Assessment of causality for individual patients

2. Overall association between a drug and an adverse event Assessment of causality for individual patients

3. Causality Assessment • Is an assessment in an individual case that the suspected drug caused the adverse event.

4. Adverse Event Adverse Reaction

5. Adverse Event • 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 (WHO 1991).

6. Adverse Drug Reaction • A response to a drug which is • noxious and unintended and which • occur at doses normally used in • man for prophylaxis, diagnosis, or • therapy of disease or modification • of physiological function

7. Aims of Causality Assessment • To assess a possible relationship between a drug and an event • To decide the nature of further inquiries • Classification of AEs • To aid conducting cluster analysis and writing PSURs • To satisfy regulatory requirements • To aid signal generation and assessment

8. Available Methods forCausality Assessment • Global introspection • Informal guides • Structured algorithms and decision trees • Bayesian probablistic • Expert systems

9. Global introspection Poor reproducibility, important factors may be missed • Informal guides Improve reproducibility without adversely affecting global medical evaluation • Structured algorithms Improve reproducibility at the expense of global medical evaluation

10. Characteristics for Judging Methods for Causality Assessment • Repeatability • Explicitness and Explanatory capability - the user should state the degree of uncertainty abouteach element of the information and be able to explain how he reached his conclusion • Completeness - incorporate all data • Biological balancing • No priori constraints on the effects of any factor

11. When to Assess Causality • Physician/Investigator • Receipt • When most of the information is available • Signal generation and evaluation • Periodic Review

12. Some Factors Considered in the Assessment of Causality • Temporal relationship • Pharmacological plausibility • Recognised association with product or class • Underlying illness/concurrent conditions • Other medications • De-challenge • Re-challenge • Dose relationship • Quality of the information

13. WHO Definitions 1991 • 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.

14. WHO Definitions 1991 • 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.

15. WHO Definitions 1991 • 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.

16. WHO Definitions 1991 • 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.

17. WHO Definitions 1991 • 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.

18. WHO Definitions 1991 • Unassessable/unclassifiable • A report suggesting an adverse reaction which cannot be judged because information is insufficient or contradictory, and which cannot be supplemented or verified

19. 1. Are there previous conclusive reports on this reaction? Yes (+1) No (0) Do not know or not done (0) 2. Did the adverse event appear after the suspected drug was given? Yes (+2) No (-1) Do not know or not done (0) 3. Did the adverse reaction improve when the drug was discontinued or a specific antagonist was given? Yes (+1) No (0) Do not know or not done (0) 4. Did the adverse reaction appear when the drug was re-administered? Yes (+2) No (-2) Do not know or not done (0) 5. Are there alternative causes that could have caused the reaction? Yes (-1) No (+2) Do not know or not done (0) 6. Did the reaction reappear when a placebo was given? Yes (-1) No (+1) Do not know or not done (0) 7. Was the drug detected in any body fluid in toxic concentrations? Yes (+1) No (0) Do not know or not done (0) 8. Was the reaction more severe when the dose was increased, or less severe when the dose was decreased? Yes (+1) No (0) Do not know or not done (0) 9. Did the patient have a similar reaction to the same or similar drugs in any previous exposure? Yes (+1) No (0) Do not know or not done (0) 10. Was the adverse event confirmed by any objective evidence? Yes (+1) No (0) Do not know or not done (0) Naranjo Probability Scale

20. Naranjo Probability Scale Score Category 9+ Highly probable 5- 8 Probable 1- 4 Possible 0- Doubtful

21. Common Problems • When there is a reasonable temporal relationship for a “possible” but another cause e.g. concurrent illness is more likely • patient with hx of angina develops chest pain after finestaride • When there is a reasonable temporal relationship and the event is known to occur with product but but insufficient information regarding other factors • weight gain with an atypical antipsychotic

22. Causal Association in Pharmacovigilance and Pharmacoepidemiology: Thoughts on the Application of the Austin Bradford-Hill Criteria. Shakir SAW and Layton D. Drug Safety. 2002;25(6):467-471

23. Austin Bradford Hill Criteria • Strength • Consistency • Specificity • Temporality • Biologic gradient • Plausibility • Coherence • Experimental evidence • Analogy

24. Strength • Strong associations are more likely to be causal than weak associations • Weak associations are more likely to be explained by unrelated biases • Examples • smoking and lung cancer • deep vein thrombosis following third generation oral contraceptives

25. Consistency • Repeated observations of an association in different populations under different circumstances • lack of consistency does not rule out a causal association • some effects may be produced by their causes only in certain circumstances

26. Specificity • A cause leads to a single effect, not multiple effects • Although the concept of specificity is sometimes helpful, it can be misleading

27. Temporality • The necessity that cause precedes effect in time

28. Temporality • Most adverse drug reactions are “type A” ADRs • look for temporal patterns • development of hazard functions curves

29. B Wiholm

30. First dose effects B Wiholm

31. Fibrotic reactions e.g. Liver fibrosis from methotrexate B Wiholm

32. B Wiholm

33. Biologic gradient • Dose-response curve • smoking

34. Dose relationships in Drug Safety • NSAIDs and GI bleeding • Inhaled corticosteroids and growth • retardation in children

35. Plausibility • Biological plausibility of the hypothesis • an important concern which may be difficult to judge

36. Plausibility • Easy • NSAIDs and GI bleeding • Bupropion (Zyban) and convulsions • Difficult • Aspirin and Rye’s syndrome in children • Requires further study • higher incidence of serious skin reactions with lamotrigine in children

37. Coherence • Coherence implies that a cause and effect interpretation for an association does not conflict with what is known of the natural history and pathology of the disease. • Example • histopathological effects of smoking on bronchial epithelium • Absence or conflicting information with regard to coherence should not be taken as evidence against causal inference

38. Coherence • Possible increase in thromboembolic • events with Cox-2 inhibitors

39. Experimental evidence • Biological models • Animal experiments • Human experiments

40. Analogy • Inventive scientists can find analogies everywhere • Analogy provides a source of more elaborate hypotheses about association under study • Absence of analogy may only reflect lack of imagination or experience, not the falsity of the hypothesis

44. saad.shakir@dsru.org www.dsru.org