1. 8. Causality assessment:
scales and methods
Multi-partner training package on active TB drug safety monitoring and management (aDSM)
July 2016

2. Objectives of the presentation By the end of this presentation, the participant is expected to be able to:
describe the main principles of causality assessment
identify the different levels of certainty when attributing an event to a suspected exposure

3. Causality assessment (1)
one of the main reasons we collect aDSM data
Programme indicators
Causality assessment
Signal detection
Drug-safety profiles

4. Causality assessment (2)
an integral part of clinical management
Evaluating the likelihood that a TB medicine was the causative agent of an observed adverse reaction forms part of clinical evaluation.
While the details of the systematic method of conducting causality assessment may not be familiar to the practitioner, the overall approach is not too different from the clinical practice followed when evaluating any patient on treatment.

5. Causality assessment (3)
attribution
The attribution (relationship or causality or drug related assessment) must be made
A physician or any other health care professional who has the right expertise describes the relationship between the adverse event and an exposure
This determination must be recorded both in the medical record as well as in the case report form
For aDSM, causality assessment should be made primarily at the country level and by consulting the relevant data sources close to where the event occurred

6. Causality assessment (4)
Is there a convincing relationship between the medicine and the event ?
Did the medicine actually cause the event ? OR
Other TB medicines ?
Medicines for other diseases ?
Effect of the TB disease itself or co-morbidities?

7. Causality assessment (5)
reaction versus event
Adverse drug reactions (ADR): a response to a medicine which is noxious and unintended, and which occurs at doses normally used in humans
Adverse events (AE): Any untoward medical occurrence that may present during treatment with a pharmaceutical product, but which does not necessarily have a causal relationship with this treatment

8. Causality assessment (6) main things to look out for
Is the time to onset of the event compatible with the suspected cause (plausible time-frame) ?
Did the event occur after the start of some other medicine or new illness?
Is the event plausible given what is known about the drug?
Is there any other possible cause for the event?
What is the response to withdrawal of the medicine
(dechallenge)?
What is the response to rechallenge, if applicable?

9. Causality assessment (7) key data elements for causality assessment
Medical history (incl. concomitant disease)
Other risk factors (social factors, alcohol use, substance abuse, etc.)
Details of drugs taken : names, doses, routes
Start and stop dates and indications for use
Description of adverse event, including clinical description, laboratory results, and date of onset / end
Evolution of event, severity, seriousness, outcome

10. Causality assessment (8) classification of level of relationship
Time to event plausible?
Other explanation excluded?
Recovery after withdrawal?
Recurrence after rechallenge?
notes
Certain
Yes
Rechallenge not needed in case of an anaphylactic reaction
Probable
No or ?
Possible ?
Unlikely No
Suggestive if event resolves despite continued exposure

11. Causality assessment (9) inference on the grade of the relationship
Definite – Clearly caused by the exposure
Probable – Likely to be related to the exposure
Possible – May be related to the exposure
Unlikely – Doubtfully related to the exposure
Unrelated – Clearly not related to the exposure

12. Causality assessment (10) inference on the grade of the relationship
Category
Definition
Definite / certain
There is clear evidence to suggest a causal relationship and other possible contributing factors can be ruled out.
Probable
There is evidence to suggest a likely causal relationship and the influence of other factors is unlikely.
Possible
There is some evidence to suggest a causal relationship (e.g. because the event occurs within a reasonable time after administration of the trial medication). However, the influence of other factors may have contributed to the event (e.g. the patient’s clinical condition, other concomitant treatments).
Unlikely
There is little evidence to suggest there is a causal relationship (e.g. the event did not occur within a reasonable time after administration of the study regimen). There is another reasonable explanation for the event (e.g. the patient’s clinical condition, other concomitant treatment).
Not related
There is no evidence of any causal relationship .
Unclassifiable
There is insufficient information about the ADRs to allow for an assessment of causality.

13. Causality assessment (11) Naranjo ADR probability scale (items and score)
Source: Naranjo CA et al. A method for estimating the probability of adverse drug reactions. Clin Pharmacol Ther 1981; 30:

14. Causality assessment (12) WHO-UMC system
Practical tool for the assessment of case reports
Combined assessment taking into account
clinical-pharmacological aspects of the case history
the quality of the documentation
Other criteria such as previous knowledge and statistical chance play a less prominent role as to facilitate detection of unknown and unexpected adverse drug reactions
Source:

15. Causality assessment (13) approaches to test hypotheses
Method
Principles
+ / -
Reproducibility
Expert opinion
Based on judgment of individual experts
Subjective
Low
Algorithms
Follows a decision tree defined by experts / pharmacology
More standardized than expert opinion
Low (subjective)
Probability assessment
Bayesian approach
Need special skills; numeric data
Considered «gold standard»
Adapted from R Benkirane (WHO-CC Morocco; 2014)

16. Causality assessment (14)
who does the causality assessment ?

17. Conclusion
An attempt to attribute an event to a cause is a basic principle of monitoring and clinical management in aDSM
Attributing a relationship requires a systematic process and is one of the main reasons why data are collected in aDSM. The exercise is done by experts who are competent in therapeutics and toxicity
The causality assessment once done attributes a level of certainty between the event and the exposure, ranging from certain to unrelated