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Enhancing the analytic utility of clinical trial data to inform health disparities research

Clinical trials are often conducted among younger, healthier, and less racially diverse patient populations than the population at large. Health disparities for individuals with cancer are most apparent when there are notable differences in the occurrence, frequency, burden of cancer and mortality r...

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Detalles Bibliográficos
Autores principales: Cohen, Steven B., Unangst, Jennifer, Yu, Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726652/
https://www.ncbi.nlm.nih.gov/pubmed/33319118
http://dx.doi.org/10.1016/j.conctc.2020.100677
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author Cohen, Steven B.
Unangst, Jennifer
Yu, Feng
author_facet Cohen, Steven B.
Unangst, Jennifer
Yu, Feng
author_sort Cohen, Steven B.
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description Clinical trials are often conducted among younger, healthier, and less racially diverse patient populations than the population at large. Health disparities for individuals with cancer are most apparent when there are notable differences in the occurrence, frequency, burden of cancer and mortality rates among specific population groups. Enhancing the diversity of participants in clinical trials to reflect the characteristics of cancer survivors in the U.S. population is of growing interest to better insure the safety and efficacy of resultant treatments. The Project Data Sphere® (PDS) cancer research platform is a first-of-its kind research environment that provides the research community with broad access to both de-identified patient-level clinical trial data and advanced analytic tools to enable big data-driven research. To address these analytic constraints, the data profiles in selected PDS patient-level cancer phase III clinical datasets have been augmented by linking the social, economic, and health-related characteristics of like cancer survivors from nationally representative health and health care-related survey data from the Medical Expenditure Panel Survey (MEPS). Our article shines a spotlight on this ongoing initiative to improve access to clinical trial data in support of health care disparities research initiatives.
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spelling pubmed-77266522020-12-13 Enhancing the analytic utility of clinical trial data to inform health disparities research Cohen, Steven B. Unangst, Jennifer Yu, Feng Contemp Clin Trials Commun Article Clinical trials are often conducted among younger, healthier, and less racially diverse patient populations than the population at large. Health disparities for individuals with cancer are most apparent when there are notable differences in the occurrence, frequency, burden of cancer and mortality rates among specific population groups. Enhancing the diversity of participants in clinical trials to reflect the characteristics of cancer survivors in the U.S. population is of growing interest to better insure the safety and efficacy of resultant treatments. The Project Data Sphere® (PDS) cancer research platform is a first-of-its kind research environment that provides the research community with broad access to both de-identified patient-level clinical trial data and advanced analytic tools to enable big data-driven research. To address these analytic constraints, the data profiles in selected PDS patient-level cancer phase III clinical datasets have been augmented by linking the social, economic, and health-related characteristics of like cancer survivors from nationally representative health and health care-related survey data from the Medical Expenditure Panel Survey (MEPS). Our article shines a spotlight on this ongoing initiative to improve access to clinical trial data in support of health care disparities research initiatives. Elsevier 2020-11-25 /pmc/articles/PMC7726652/ /pubmed/33319118 http://dx.doi.org/10.1016/j.conctc.2020.100677 Text en © 2020 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Cohen, Steven B.
Unangst, Jennifer
Yu, Feng
Enhancing the analytic utility of clinical trial data to inform health disparities research
title Enhancing the analytic utility of clinical trial data to inform health disparities research
title_full Enhancing the analytic utility of clinical trial data to inform health disparities research
title_fullStr Enhancing the analytic utility of clinical trial data to inform health disparities research
title_full_unstemmed Enhancing the analytic utility of clinical trial data to inform health disparities research
title_short Enhancing the analytic utility of clinical trial data to inform health disparities research
title_sort enhancing the analytic utility of clinical trial data to inform health disparities research
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7726652/
https://www.ncbi.nlm.nih.gov/pubmed/33319118
http://dx.doi.org/10.1016/j.conctc.2020.100677
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