Statistical challenges in assessing potential efficacy of complex interventions in pilot or feasibility studies
Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, ea...
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| Vydané v: | Statistical methods in medical research Ročník 25; číslo 3; s. 997 - 1009 |
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| Hlavní autori: | , , , , |
| Médium: | Journal Article |
| Jazyk: | English |
| Vydavateľské údaje: |
England
01.06.2016
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| ISSN: | 1477-0334 |
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| Abstract | Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of efficacy is common for drug therapies, where phase II trials are often used as a screening mechanism to identify promising treatments. In this paper, we outline the challenges encountered in extending ideas developed in the phase II drug trial literature to the complex intervention setting. The prevalence of multiple endpoints and clustering of outcome data are identified as important considerations, having implications for timely and robust determination of optimal trial design parameters. The potential for Bayesian methods to help to identify robust trial designs and optimal decision rules is also explored. |
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| AbstractList | Early phase trials of complex interventions currently focus on assessing the feasibility of a large randomised control trial and on conducting pilot work. Assessing the efficacy of the proposed intervention is generally discouraged, due to concerns of underpowered hypothesis testing. In contrast, early assessment of efficacy is common for drug therapies, where phase II trials are often used as a screening mechanism to identify promising treatments. In this paper, we outline the challenges encountered in extending ideas developed in the phase II drug trial literature to the complex intervention setting. The prevalence of multiple endpoints and clustering of outcome data are identified as important considerations, having implications for timely and robust determination of optimal trial design parameters. The potential for Bayesian methods to help to identify robust trial designs and optimal decision rules is also explored. |
| Author | Brown, Sarah R Walwyn, Rebecca Ea Brown, Julia Farrin, Amanda J Wilson, Duncan T |
| Author_xml | – sequence: 1 givenname: Duncan T surname: Wilson fullname: Wilson, Duncan T email: d.t.wilson@leeds.ac.uk organization: Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK d.t.wilson@leeds.ac.uk – sequence: 2 givenname: Rebecca Ea surname: Walwyn fullname: Walwyn, Rebecca Ea organization: Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK – sequence: 3 givenname: Julia surname: Brown fullname: Brown, Julia organization: Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK – sequence: 4 givenname: Amanda J surname: Farrin fullname: Farrin, Amanda J organization: Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK – sequence: 5 givenname: Sarah R surname: Brown fullname: Brown, Sarah R organization: Clinical Trials Research Unit, Leeds Institute of Clinical Trials Research, University of Leeds, Leeds, UK |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/26071430$$D View this record in MEDLINE/PubMed |
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| Title | Statistical challenges in assessing potential efficacy of complex interventions in pilot or feasibility studies |
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