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Clinical trial adaptation by matching evidence in complementary patient sub-groups of auxiliary blinding questionnaire responses

Arandjelović, Ognjen 2015, Clinical trial adaptation by matching evidence in complementary patient sub-groups of auxiliary blinding questionnaire responses, PLoS one, vol. 10, no. 7, Article number: e0131524, pp. 1-24, doi: 10.1371/journal.pone.0131524.

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Title Clinical trial adaptation by matching evidence in complementary patient sub-groups of auxiliary blinding questionnaire responses
Author(s) Arandjelović, Ognjen
Journal name PLoS one
Volume number 10
Issue number 7
Season Article number: e0131524
Start page 1
End page 24
Total pages 24
Publisher Public Library of Science
Place of publication San Francisco, Calif.
Publication date 2015-07-10
ISSN 1932-6203
Keyword(s) Science & Technology
Multidisciplinary Sciences
Science & Technology - Other Topics
DESIGN
SUCCESS
Summary Clinical trial adaptation refers to any adjustment of the trial protocol after the onset of the trial. Such adjustment may take on various forms, including the change in the dose of administered medicines, the frequency of administering an intervention, the number of trial participants, or the duration of the trial, to name just some possibilities. The main goal is to make the process of introducing new medical interventions to patients more efficient, either by reducing the cost or the time associated with evaluating their safety and efficacy. The principal challenge, which is an outstanding research problem, is to be found in the question of how adaptation should be performed so as to minimize the chance of distorting the outcome of the trial. In this paper we propose a novel method for achieving this. Unlike most of the previously published work, our approach focuses on trial adaptation by sample size adjustment i.e. by reducing the number of trial participants in a statistically informed manner. We adopt a stratification framework recently proposed for the analysis of trial outcomes in the presence of imperfect blinding and based on the administration of a generic auxiliary questionnaire that allows the participants to express their belief concerning the assigned intervention (treatment or control). We show that this data, together with the primary measured variables, can be used to make the probabilistically optimal choice of the particular sub-group a participant should be removed from if trial size reduction is desired. Extensive experiments on a series of simulated trials are used to illustrate the effectiveness of our method.
Language eng
DOI 10.1371/journal.pone.0131524
Field of Research 080109 Pattern Recognition and Data Mining
Socio Economic Objective 970108 Expanding Knowledge in the Information and Computing Sciences
HERDC Research category C1 Refereed article in a scholarly journal
ERA Research output type C Journal article
Copyright notice ©2015, The Authors
Free to Read? Yes
Use Rights Creative Commons Attribution licence
Persistent URL http://hdl.handle.net/10536/DRO/DU:30081827

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.