Currently, clinical trials tend to be individually funded and applicants must include a power calculation in their grant request.
However, conventional levels of statistical precision are unlikely to be obtainable prospectively if the trial is required to evaluate treatment of a rare disease.
This means that clinicians treating such diseases remain in ignorance and must form their judgments solely on the basis of (potentially biased) observational studies, experience, and anecdote.
Since some unbiased evidence is clearly better than none, this state of affairs should not continue.
However, conventional (frequentist) confidence limits are unlikely to exclude a null result, even when treatments differ substantially.
Bayesian methods utilise all available data to calculate probabilities that may be extrapolated directly to clinical practice.
Funding bodies should therefore fund a repertoire of small trials, which need have no predetermined end, alongside standard larger studies.
Mots-clés Pascal : Traitement, Homme, Essai thérapeutique contrôlé, Fréquence, Randomisation, Statistique, Probabilité, Ethique, Maladie, Royaume Uni, Europe
Mots-clés Pascal anglais : Treatment, Human, Controlled therapeutic trial, Frequency, Randomization, Statistics, Probability, Ethics, Disease, United Kingdom, Europe
Notice produite par :
Inist-CNRS - Institut de l'Information Scientifique et Technique
Cote : 96-0077581
Code Inist : 002B30A01. Création : 199608.