Literature DB >> 12357585

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

C R Palmer1.   

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.

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Year:  2002        PMID: 12357585     DOI: 10.1191/0962280202sm298ra

Source DB:  PubMed          Journal:  Stat Methods Med Res        ISSN: 0962-2802            Impact factor:   3.021


  7 in total

1.  Uncertainty and the ethics of clinical trials.

Authors:  Sven Ove Hansson
Journal:  Theor Med Bioeth       Date:  2006

2.  Bayesian Models and Decision Algorithms for Complex Early Phase Clinical Trials.

Authors:  Peter F Thall
Journal:  Stat Sci       Date:  2010-05       Impact factor: 2.901

3.  Modelling of the outcome of non-inferiority trials by integration of historical data.

Authors:  Alberto Russu; Erik van Zwet; Giuseppe De Nicolao; Oscar Della Pasqua
Journal:  J Pharmacokinet Pharmacodyn       Date:  2011-08-21       Impact factor: 2.745

4.  Bayesian adaptive design for targeted therapy development in lung cancer--a step toward personalized medicine.

Authors:  Xian Zhou; Suyu Liu; Edward S Kim; Roy S Herbst; J Jack Lee
Journal:  Clin Trials       Date:  2008       Impact factor: 2.486

5.  Multi-armed Bandit Models for the Optimal Design of Clinical Trials: Benefits and Challenges.

Authors:  Sofía S Villar; Jack Bowden; James Wason
Journal:  Stat Sci       Date:  2015       Impact factor: 2.901

6.  Adaptive designs based on the truncated product method.

Authors:  Markus Neuhäuser; Frank Bretz
Journal:  BMC Med Res Methodol       Date:  2005-09-19       Impact factor: 4.615

7.  Dose Titration Algorithm Tuning (DTAT) should supersede 'the' Maximum Tolerated Dose (MTD) in oncology dose-finding trials.

Authors:  David C Norris
Journal:  F1000Res       Date:  2017-02-07
  7 in total

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