Cargando…

Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials

Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Since the sample size is usually determined by an argument based on the power of the trial, an interim analysis raises the question of how the final sample size shoul...

Descripción completa

Detalles Bibliográficos
Autores principales: Kunzmann, Kevin, Grayling, Michael J., Lee, Kim May, Robertson, David S., Rufibach, Kaspar, Wason, James M. S.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303654/
https://www.ncbi.nlm.nih.gov/pubmed/35023184
http://dx.doi.org/10.1002/sim.9288
_version_ 1784751920652484608
author Kunzmann, Kevin
Grayling, Michael J.
Lee, Kim May
Robertson, David S.
Rufibach, Kaspar
Wason, James M. S.
author_facet Kunzmann, Kevin
Grayling, Michael J.
Lee, Kim May
Robertson, David S.
Rufibach, Kaspar
Wason, James M. S.
author_sort Kunzmann, Kevin
collection PubMed
description Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Since the sample size is usually determined by an argument based on the power of the trial, an interim analysis raises the question of how the final sample size should be determined conditional on the accrued information. To this end, we first review and compare common approaches to estimating conditional power, which is often used in heuristic sample size recalculation rules. We then discuss the connection of heuristic sample size recalculation and optimal two‐stage designs, demonstrating that the latter is the superior approach in a fully preplanned setting. Hence, unplanned design adaptations should only be conducted as reaction to trial‐external new evidence, operational needs to violate the originally chosen design, or post hoc changes in the optimality criterion but not as a reaction to trial‐internal data. We are able to show that commonly discussed sample size recalculation rules lead to paradoxical adaptations where an initially planned optimal design is not invariant under the adaptation rule even if the planning assumptions do not change. Finally, we propose two alternative ways of reacting to newly emerging trial‐external evidence in ways that are consistent with the originally planned design to avoid such inconsistencies.
format Online
Article
Text
id pubmed-9303654
institution National Center for Biotechnology Information
language English
publishDate 2022
publisher John Wiley and Sons Inc.
record_format MEDLINE/PubMed
spelling pubmed-93036542022-07-28 Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials Kunzmann, Kevin Grayling, Michael J. Lee, Kim May Robertson, David S. Rufibach, Kaspar Wason, James M. S. Stat Med Research Articles Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Since the sample size is usually determined by an argument based on the power of the trial, an interim analysis raises the question of how the final sample size should be determined conditional on the accrued information. To this end, we first review and compare common approaches to estimating conditional power, which is often used in heuristic sample size recalculation rules. We then discuss the connection of heuristic sample size recalculation and optimal two‐stage designs, demonstrating that the latter is the superior approach in a fully preplanned setting. Hence, unplanned design adaptations should only be conducted as reaction to trial‐external new evidence, operational needs to violate the originally chosen design, or post hoc changes in the optimality criterion but not as a reaction to trial‐internal data. We are able to show that commonly discussed sample size recalculation rules lead to paradoxical adaptations where an initially planned optimal design is not invariant under the adaptation rule even if the planning assumptions do not change. Finally, we propose two alternative ways of reacting to newly emerging trial‐external evidence in ways that are consistent with the originally planned design to avoid such inconsistencies. John Wiley and Sons Inc. 2022-01-13 2022-02-28 /pmc/articles/PMC9303654/ /pubmed/35023184 http://dx.doi.org/10.1002/sim.9288 Text en © 2022 The Authors. Statistics in Medicine published by John Wiley & Sons Ltd. https://creativecommons.org/licenses/by/4.0/This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Research Articles
Kunzmann, Kevin
Grayling, Michael J.
Lee, Kim May
Robertson, David S.
Rufibach, Kaspar
Wason, James M. S.
Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
title Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
title_full Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
title_fullStr Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
title_full_unstemmed Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
title_short Conditional power and friends: The why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
title_sort conditional power and friends: the why and how of (un)planned, unblinded sample size recalculations in confirmatory trials
topic Research Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9303654/
https://www.ncbi.nlm.nih.gov/pubmed/35023184
http://dx.doi.org/10.1002/sim.9288
work_keys_str_mv AT kunzmannkevin conditionalpowerandfriendsthewhyandhowofunplannedunblindedsamplesizerecalculationsinconfirmatorytrials
AT graylingmichaelj conditionalpowerandfriendsthewhyandhowofunplannedunblindedsamplesizerecalculationsinconfirmatorytrials
AT leekimmay conditionalpowerandfriendsthewhyandhowofunplannedunblindedsamplesizerecalculationsinconfirmatorytrials
AT robertsondavids conditionalpowerandfriendsthewhyandhowofunplannedunblindedsamplesizerecalculationsinconfirmatorytrials
AT rufibachkaspar conditionalpowerandfriendsthewhyandhowofunplannedunblindedsamplesizerecalculationsinconfirmatorytrials
AT wasonjamesms conditionalpowerandfriendsthewhyandhowofunplannedunblindedsamplesizerecalculationsinconfirmatorytrials