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    Stat Methods Med Res. 2002 Oct;11(5):381-402.

    Ethics, data-dependent designs, and the strategy of clinical trials: time to start learning-as-we-go?

    Source

    Centre for Applied Medical Statistics, Department of Public Health and Primary Care, University of Cambridge, Institute of Public Health, Robinson Way, Cambridge CB2 2SR, UK. chris.palmer@medschl.cam.ac.uk

    Abstract

    The seeds of modern clinical trials were unwittingly sown with the first use of randomization in a 1920s agricultural field experiment. The historical development of trials is briefly reviewed here, as are multifarious pressures and problems faced by those involved with clinical trials today. These challenges include recruitment difficulties, the emerging role of patient support groups, and legal threats over informed consent, to name three. Fundamentally, they reflect an overall shift towards patient-centred, individual ethics. I suggest many problems may be overcome by increased implementation of hitherto neglected, data-dependent designs for clinical trials. Over a dozen arguments against their use are countered, primarily through ethical considerations. Benefits and costs of refining clinical trials strategy are explored hypothetically under enhanced use of such 'learn-as-you-go' designs, in contrast to traditional, equal-allocation, fixed-sample-size and frequentist-based designs. These latter methods mirror crop field trials in which one cannot make scientific progress until after gathering objective data at harvest time. Some attempts to alleviate certain problems, such as Zelen randomization to boost recruitment, or over-reliance on 'large and simple trials' to detect moderate-sized treatment effects, are discussed and found inadequate. A proposal for wider discussion is made to assist the selective introduction of 'small and complex trials,' which could simultaneously expedite medical research, satisfy the concerns of regulators, statisticians, and doctors alike, and help address the growing demands of 21st-century patients.

    PMID:
    12357585
    [PubMed - indexed for MEDLINE]

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