Cargando…

A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data

Background: Trial data often does not cover a sufficiently long period of time to truly capture time-toevent endpoints, however, Health Technology Assessment (HTA) bodies often require overall survival (OS) and progression-free survival (PFS) estimates. Often, significant survival effects are found...

Descripción completa

Detalles Bibliográficos
Autores principales: Tremblay, Gabriel, Haines, Patrick, Briggs, Andrew
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Columbia Data Analytics, LLC 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471402/
https://www.ncbi.nlm.nih.gov/pubmed/37663587
http://dx.doi.org/10.36469/9896
_version_ 1785099843403776000
author Tremblay, Gabriel
Haines, Patrick
Briggs, Andrew
author_facet Tremblay, Gabriel
Haines, Patrick
Briggs, Andrew
author_sort Tremblay, Gabriel
collection PubMed
description Background: Trial data often does not cover a sufficiently long period of time to truly capture time-toevent endpoints, however, Health Technology Assessment (HTA) bodies often require overall survival (OS) and progression-free survival (PFS) estimates. Often, significant survival effects are found beyond the time period observed in clinical trials, thus, extrapolation of trial results is required for health economic and HTA evaluations. Objectives: This paper looks at different techniques that can be used to extrapolate trial data, as well as criteria that should be used to select the most appropriate technique. Using these insights a formal decisionmaking criteria will be established, allowing users to follow a systematic approach to extrapolating survival estimates. The techniques are then applied to a metastatic breast cancer (MBC) example. Methods: A criterion-based guide was devised to allow the accurate extrapolation and justification of survival estimates in a MBC study comparing eribulin (Halaven) monotherapy with treatment of their (patient’s) physician’s choice (TPC). Parametric and piecewise models are used to extrapolate survival estimates, and statistical as well as visual tests are used to decide the most appropriate modelling technique. Results: In the case study presented, the optimal model was identified as the Accelerated Failure Time (AFT) Parametric model using a Gamma distribution with a treatment covariate for OS, and the Kaplan-Meier survival estimates for PFS. Conclusions: Survival estimates must be extrapolated to a time point such that the benefits of a therapy can be clearly demonstrated. A systematic approach combined with a formal decision-making structure should be used to minimize the potential for bias as well as making the process transparent.
format Online
Article
Text
id pubmed-10471402
institution National Center for Biotechnology Information
language English
publishDate 2015
publisher Columbia Data Analytics, LLC
record_format MEDLINE/PubMed
spelling pubmed-104714022023-09-01 A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data Tremblay, Gabriel Haines, Patrick Briggs, Andrew J Health Econ Outcomes Res Methodology and Healthcare Policy Background: Trial data often does not cover a sufficiently long period of time to truly capture time-toevent endpoints, however, Health Technology Assessment (HTA) bodies often require overall survival (OS) and progression-free survival (PFS) estimates. Often, significant survival effects are found beyond the time period observed in clinical trials, thus, extrapolation of trial results is required for health economic and HTA evaluations. Objectives: This paper looks at different techniques that can be used to extrapolate trial data, as well as criteria that should be used to select the most appropriate technique. Using these insights a formal decisionmaking criteria will be established, allowing users to follow a systematic approach to extrapolating survival estimates. The techniques are then applied to a metastatic breast cancer (MBC) example. Methods: A criterion-based guide was devised to allow the accurate extrapolation and justification of survival estimates in a MBC study comparing eribulin (Halaven) monotherapy with treatment of their (patient’s) physician’s choice (TPC). Parametric and piecewise models are used to extrapolate survival estimates, and statistical as well as visual tests are used to decide the most appropriate modelling technique. Results: In the case study presented, the optimal model was identified as the Accelerated Failure Time (AFT) Parametric model using a Gamma distribution with a treatment covariate for OS, and the Kaplan-Meier survival estimates for PFS. Conclusions: Survival estimates must be extrapolated to a time point such that the benefits of a therapy can be clearly demonstrated. A systematic approach combined with a formal decision-making structure should be used to minimize the potential for bias as well as making the process transparent. Columbia Data Analytics, LLC 2015-02-14 /pmc/articles/PMC10471402/ /pubmed/37663587 http://dx.doi.org/10.36469/9896 Text en https://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (4.0) (https://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Methodology and Healthcare Policy
Tremblay, Gabriel
Haines, Patrick
Briggs, Andrew
A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data
title A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data
title_full A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data
title_fullStr A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data
title_full_unstemmed A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data
title_short A Criterion-based Approach for the Systematic and Transparent Extrapolation of Clinical Trial Survival Data
title_sort criterion-based approach for the systematic and transparent extrapolation of clinical trial survival data
topic Methodology and Healthcare Policy
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10471402/
https://www.ncbi.nlm.nih.gov/pubmed/37663587
http://dx.doi.org/10.36469/9896
work_keys_str_mv AT tremblaygabriel acriterionbasedapproachforthesystematicandtransparentextrapolationofclinicaltrialsurvivaldata
AT hainespatrick acriterionbasedapproachforthesystematicandtransparentextrapolationofclinicaltrialsurvivaldata
AT briggsandrew acriterionbasedapproachforthesystematicandtransparentextrapolationofclinicaltrialsurvivaldata
AT tremblaygabriel criterionbasedapproachforthesystematicandtransparentextrapolationofclinicaltrialsurvivaldata
AT hainespatrick criterionbasedapproachforthesystematicandtransparentextrapolationofclinicaltrialsurvivaldata
AT briggsandrew criterionbasedapproachforthesystematicandtransparentextrapolationofclinicaltrialsurvivaldata