Adverse drug reaction causality assessment Presented by Sirinoot Palapinyo, RPh, PharmD.

1. Adverse Drug Reaction
Causality Assessment
Sirinoot Palapinyo, RPh
February,2015

2. Outline
• Introduction
• Method used for causality assessment
• Algorithms

3. Introduction

4. Steps of
Monitoring
• Adverse events identification
• Causality assessment
• Management
• Documentation
• Report to pharmacovigilance centre/regulatory
authority

5. A
Assessment
• Causality assessment
probability
an observed adverse event
• Adverse events with high causal association (probable
and certain) with the drug are likely to recur
• An important component of the evaluation of the
benefit/harm profiles of drugs
• Thus, providing information on this causal link may be
useful in preventing future recurrences.
The use of the WHO-UMC system for standardised case causality assessment.
[Last accessed on 2015 Feb 8]. Available from:
graphics/4409.pdf

6. Methods used for
Causality Assessment
- Taofikat B. Agbabiaka, J. Savovi´c and Edzard, E. Methods for causality assessment of
adverse drug reactions: A systematic review. Drug Safety 2008; 31 (1): 21-37
- Hutchinson TA, Dawid AP, Spiegelhalter DJ, et al. Computer- ized aids for probabilistic
assessment of drug safety: I. A spreadsheet program. Drug Inf J 1991; 25: 29-39
- Arimone Y, Miremont-Salamé G, Haramburu F, Molimard M, Moore N, Fourrier-
Réglat A, Bégaud B. Inter-expert agreement of seven criteria in causality assessment of
adverse drug reactions. Br J Clin Pharmacol. 2007c; 64(4):482–8.

7. Method Global Introspection Algorithms
Probabilistic or Bayesian
approaches
Details
Clinical judgment; an expert
panel considering all available
data relevant to a suspected
ADR
Sets of specific
questions with
associated scores for
calculating the
likelihood of a cause-
effect relationship
Probability for causality
calculated from prior
knowledge &
need the specific
findings in a case
Pros
• Most common approach:
major role in the
identification and rating of
potential ADRs
• More sensitivity
• More reliable and
reproducible
measurement (Least
inter- and intra-rater
contradiction)
• Simplicity
• Overcome the
numerous limitations
associated with expert
judgements &
algorithms The Bayesian
Adverse Reactions Diagnostic
Instrument (BARDI)
• Valid and internally
consistent assessment
Cons
• inter- and intra-rater
contradiction
• Subjectivity& Imprecision
• Poor reproducibility
because it is mainly based
on expert clinical
judgements
• No one universal
algorithm
• Scoring can be
arbitrary
• Responses to
questions can be
subjective
• Poor specificity
• Complex calculations
• Requires more time
and more expertise

8. Algorithms
for causality assessment

9. Algorithms for causality evaluation tools
• Early 17s: Principle of disease to drugs in
individual patients
• 1981: International meeting in Morges, Switzerland
concluded 9 important points in causality
assessment
Meyboom RH
IR.Causal or casual? The role of causality assessment in
pharmacovigilance.

10. Meyboom RH
IR.Causal or casual? The role of causality assessment in
pharmacovigilance.

11. Algorithms
More than thirty algorithms of causality evaluation
tools were developed
• General algorithms :
UMC
• Specific algorithms :
for International Organizations of Medical
Sciences/Roussel Uclaf Causality Assessment
Method (CIOMS/RUCAM)

12. General algorithms
• Karch and Lasagna algorithm (1977) : Three tables
• Begaud algorithm (1977) -> French criteria : Three-stage
process
• Jones algorithm (1979) : Yes-No series
• Kramer (1979) : 56 questions
• Naranjo’s algorithm (1981) : 10 questions
• WHO-UMC : Grades of certainty (Certain, Probable/Likely,
Possible, Unlikely)
• Thai algorithm

16. Begaud algorithm (1977) -> French
• Three-stage process
• Assessment of three chronological criteria
(challenge, dechallenge, and rechallenge)
• Assessment of clinical and biological findings
• Combination of chronological and
symptomatological assessments to obtain a 3-degree
global score (1: doubtful, 2: possible, 3: probable)

17. Jones algorithms
Jones JK. Adverse drug reactions in the community health
setting: approaches to recognizing, counseling, and reporting.
Clin Comm Health. 1982;5(2):58-
No score calculation

18. Naranjo’s algorithm
• Total score: Definite > 8; probable 5-8; possible 1-4; doubtful <0
• Modified Naranjo’s algorithm
Naranjo C.A., Busto U., Sellers E.M., Sandor P., I. Ruiz,
E.A., Roberts, et al.A method for estimating
the probability of adverse drug reactions.
Pharmacol. Ther., 30 (1981), pp. 239–245

19. • WHO-UMC

22. • Which algorithm is the best
• If I selected others such as Naranjo’s algorithm to
evaluate my patients, How can I report to WHO ?

