unlikely" are used to describe reactions it must be understood that "possible" include those reactions which are called by others "probable" and "certain", as well as "possible".

Whilst "conditional/unclassified" and "unassessible/unclassifiable" are not causality terms, they describe the status of adverse reaction reports and therefore allow for practical communication about ADR issues.

WHO-UMC causality assessment system

For a fuller explanation of the use of the WHO-UMC system for standardised case causality assessment, please download this Adobe Acrobat document (125KB).

If you have any comments on causality or relationships in pharmacovigilance, please contact Dr Ronald Meyboom.