Methods in Causality assessment: BP805T Pharmacovigilance Notes
Many researchers developed various methods of causality assessment of ADRs by using different criteria like chronological relationship between the administration of the drug and the occurrence of the ADR, screening for non drug related causes, confirmation of the reaction by in vivo or in vitro tests, and previous information on similar events attributed to the suspect drug or to its therapeutic class, etc
Three broad categories of various methods of causality assessment:
1. Expert judgment/global introspection
3. Probabilistic methods (Bayesian approaches)
Expert judgment/global introspection
Expert judgment/global introspection Expert judgments are individual assessments based on previous knowledge and experience in the field using no standardized tool to arrive at conclusions regarding causality.
Expert judgment/global introspection Swedish method by Wilholm Evaluates the causal relationship by considering seven different factors:
(i) the temporal sequence (ii) previous information on the drug (iii) dose relationship (iv) response pattern to drug (v) rechallenge (vi) alternative etiological candidates and (vii) concomitant drugs Events are classified as probable or possible and non- assessable or unlikely‟.
A limitation of this method is the small number of categories into which causality can be placed, as there may be an overlap and ADRs could be wrongly evaluated
Algorithms are sets of specific questions with associated scores for calculating the likelihood of a cause-effect relationship.
An algorithm is a problem-specific flow chart with step- by-step instruction on how to arrive at an answer. It is a clinical instrument in the form of a questionnaire that gives detailed operational criteria for ranking the probability of causation when an ADR is suspected. Algorithms give structured and standardized methods of assessment in a systematic approach to identifying ADRs based on parameters such as time to onset of the ADR or temporal sequence, previous drug/adverse reaction history and dechallenge and rechallenge.
Individual cases are approached systematically, resulting in a high degree of consistency and reproducibility. Clinical judgment is, however, required at various stages to arrive at a conclusion. Currently, there are many algorithmic methods of causality assessment but no single algorithm is accepted as the gold standard, because of the shortcomings and disagreements that exist between them
1. Dangaumou’s French method
Scores are grouped into likely, possible and dubious. The advantage of this method is that it allows certain drugs taken at the same time with the suspect drug to be excluded, because each drug is imputed separately. However, this method requires more time than most other algorithms.
2. Kramer et al. method
This algorithm applies to a single clinical manifestation occurring after administration of a single suspect drug. In cases where multiple drugs are involved, each is assessed separately. One of the advantages of this algorithm is its transparency. However, certain levels of expertise, experience and time are required to use this method effectively.
3. Balanced assessment method (Lagier et al)
It evaluates case reports on a series of visual analogue scales (VAS), according to the likelihood that each criterion is fulfilled. Its advantage is that it considers the possibility of an alternative to causation for each of the factors and not just as a separate factor. Although each case is assessed by two independent assessors, the evaluation still depends, to a large extent, on the level of assessor‟s knowledge. An evaluator needs to be an expert in the particular area to make reliable evaluations.
Probabilistic methods (Bayesian approaches)
Bayesian approaches use specific findings in a case to transform the prior estimate of probability into a posterior estimate of probability of drug causation. The prior probability is calculated from epidemiological information and the posterior probability combines this background information with the evidence in the individual case to come up with an estimate of causation.
1. Australian method
• It is one of the first probabilistic methods used.
• Conclusions are drawn from internal evidence, such as timing, and laboratory information from case reports.
• Previous knowledge on the suspect-drug profile is deliberately excluded in the assessment.
2. Bayesian Adverse Reactions Diagnostic Instrument (BARDI):
• Developed to overcome the numerous limitations associated with expert judgments and algorithms.
• This BARDI is used to calculate the odds in favor of a particular drug causing an adverse event compared with an alternative cause. These odds are referred to as the posterior odds. The posterior odds factor is calculated by considering six assessment subsets: one deals with background epidemiologic or clinical trials information (the prior odds) and the other five deal with case specific information (the likelihood ratios).
The Bayesian approach can be implemented as a spreadsheet programme on either paper or computer. • It calculates and provides instant numerical and graphical feedback as soon as new pieces of evidence of the suspected ADR are evaluated
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