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Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores
There is the potential for high-dimensional information about patients collected in clinical trials (such as genomic, imaging, and data from wearable technologies) to be informative for the efficacy of a new treatment in situations where only a subset of patients benefits from the treatment. The ada...
Autores principales: | , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611900/ https://www.ncbi.nlm.nih.gov/pubmed/32662542 http://dx.doi.org/10.1002/sim.8665 |
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author | Cherlin, Svetlana Wason, James M.S. |
author_facet | Cherlin, Svetlana Wason, James M.S. |
author_sort | Cherlin, Svetlana |
collection | PubMed |
description | There is the potential for high-dimensional information about patients collected in clinical trials (such as genomic, imaging, and data from wearable technologies) to be informative for the efficacy of a new treatment in situations where only a subset of patients benefits from the treatment. The adaptive signature design (ASD) method has been proposed for developing and testing the efficacy of a treatment in a high-efficacy patient group (the sensitive group) using genetic data. The method requires selection of three tuning parameters which may be highly computationally expensive. We propose a variation to the ASD method, the cross-validated risk scores (CVRS) design method, that does not require selection of any tuning parameters. The method is based on computing a risk score for each patient and dividing them into clusters using a nonparametric clustering procedure.We assess the properties of CVRS against the originally proposed cross-validated ASD using simulation data and a real psychiatry trial. CVRS, as assessed for various sample sizes and response rates, has a substantial reduction in the computational time required. In many simulation scenarios, there is a substantial improvement in the ability to correctly identify the sensitive group and the power of the design to detect a treatment effect in the sensitive group.We illustrate the application of the CVRS method on the psychiatry trial. |
format | Online Article Text |
id | pubmed-7611900 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
record_format | MEDLINE/PubMed |
spelling | pubmed-76119002021-10-27 Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores Cherlin, Svetlana Wason, James M.S. Stat Med Article There is the potential for high-dimensional information about patients collected in clinical trials (such as genomic, imaging, and data from wearable technologies) to be informative for the efficacy of a new treatment in situations where only a subset of patients benefits from the treatment. The adaptive signature design (ASD) method has been proposed for developing and testing the efficacy of a treatment in a high-efficacy patient group (the sensitive group) using genetic data. The method requires selection of three tuning parameters which may be highly computationally expensive. We propose a variation to the ASD method, the cross-validated risk scores (CVRS) design method, that does not require selection of any tuning parameters. The method is based on computing a risk score for each patient and dividing them into clusters using a nonparametric clustering procedure.We assess the properties of CVRS against the originally proposed cross-validated ASD using simulation data and a real psychiatry trial. CVRS, as assessed for various sample sizes and response rates, has a substantial reduction in the computational time required. In many simulation scenarios, there is a substantial improvement in the ability to correctly identify the sensitive group and the power of the design to detect a treatment effect in the sensitive group.We illustrate the application of the CVRS method on the psychiatry trial. 2020-10-30 2020-07-14 /pmc/articles/PMC7611900/ /pubmed/32662542 http://dx.doi.org/10.1002/sim.8665 Text en https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the Creative Commons Attribution (https://creativecommons.org/licenses/by/4.0/) , which permits use, distribution and reproduction in any medium, provided the original work is properly cited |
spellingShingle | Article Cherlin, Svetlana Wason, James M.S. Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
title | Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
title_full | Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
title_fullStr | Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
title_full_unstemmed | Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
title_short | Developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
title_sort | developing and testing high-efficacy patient subgroups within a clinical trial using risk scores |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7611900/ https://www.ncbi.nlm.nih.gov/pubmed/32662542 http://dx.doi.org/10.1002/sim.8665 |
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