ArticleDrug safety2015
Causal assessment of pharmaceutical treatments: why standards of evidence should not be the same for benefits and harms?
Article in Drug safety, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
4 citing papers in PubMed.
- Enhancing Safety Evaluations: A Comprehensive Framework for Evidence-Based Safety Assessment Using the Bradford Hill Criteria.Therapeutic innovation & regulatory science · 2026Article
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Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
It is increasingly acknowledged both among epidemiologists and regulators that the assessment of pharmaceutical harm requires specific methodological approaches that cannot simply duplicate those developed for testing efficacy. However, this intuition lacks sound epistemic bases and delivers ad hoc advice. This paper explains why the same methods of scientific inference do not fare equally well for efficacy and safety assessment by tracing them back to their epistemic foundations. To illustrate this, Cartwright's distinction into clinching and vouching methods is adopted and a series of reasons is provided for preferring the latter to the former: (1) the need to take into account all available knowledge and integrate it with incoming data; (2) the awareness that a latent unknown risk may always change the safety profile of a given drug (precautionary principle); (3) cumulative learning over time; (4) requirement of probabilistic causal assessment to allow decision under uncertainty; (5) impartiality; and (6) limited and local information provided by randomised controlled trials. Subsequently, the clinchers/vouchers distinction is applied to a case study concerning the debated causal association between paracetamol and asthma. This study illustrates the tension between implicit epistemologies adopted in evaluating evidence and causality; furthermore, it also shows that discounting causal evidence may be a result of unacknowledged low priors or lack of valid alternative options. We conclude with a presentation of the changing landscape in pharmacology and the trend towards an increased use of Bayesian tools for assessment of harms.
Indexed as
Identifiers
25519721What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.