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Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables
Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. Trial characteristics such as the accrual rate and the prognostic value of baseline...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier
2017
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898543/ https://www.ncbi.nlm.nih.gov/pubmed/29696195 http://dx.doi.org/10.1016/j.conctc.2017.08.003 |
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author | Qian, Tianchen Colantuoni, Elizabeth Fisher, Aaron Rosenblum, Michael |
author_facet | Qian, Tianchen Colantuoni, Elizabeth Fisher, Aaron Rosenblum, Michael |
author_sort | Qian, Tianchen |
collection | PubMed |
description | Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. Trial characteristics such as the accrual rate and the prognostic value of baseline variables are typically unknown when a trial is being planned; these values are typically assumed based on information available before the trial starts. Because of the added complexity in adaptive enrichment designs compared to standard designs, it may be of special concern how sensitive the trial performance is to deviations from assumptions. Through simulation studies, we evaluate the sensitivity of Type I error, power, expected sample size, and trial duration to different design characteristics. Our simulation distributions mimic features of data from the Alzheimer's Disease Neuroimaging Initiative cohort study, and involve two subpopulations based on a genetic marker. We investigate the impact of the following design characteristics: the accrual rate, the time from enrollment to measurement of a short-term outcome and the primary outcome, and the prognostic value of baseline variables and short-term outcomes. To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators. We apply information-based monitoring, and evaluate how accurately information can be estimated in an ongoing trial. |
format | Online Article Text |
id | pubmed-5898543 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2017 |
publisher | Elsevier |
record_format | MEDLINE/PubMed |
spelling | pubmed-58985432018-04-25 Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables Qian, Tianchen Colantuoni, Elizabeth Fisher, Aaron Rosenblum, Michael Contemp Clin Trials Commun Article Adaptive enrichment designs involve rules for restricting enrollment to a subset of the population during the course of an ongoing trial. This can be used to target those who benefit from the experimental treatment. Trial characteristics such as the accrual rate and the prognostic value of baseline variables are typically unknown when a trial is being planned; these values are typically assumed based on information available before the trial starts. Because of the added complexity in adaptive enrichment designs compared to standard designs, it may be of special concern how sensitive the trial performance is to deviations from assumptions. Through simulation studies, we evaluate the sensitivity of Type I error, power, expected sample size, and trial duration to different design characteristics. Our simulation distributions mimic features of data from the Alzheimer's Disease Neuroimaging Initiative cohort study, and involve two subpopulations based on a genetic marker. We investigate the impact of the following design characteristics: the accrual rate, the time from enrollment to measurement of a short-term outcome and the primary outcome, and the prognostic value of baseline variables and short-term outcomes. To leverage prognostic information in baseline variables and short-term outcomes, we use a semiparametric, locally efficient estimator, and investigate its strengths and limitations compared to standard estimators. We apply information-based monitoring, and evaluate how accurately information can be estimated in an ongoing trial. Elsevier 2017-08-16 /pmc/articles/PMC5898543/ /pubmed/29696195 http://dx.doi.org/10.1016/j.conctc.2017.08.003 Text en © 2017 The Authors http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). |
spellingShingle | Article Qian, Tianchen Colantuoni, Elizabeth Fisher, Aaron Rosenblum, Michael Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
title | Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
title_full | Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
title_fullStr | Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
title_full_unstemmed | Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
title_short | Sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
title_sort | sensitivity of adaptive enrichment trial designs to accrual rates, time to outcome measurement, and prognostic variables |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5898543/ https://www.ncbi.nlm.nih.gov/pubmed/29696195 http://dx.doi.org/10.1016/j.conctc.2017.08.003 |
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