Biomaterial Database

A Bayesian approach to the interpretation of subgroup results in clinical trials. 1982

A Donner

Problems of interpretation often arise when patients who have been entered into a randomized clinical trial are post-stratified according to prognostic descriptors, and treatment comparisons performed within subgroups. In this paper a Bayesian approach to interpreting these comparisons is proposed, which takes into account the investigator's prior expectations concerning the relative magnitudes of treatment effects in different subgroups.

UI	MeSH Term	Description	Entries
D011336	Probability	The study of chance processes or the relative frequency characterizing a chance process.	Probabilities
D011379	Prognosis	A prediction of the probable outcome of a disease based on a individual's condition and the usual course of the disease as seen in similar situations.	Prognostic Factor,Prognostic Factors,Factor, Prognostic,Factors, Prognostic,Prognoses
D011897	Random Allocation	A process involving chance used in therapeutic trials or other research endeavor for allocating experimental subjects, human or animal, between treatment and control groups, or among treatment groups. It may also apply to experiments on inanimate objects.	Randomization,Allocation, Random
D002986	Clinical Trials as Topic	Works about pre-planned studies of the safety, efficacy, or optimum dosage schedule (if appropriate) of one or more diagnostic, therapeutic, or prophylactic drugs, devices, or techniques selected according to predetermined criteria of eligibility and observed for predefined evidence of favorable and unfavorable effects. This concept includes clinical trials conducted both in the U.S. and in other countries.	Clinical Trial as Topic
D006801	Humans	Members of the species Homo sapiens.	Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D001499	Bayes Theorem	A theorem in probability theory named for Thomas Bayes (1702-1761). In epidemiology, it is used to obtain the probability of disease in a group of people with some characteristic on the basis of the overall rate of that disease and of the likelihood of that characteristic in healthy and diseased individuals. The most familiar application is in clinical decision analysis where it is used for estimating the probability of a particular diagnosis given the appearance of some symptoms or test result.	Bayesian Analysis,Bayesian Estimation,Bayesian Forecast,Bayesian Method,Bayesian Prediction,Analysis, Bayesian,Bayesian Approach,Approach, Bayesian,Approachs, Bayesian,Bayesian Approachs,Estimation, Bayesian,Forecast, Bayesian,Method, Bayesian,Prediction, Bayesian,Theorem, Bayes
D013223	Statistics as Topic	Works about the science and art of collecting, summarizing, and analyzing data that are subject to random variation.	Area Analysis,Estimation Technics,Estimation Techniques,Indirect Estimation Technics,Indirect Estimation Techniques,Multiple Classification Analysis,Service Statistics,Statistical Study,Statistics, Service,Tables and Charts as Topic,Analyses, Area,Analyses, Multiple Classification,Area Analyses,Classification Analyses, Multiple,Classification Analysis, Multiple,Estimation Technic, Indirect,Estimation Technics, Indirect,Estimation Technique,Estimation Technique, Indirect,Estimation Techniques, Indirect,Indirect Estimation Technic,Indirect Estimation Technique,Multiple Classification Analyses,Statistical Studies,Studies, Statistical,Study, Statistical,Technic, Indirect Estimation,Technics, Estimation,Technics, Indirect Estimation,Technique, Estimation,Technique, Indirect Estimation,Techniques, Estimation,Techniques, Indirect Estimation