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Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials
BACKGROUND: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of hea...
Autores principales: | , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
S. Karger AG
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716191/ https://www.ncbi.nlm.nih.gov/pubmed/36466953 http://dx.doi.org/10.1159/000525897 |
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author | Ratitch, Bohdana Rodriguez-Chavez, Isaac R. Dabral, Abhishek Fontanari, Adriano Vega, Julio Onorati, Francesco Vandendriessche, Benjamin Morton, Stuart Damestani, Yasaman |
author_facet | Ratitch, Bohdana Rodriguez-Chavez, Isaac R. Dabral, Abhishek Fontanari, Adriano Vega, Julio Onorati, Francesco Vandendriessche, Benjamin Morton, Stuart Damestani, Yasaman |
author_sort | Ratitch, Bohdana |
collection | PubMed |
description | BACKGROUND: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. SUMMARY: Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. KEY MESSAGES: This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies. |
format | Online Article Text |
id | pubmed-9716191 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | S. Karger AG |
record_format | MEDLINE/PubMed |
spelling | pubmed-97161912022-12-03 Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials Ratitch, Bohdana Rodriguez-Chavez, Isaac R. Dabral, Abhishek Fontanari, Adriano Vega, Julio Onorati, Francesco Vandendriessche, Benjamin Morton, Stuart Damestani, Yasaman Digit Biomark Viewpoint BACKGROUND: The proliferation and increasing maturity of biometric monitoring technologies allow clinical investigators to measure the health status of trial participants in a more holistic manner, especially outside of traditional clinical settings. This includes capturing meaningful aspects of health in daily living and a more granular and objective manner compared to traditional tools in clinical settings. SUMMARY: Within multidisciplinary teams, statisticians and data scientists are increasingly involved in clinical trials that incorporate digital clinical measures. They are called upon to provide input into trial planning, generation of evidence on the clinical validity of novel clinical measures, and evaluation of the adequacy of existing evidence. Analysis objectives related to demonstrating clinical validity of novel clinical measures differ from typical objectives related to demonstrating safety and efficacy of therapeutic interventions using established measures which statisticians are most familiar with. KEY MESSAGES: This paper discusses key considerations for generating evidence for clinical validity through the lens of the type and intended use of a clinical measure. This paper also briefly discusses the regulatory pathways through which clinical validity evidence may be reviewed and highlights challenges that investigators may encounter while dealing with data from biometric monitoring technologies. S. Karger AG 2022-08-29 /pmc/articles/PMC9716191/ /pubmed/36466953 http://dx.doi.org/10.1159/000525897 Text en Copyright © 2022 by The Author(s). Published by S. Karger AG, Basel https://creativecommons.org/licenses/by-nc/4.0/This article is licensed under the Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC). Usage and distribution for commercial purposes requires written permission. |
spellingShingle | Viewpoint Ratitch, Bohdana Rodriguez-Chavez, Isaac R. Dabral, Abhishek Fontanari, Adriano Vega, Julio Onorati, Francesco Vandendriessche, Benjamin Morton, Stuart Damestani, Yasaman Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials |
title | Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials |
title_full | Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials |
title_fullStr | Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials |
title_full_unstemmed | Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials |
title_short | Considerations for Analyzing and Interpreting Data from Biometric Monitoring Technologies in Clinical Trials |
title_sort | considerations for analyzing and interpreting data from biometric monitoring technologies in clinical trials |
topic | Viewpoint |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9716191/ https://www.ncbi.nlm.nih.gov/pubmed/36466953 http://dx.doi.org/10.1159/000525897 |
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