A Bayesian strategy for evaluating treatments applicable only to a subset of patients

If we wish to evaluate the efficacy of a proposed treatment applicable only to a subset of the patient population, then a comparison of the results of the proposed treatment with historical experience may be misleading if the applicability of the proposed treatment is itself of prognostic value. We...

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Bibliographic Details
Published in:Statistics in medicine 1997-08, Vol.16 (16), p.1803-1815
Main Author: Neely Atkinson, E.
Format: Article
Language:English
Subjects:
Antineoplastic Combined Chemotherapy Protocols - therapeutic use
Bayes Theorem
Biological and medical sciences
Carcinoma - drug therapy
Cisplatin - administration & dosage
Computerized, statistical medical data processing and models in biomedicine
Drug Evaluation - methods
Female
Genital Neoplasms, Female - drug therapy
Humans
Medical sciences
Medical statistics
Paclitaxel - administration & dosage
Pilot Projects
Prognosis
Randomized Controlled Trials as Topic - methods
Research Design
Selection Bias
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Summary:If we wish to evaluate the efficacy of a proposed treatment applicable only to a subset of the patient population, then a comparison of the results of the proposed treatment with historical experience may be misleading if the applicability of the proposed treatment is itself of prognostic value. We present a Bayesian strategy to estimate the response rate of patients eligible for the proposed treatment but who receive standard therapy; we can compare the results with the experimentally observed response rate of patients who receive the proposed therapy. I extend the approach to apply to time to event data that may be censored, such as time to disease progression. One can use the information obtained in this fashion to evaluate experimental designs for future trials of the proposed treatment. © 1997 John Wiley &Sons, Ltd.
ISSN:0277-6715
1097-0258
DOI:10.1002/(SICI)1097-0258(19970830)16:16<1803::AID-SIM612>3.0.CO;2-Y