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The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations

INTRODUCTION: Ideally, real-world data (RWD) collected to generate real-world evidence (RWE) should lead to impact on the care and health of real-world patients. Deriving from care in which clinicians and patients try various treatments to inform therapeutic decisions, N-of-1 trials bring scientific...

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Autores principales: Selker, Harry P., Dulko, Dorothy, Greenblatt, David J., Palm, Marisha, Trinquart, Ludovic
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Cambridge University Press 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10565195/
https://www.ncbi.nlm.nih.gov/pubmed/37830006
http://dx.doi.org/10.1017/cts.2023.604
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author Selker, Harry P.
Dulko, Dorothy
Greenblatt, David J.
Palm, Marisha
Trinquart, Ludovic
author_facet Selker, Harry P.
Dulko, Dorothy
Greenblatt, David J.
Palm, Marisha
Trinquart, Ludovic
author_sort Selker, Harry P.
collection PubMed
description INTRODUCTION: Ideally, real-world data (RWD) collected to generate real-world evidence (RWE) should lead to impact on the care and health of real-world patients. Deriving from care in which clinicians and patients try various treatments to inform therapeutic decisions, N-of-1 trials bring scientific methods to real-world practice. METHODS: These single-patient crossover trials generate RWD and RWE by giving individual patients various treatments in a double-blinded way in sequential periods to determine the most effective treatment for a given patient. RESULTS: This approach is most often used for patients with chronic, relatively stable conditions that provide the opportunity to make comparisons over multiple treatment periods, termed Type 1 N-of-1 trials. These are most helpful when there is heterogeneity of treatment effects among patients and no a priori best option. N-of-1 trials also can be done for patients with rare diseases, potentially testing only one treatment, to generate evidence for personalized treatment decisions, designated as Type 2 N-of-1 trials. With both types, in addition to informing individual’s treatments, when uniform protocols are used for multiple patients with the same condition, the data collected in the individual N-of-1 trials can be aggregated to provide RWD/RWE to inform more general use of the treatments. Thereby, N-of-1 trials can provide RWE for the care of individuals and for populations. CONCLUSIONS: To fulfill this potential, we believe N-of-1 trials should be built into our current healthcare ecosystem. To this end, we are building the needed infrastructure and engaging the stakeholders who should receive value from this approach.
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spelling pubmed-105651952023-10-12 The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations Selker, Harry P. Dulko, Dorothy Greenblatt, David J. Palm, Marisha Trinquart, Ludovic J Clin Transl Sci Research Article INTRODUCTION: Ideally, real-world data (RWD) collected to generate real-world evidence (RWE) should lead to impact on the care and health of real-world patients. Deriving from care in which clinicians and patients try various treatments to inform therapeutic decisions, N-of-1 trials bring scientific methods to real-world practice. METHODS: These single-patient crossover trials generate RWD and RWE by giving individual patients various treatments in a double-blinded way in sequential periods to determine the most effective treatment for a given patient. RESULTS: This approach is most often used for patients with chronic, relatively stable conditions that provide the opportunity to make comparisons over multiple treatment periods, termed Type 1 N-of-1 trials. These are most helpful when there is heterogeneity of treatment effects among patients and no a priori best option. N-of-1 trials also can be done for patients with rare diseases, potentially testing only one treatment, to generate evidence for personalized treatment decisions, designated as Type 2 N-of-1 trials. With both types, in addition to informing individual’s treatments, when uniform protocols are used for multiple patients with the same condition, the data collected in the individual N-of-1 trials can be aggregated to provide RWD/RWE to inform more general use of the treatments. Thereby, N-of-1 trials can provide RWE for the care of individuals and for populations. CONCLUSIONS: To fulfill this potential, we believe N-of-1 trials should be built into our current healthcare ecosystem. To this end, we are building the needed infrastructure and engaging the stakeholders who should receive value from this approach. Cambridge University Press 2023-09-06 /pmc/articles/PMC10565195/ /pubmed/37830006 http://dx.doi.org/10.1017/cts.2023.604 Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution and reproduction, provided the original article is properly cited.
spellingShingle Research Article
Selker, Harry P.
Dulko, Dorothy
Greenblatt, David J.
Palm, Marisha
Trinquart, Ludovic
The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
title The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
title_full The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
title_fullStr The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
title_full_unstemmed The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
title_short The use of N-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
title_sort use of n-of-1 trials to generate real-world evidence for optimal treatment of individuals and populations
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10565195/
https://www.ncbi.nlm.nih.gov/pubmed/37830006
http://dx.doi.org/10.1017/cts.2023.604
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