1. Name: Chetan G. Kumbhar
Roll no: 22
Class: Final year
Topic:
Guided By
Mrs Reshma V. Pawar
Associate Professor,
SPM’s College of Pharmacy, Akluj
Methods in causality assessment
2. CAUSALITY ASSESSMENT
Definition : Causality assessment can be defined as the assessment of
relationship between the treatment with any drug treatment and incidence
of an adverse reacion or event.
Methods in causality assessment are borad classified into three
categories as follows:
I. Expert judgment/global introspection
II. Algorithms
III.Probabilistic methods (Bayesian approaches)
3. Objectives
1)Setup relationship between the medicine and events.
2)Detection of signal (“a possible causal corelation between the drug and an
adverse event, the relationship being either incompletely documented
previously or unknown”.)
3)Better evaluation of the toxic or beneficial effects of drugs.
4)Plays an important part for evaluating ADR reports for regulatory purposes and
in early warning systems.
4. I. Expert Judgment/Global Introspection
Expert judgments are individual evaluation on the basis of previous knowledge
and experience in the field. These judgments are made without using any
standardized tool for getting the conclusions regarding causality.
There are two methods based on expert opinion or global introspection:
1. Swedish method by Wilholm et al.
2. World Health Organization (WHO)
5. II. Algorithms
Algorithms are sets of specific questions with associated scores for calculating
the likelihood of a cause-effect relationship. It consists of a problem-specific
flow chart with step-by-step instruction on how to arrive at an answer.
Important Algorithmic Methods are:
1. Dangaumou’s french method
2. Kramer et al. Method
3. Naranjo et al. Method (Naranjo scale)
4. Balanced assessment method (Lagier et al.)
5. Summary time plot (Castle et al.)
6. Ciba geigy method (Venulet et al.)
7. Roussel Uclaf causality assessment method (RUCAM)
8. Maria and Victorino (M and V) scale
9. Drug Interaction Probability Scale (DIPS)
6. III. Probabilistic Method ( Bayesian Approaches)
This method is used in case of specific findings while transforming the
estimate of prior probability into posterior probability of drug causation.
With the help of epidemiological information, prior probability can be
calculated and posterior probability combines with the previous
information along with the evidence of the particular case to find out an
approximate of causation.
