Cargando…
Approaches to Selecting “Time Zero” in External Control Arms with Multiple Potential Entry Points: A Simulation Study of 8 Approaches
BACKGROUND: When including data from an external control arm to estimate comparative effectiveness, there is a methodological choice of when to set “time zero,” the point at which a patient would be eligible/enrolled in a contemporary study. Where patients receive multiple lines of eligible therapy...
Autores principales: | , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
SAGE Publications
2022
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459359/ https://www.ncbi.nlm.nih.gov/pubmed/35514320 http://dx.doi.org/10.1177/0272989X221096070 |
_version_ | 1784786494281482240 |
---|---|
author | Hatswell, Anthony J. Deighton, Kevin Snider, Julia Thornton Brookhart, M. Alan Faghmous, Imi Patel, Anik R. |
author_facet | Hatswell, Anthony J. Deighton, Kevin Snider, Julia Thornton Brookhart, M. Alan Faghmous, Imi Patel, Anik R. |
author_sort | Hatswell, Anthony J. |
collection | PubMed |
description | BACKGROUND: When including data from an external control arm to estimate comparative effectiveness, there is a methodological choice of when to set “time zero,” the point at which a patient would be eligible/enrolled in a contemporary study. Where patients receive multiple lines of eligible therapy and thus alternative points could be selected, this issue is complex. METHODS: A simulation study was conducted in which patients received multiple prior lines of therapy before entering either cohort. The results from the control and intervention data sets are compared using 8 methods for selecting time zero. The base-case comparison was set up to be biased against the intervention (which is generally received later), with methods compared in their ability to estimate the true intervention effectiveness. We further investigate the impact of key study attributes (such as sample size) and degree of overlap in time-varying covariates (such as prior lines of therapy) on study results. RESULTS: Of the 8 methods, 5 (all lines, random line, systematically selecting groups based on mean absolute error, root mean square error, or propensity scores) showed good performance in accounting for differences between the line at which patients were included. The first eligible line can be statistically inefficient in some situations. All lines (with censoring) cannot be used for survival outcomes. The last eligible line cannot be recommended. CONCLUSIONS: Multiple methods are available for selecting the most appropriate time zero from an external control arm. Based on the simulation, we demonstrate that some methods frequently perform poorly, with several viable methods remaining. In selecting between the viable methods, analysts should consider the context of their analysis and justify the approach selected. HIGHLIGHTS: There are multiple methods available from which an analyst may select “time zero” in an external control cohort. This simulation study demonstrates that some methods perform poorly but most are viable options, depending on context and the degree of overlap in time zero across cohorts. Careful thought and clear justification should be used when selecting the strategy for a study. |
format | Online Article Text |
id | pubmed-9459359 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | SAGE Publications |
record_format | MEDLINE/PubMed |
spelling | pubmed-94593592022-09-10 Approaches to Selecting “Time Zero” in External Control Arms with Multiple Potential Entry Points: A Simulation Study of 8 Approaches Hatswell, Anthony J. Deighton, Kevin Snider, Julia Thornton Brookhart, M. Alan Faghmous, Imi Patel, Anik R. Med Decis Making Original Research Articles BACKGROUND: When including data from an external control arm to estimate comparative effectiveness, there is a methodological choice of when to set “time zero,” the point at which a patient would be eligible/enrolled in a contemporary study. Where patients receive multiple lines of eligible therapy and thus alternative points could be selected, this issue is complex. METHODS: A simulation study was conducted in which patients received multiple prior lines of therapy before entering either cohort. The results from the control and intervention data sets are compared using 8 methods for selecting time zero. The base-case comparison was set up to be biased against the intervention (which is generally received later), with methods compared in their ability to estimate the true intervention effectiveness. We further investigate the impact of key study attributes (such as sample size) and degree of overlap in time-varying covariates (such as prior lines of therapy) on study results. RESULTS: Of the 8 methods, 5 (all lines, random line, systematically selecting groups based on mean absolute error, root mean square error, or propensity scores) showed good performance in accounting for differences between the line at which patients were included. The first eligible line can be statistically inefficient in some situations. All lines (with censoring) cannot be used for survival outcomes. The last eligible line cannot be recommended. CONCLUSIONS: Multiple methods are available for selecting the most appropriate time zero from an external control arm. Based on the simulation, we demonstrate that some methods frequently perform poorly, with several viable methods remaining. In selecting between the viable methods, analysts should consider the context of their analysis and justify the approach selected. HIGHLIGHTS: There are multiple methods available from which an analyst may select “time zero” in an external control cohort. This simulation study demonstrates that some methods perform poorly but most are viable options, depending on context and the degree of overlap in time zero across cohorts. Careful thought and clear justification should be used when selecting the strategy for a study. SAGE Publications 2022-05-06 2022-10 /pmc/articles/PMC9459359/ /pubmed/35514320 http://dx.doi.org/10.1177/0272989X221096070 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by-nc/4.0/This article is distributed under the terms of the Creative Commons Attribution-NonCommercial 4.0 License (https://creativecommons.org/licenses/by-nc/4.0/) which permits non-commercial use, reproduction and distribution of the work without further permission provided the original work is attributed as specified on the SAGE and Open Access pages (https://us.sagepub.com/en-us/nam/open-access-at-sage). |
spellingShingle | Original Research Articles Hatswell, Anthony J. Deighton, Kevin Snider, Julia Thornton Brookhart, M. Alan Faghmous, Imi Patel, Anik R. Approaches to Selecting “Time Zero” in External Control Arms with Multiple Potential Entry Points: A Simulation Study of 8 Approaches |
title | Approaches to Selecting “Time Zero” in External Control Arms with
Multiple Potential Entry Points: A Simulation Study of 8
Approaches |
title_full | Approaches to Selecting “Time Zero” in External Control Arms with
Multiple Potential Entry Points: A Simulation Study of 8
Approaches |
title_fullStr | Approaches to Selecting “Time Zero” in External Control Arms with
Multiple Potential Entry Points: A Simulation Study of 8
Approaches |
title_full_unstemmed | Approaches to Selecting “Time Zero” in External Control Arms with
Multiple Potential Entry Points: A Simulation Study of 8
Approaches |
title_short | Approaches to Selecting “Time Zero” in External Control Arms with
Multiple Potential Entry Points: A Simulation Study of 8
Approaches |
title_sort | approaches to selecting “time zero” in external control arms with
multiple potential entry points: a simulation study of 8
approaches |
topic | Original Research Articles |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9459359/ https://www.ncbi.nlm.nih.gov/pubmed/35514320 http://dx.doi.org/10.1177/0272989X221096070 |
work_keys_str_mv | AT hatswellanthonyj approachestoselectingtimezeroinexternalcontrolarmswithmultiplepotentialentrypointsasimulationstudyof8approaches AT deightonkevin approachestoselectingtimezeroinexternalcontrolarmswithmultiplepotentialentrypointsasimulationstudyof8approaches AT sniderjuliathornton approachestoselectingtimezeroinexternalcontrolarmswithmultiplepotentialentrypointsasimulationstudyof8approaches AT brookhartmalan approachestoselectingtimezeroinexternalcontrolarmswithmultiplepotentialentrypointsasimulationstudyof8approaches AT faghmousimi approachestoselectingtimezeroinexternalcontrolarmswithmultiplepotentialentrypointsasimulationstudyof8approaches AT patelanikr approachestoselectingtimezeroinexternalcontrolarmswithmultiplepotentialentrypointsasimulationstudyof8approaches |