Cargando…
Leveraging observational data to identify targeted patient populations for future randomized trials
Randomized controlled trials reported in the literature are often affected by poor generalizability, and pragmatic trials have become an increasingly utilized workaround approach to overcome logistical limitations and explore routine interventions demonstrating equipoise in clinical practice. Intrav...
Autores principales: | , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
American Journal Experts
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187375/ https://www.ncbi.nlm.nih.gov/pubmed/37205590 http://dx.doi.org/10.21203/rs.3.rs-2641628/v1 |
_version_ | 1785042728051015680 |
---|---|
author | Lazzareschi, Daniel V. Fong, Nicholas Pirracchio, Romain Mathis, Michael R. Legrand, Matthieu |
author_facet | Lazzareschi, Daniel V. Fong, Nicholas Pirracchio, Romain Mathis, Michael R. Legrand, Matthieu |
author_sort | Lazzareschi, Daniel V. |
collection | PubMed |
description | Randomized controlled trials reported in the literature are often affected by poor generalizability, and pragmatic trials have become an increasingly utilized workaround approach to overcome logistical limitations and explore routine interventions demonstrating equipoise in clinical practice. Intravenous albumin, for example, is commonly administered in the perioperative setting despite lacking supportive evidence. Given concerns for cost, safety, and efficacy, randomized trials are needed to explore the clinical equipoise of albumin therapy in this setting, and we therefore present an approach to identifying populations exposed to perioperative albumin to encourage clinical equipoise in patient selection and optimize study design for clinical trials. |
format | Online Article Text |
id | pubmed-10187375 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | American Journal Experts |
record_format | MEDLINE/PubMed |
spelling | pubmed-101873752023-05-17 Leveraging observational data to identify targeted patient populations for future randomized trials Lazzareschi, Daniel V. Fong, Nicholas Pirracchio, Romain Mathis, Michael R. Legrand, Matthieu Res Sq Article Randomized controlled trials reported in the literature are often affected by poor generalizability, and pragmatic trials have become an increasingly utilized workaround approach to overcome logistical limitations and explore routine interventions demonstrating equipoise in clinical practice. Intravenous albumin, for example, is commonly administered in the perioperative setting despite lacking supportive evidence. Given concerns for cost, safety, and efficacy, randomized trials are needed to explore the clinical equipoise of albumin therapy in this setting, and we therefore present an approach to identifying populations exposed to perioperative albumin to encourage clinical equipoise in patient selection and optimize study design for clinical trials. American Journal Experts 2023-05-05 /pmc/articles/PMC10187375/ /pubmed/37205590 http://dx.doi.org/10.21203/rs.3.rs-2641628/v1 Text en https://creativecommons.org/licenses/by/4.0/This work is licensed under a Creative Commons Attribution 4.0 International License (https://creativecommons.org/licenses/by/4.0/) , which allows reusers to distribute, remix, adapt, and build upon the material in any medium or format, so long as attribution is given to the creator. The license allows for commercial use. |
spellingShingle | Article Lazzareschi, Daniel V. Fong, Nicholas Pirracchio, Romain Mathis, Michael R. Legrand, Matthieu Leveraging observational data to identify targeted patient populations for future randomized trials |
title | Leveraging observational data to identify targeted patient populations for future randomized trials |
title_full | Leveraging observational data to identify targeted patient populations for future randomized trials |
title_fullStr | Leveraging observational data to identify targeted patient populations for future randomized trials |
title_full_unstemmed | Leveraging observational data to identify targeted patient populations for future randomized trials |
title_short | Leveraging observational data to identify targeted patient populations for future randomized trials |
title_sort | leveraging observational data to identify targeted patient populations for future randomized trials |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10187375/ https://www.ncbi.nlm.nih.gov/pubmed/37205590 http://dx.doi.org/10.21203/rs.3.rs-2641628/v1 |
work_keys_str_mv | AT lazzareschidanielv leveragingobservationaldatatoidentifytargetedpatientpopulationsforfuturerandomizedtrials AT fongnicholas leveragingobservationaldatatoidentifytargetedpatientpopulationsforfuturerandomizedtrials AT pirracchioromain leveragingobservationaldatatoidentifytargetedpatientpopulationsforfuturerandomizedtrials AT mathismichaelr leveragingobservationaldatatoidentifytargetedpatientpopulationsforfuturerandomizedtrials AT legrandmatthieu leveragingobservationaldatatoidentifytargetedpatientpopulationsforfuturerandomizedtrials |