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Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses

Meta‐analyses typically assess comparative treatment response for an end point at specific timepoints across studies. However, during drug development, it is often of interest to understand the response time‐course of competitor compounds for a variety of purposes. Examples of such application inclu...

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Detalles Bibliográficos
Autores principales: Boucher, Martin, Bennetts, Meg
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980518/
https://www.ncbi.nlm.nih.gov/pubmed/29569841
http://dx.doi.org/10.1002/psp4.12299
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author Boucher, Martin
Bennetts, Meg
author_facet Boucher, Martin
Bennetts, Meg
author_sort Boucher, Martin
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description Meta‐analyses typically assess comparative treatment response for an end point at specific timepoints across studies. However, during drug development, it is often of interest to understand the response time‐course of competitor compounds for a variety of purposes. Examples of such application include informing study design and characterizing the onset, maintenance, and offset of action. This tutorial acts as a “points for consideration” document, reviews relevant literature, and fits a longitudinal model to an example dataset.
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spelling pubmed-59805182018-06-01 Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses Boucher, Martin Bennetts, Meg CPT Pharmacometrics Syst Pharmacol Tutorial Meta‐analyses typically assess comparative treatment response for an end point at specific timepoints across studies. However, during drug development, it is often of interest to understand the response time‐course of competitor compounds for a variety of purposes. Examples of such application include informing study design and characterizing the onset, maintenance, and offset of action. This tutorial acts as a “points for consideration” document, reviews relevant literature, and fits a longitudinal model to an example dataset. John Wiley and Sons Inc. 2018-04-20 2018-05 /pmc/articles/PMC5980518/ /pubmed/29569841 http://dx.doi.org/10.1002/psp4.12299 Text en © 2018 The Authors CPT: Pharmacometrics & Systems Pharmacology published by Wiley Periodicals, Inc. on behalf of American Society for Clinical Pharmacology and Therapeutics This is an open access article under the terms of the http://creativecommons.org/licenses/by-nc/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited and is not used for commercial purposes.
spellingShingle Tutorial
Boucher, Martin
Bennetts, Meg
Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses
title Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses
title_full Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses
title_fullStr Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses
title_full_unstemmed Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses
title_short Many Flavors of Model‐Based Meta‐Analysis: Part II – Modeling Summary Level Longitudinal Responses
title_sort many flavors of model‐based meta‐analysis: part ii – modeling summary level longitudinal responses
topic Tutorial
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5980518/
https://www.ncbi.nlm.nih.gov/pubmed/29569841
http://dx.doi.org/10.1002/psp4.12299
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