23. Comparison of
algorithms

24. Algorithm characteristics
Algorithms Advantage Limitation
Karch &
Lasagna
No specific advantage in comparison to
others
• Reliability & validity not well
established
Begaud More specific than Jones algorithm
• Consume more time than others
Jones
Shorter and quicker to complete &
detect the least ADR ?
• Cannot identified actual cause
Kramer More specific than others
• Clinicians can disagree on the weighted
values, make subjective judgments for
some questions
• Unexpected ADR may not score well
Naranjo
Simple & brief
Type A ADR
• Dependability and validity not
confirmed in children
• Drug interaction
WHO-UMC
Mainly planned as convenient tool
for the assessment of individual case
reports
• Non probabilistic method and creates
extensive unpredictability in evaluation
• Hard to remember
Thai Type B ADR • Less acceptance (Vs modified Naranjo’s)

25. • 120 patients from 4 groups were chosen at random:
• Proven hypersensitivity to b-lactams(n=30)
• Without proven hypersensitivity to b-lactams(n=30)
• Proven hypersensitivity to NSAIDs
• Without proven hypersensitivity to NSAIDs

28. K=1
K=0.12

29. Conclusion
• Jones algorithm compared favourably with the
Naranjo algorithm in scoring drug hypersensitivity
reactions, it is a simpler algorithm to use
• The Begaud algorithm
the Jones algorithm, may be more specific with
better predictive values.

31. Khan, L.M., Al-Harthi, S.E., Osman, A.M.,
AbdulSattar, M.A., Ali, A.S., Dilemmas of the
causality assessment tools in the diagnosis of adverse
drug reactions, Saudi Pharmaceutical Journal (2015)

32. Evaluation terms
Definite
Highly
probable
Definite Definite Certain Certain
Probable Probable Probable Probable Probable Probable Probable
Possible Possible Possible Possible Possible Possible Possible
Conditional Doubful Remote Unlikely Doubful Unlikely Unlikely
Karch &
Lasagna
Begaud Jones Kramer Naranjo
WHO-
UMC
Thai

33. Specific algorithms
• CIOMS/RUCAM for DILI
• ALDEN score (
E

36. Evaluation of
• Points are summed and the total compared to this chart:
• 0 or lower: relationship with the drug excluded
• 1-2: unlikely
• 3-5: possible
• 6-8: probable
• >8: highly probable

37. Limitation of
• Complexity. Ambiguous instructions
• Mixed cases included into the cholestatic group
• Atypical time or
to onset
• Arbitrary risk factors: age ≥ 55y, alcohol, pregnant
• Unclear criteria for competing drug(s) Subjective
interpretation of the drug hepatotoxic

39. • Among 187 enrollees,
complete agreement was reached for 50 (27%) with the expert
opinion process and for 34 (19%) with a five-category RUCAM
scale (P = 0.08), and the two methods demonstrated a modest
correlation with each other (Spearman's r = 0.42, P = 0.0001)

40. Conclusion
• The structured
produced higher agreement rates and likelihood
scores than RUCAM
there was still considerable interobserver variability
in both.
• Accordingly, a more objective, reliable, and
reproducible means of assessing DILI causality is
still needed.

43. • CIOMS/RUCAM scale had better interobserver
reliability (reproducibility) than the NARANJO
scale.
• In the assessment routines for signal detection at
pharmacovigilance centres, the CIOMS/RUCAM
scale is the preferred tool for caus- ality assessment
in hepatotoxicity

44. AL
• ALDEN scores were strongly correlated with those
of the EuroSCAR case-control analysis for drugs
associated with EN (r = 0.90, P < 0.0001)
Clin Pharmacol Ther. 2010 Jul;88(1):60-8. doi: 10.1038/clpt.2009.252. Epub 2010 Apr 7.
ALDEN, an algorithm for assessment of drug causality in Stevens-Johnson Syndrome and toxic epidermal
necrolysis: comparison with case-control analysis.
Sassolas B
Louet H.

45. ALDEN scores

46. ALDEN scores

47. • Which algorithm is the best
• If I selected others such as Naranjo’s algorithm to
evaluate my patients, How can I report to WHO ?

48. Conclusion
• No standard algorithms
• Understand the limitations
• Types of ADRs
• Populations
• Gap of knowledge

49. Thank you