Cargando…
FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS
Personalized medicine is care that is tailored to an individual patient. In contrast, randomized trials are designed to report evidence of benefits and harms “on average”. The average trial participant though, is often healthier than older patients seen in clinical practice. A variety of methods hav...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Oxford University Press
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9765781/ http://dx.doi.org/10.1093/geroni/igac059.711 |
_version_ | 1784853570584051712 |
---|---|
author | Griswold, Michael Henegan, James Blackshear, Chad Windham, Beverly Gwen Mosley, Thomas |
author_facet | Griswold, Michael Henegan, James Blackshear, Chad Windham, Beverly Gwen Mosley, Thomas |
author_sort | Griswold, Michael |
collection | PubMed |
description | Personalized medicine is care that is tailored to an individual patient. In contrast, randomized trials are designed to report evidence of benefits and harms “on average”. The average trial participant though, is often healthier than older patients seen in clinical practice. A variety of methods have been proposed which offer improvements to traditional (but questionable) practices of one-subgroup-at-a-time examinations of treatment effect heterogeneity, but translating evidence from these advancements has received less attention. Data Science initiatives have allowed broader data sharing, data harmonization and data synthesizing approaches, as well as an enormous maturing of interactive visualization techniques. Motivated by the SPRINT study and using advanced approaches of marginalized standardization and the Predictive Approaches to Treatment effect Heterogeneity (PATH) statement, we show how researchers, regulators, clinicians and patients can "find themselves" on the treatment effect continuum and be better informed of potential individualized evidence through interactive visualizations. |
format | Online Article Text |
id | pubmed-9765781 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Oxford University Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-97657812022-12-20 FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS Griswold, Michael Henegan, James Blackshear, Chad Windham, Beverly Gwen Mosley, Thomas Innov Aging Abstracts Personalized medicine is care that is tailored to an individual patient. In contrast, randomized trials are designed to report evidence of benefits and harms “on average”. The average trial participant though, is often healthier than older patients seen in clinical practice. A variety of methods have been proposed which offer improvements to traditional (but questionable) practices of one-subgroup-at-a-time examinations of treatment effect heterogeneity, but translating evidence from these advancements has received less attention. Data Science initiatives have allowed broader data sharing, data harmonization and data synthesizing approaches, as well as an enormous maturing of interactive visualization techniques. Motivated by the SPRINT study and using advanced approaches of marginalized standardization and the Predictive Approaches to Treatment effect Heterogeneity (PATH) statement, we show how researchers, regulators, clinicians and patients can "find themselves" on the treatment effect continuum and be better informed of potential individualized evidence through interactive visualizations. Oxford University Press 2022-12-20 /pmc/articles/PMC9765781/ http://dx.doi.org/10.1093/geroni/igac059.711 Text en © The Author(s) 2022. Published by Oxford University Press on behalf of The Gerontological Society of America. https://creativecommons.org/licenses/by/4.0/This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted reuse, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Abstracts Griswold, Michael Henegan, James Blackshear, Chad Windham, Beverly Gwen Mosley, Thomas FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS |
title | FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS |
title_full | FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS |
title_fullStr | FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS |
title_full_unstemmed | FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS |
title_short | FINDING YOURSELF: PERSONALIZED MEDICINE, DATA SCIENCE, AND INTERACTIVE VISUALIZATIONS |
title_sort | finding yourself: personalized medicine, data science, and interactive visualizations |
topic | Abstracts |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9765781/ http://dx.doi.org/10.1093/geroni/igac059.711 |
work_keys_str_mv | AT griswoldmichael findingyourselfpersonalizedmedicinedatascienceandinteractivevisualizations AT heneganjames findingyourselfpersonalizedmedicinedatascienceandinteractivevisualizations AT blackshearchad findingyourselfpersonalizedmedicinedatascienceandinteractivevisualizations AT windhambeverlygwen findingyourselfpersonalizedmedicinedatascienceandinteractivevisualizations AT mosleythomas findingyourselfpersonalizedmedicinedatascienceandinteractivevisualizations |