A principal stratification approach to estimating the effect of continuing treatment after observing early outcomes
Patrick M. Schnell,
Richard Baumgartner,
Shahrul Mt‐Isa and
Vladimir Svetnik
Journal of the Royal Statistical Society Series C, 2022, vol. 71, issue 5, 1065-1084
Abstract:
Chronic diseases often require continuing care, and early response to treatment can be an important predictor of long‐term efficacy. Often, an apparent lack of early efficacy may lead to discontinuation of treatment, with the decision made either by clinicians or by the patients themselves. Thus, it is important to determine whether or not a desired early outcome corresponds to a beneficial long‐term effect of continuing treatment, and conversely, whether or not the absence of such an outcome corresponds to a lack of long‐term benefit. However, primary clinical trials of such treatments are not commonly designed to answer such questions, for example by randomizing subjects to continue or discontinue treatment after observing early outcomes. We propose an approach to estimating the effect of continuing treatment after observing early outcomes using data from randomized controlled trials in which treatment discontinuation was not part of the design. Our approach estimates average causal effects of continuing treatment on long‐term outcomes in principal strata defined by the potential early outcomes under treatment. For illustration, we estimate the effects of continuing to take gaboxadol to treat insomnia conditional on early improvement in subjective sleep quality after two nights, based on a standard parallel‐arm randomized controlled trial.
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:
Downloads: (external link)
https://doi.org/10.1111/rssc.12552
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:bla:jorssc:v:71:y:2022:i:5:p:1065-1084
Ordering information: This journal article can be ordered from
http://ordering.onli ... 1111/(ISSN)1467-9876
Access Statistics for this article
Journal of the Royal Statistical Society Series C is currently edited by R. Chandler and P. W. F. Smith
More articles in Journal of the Royal Statistical Society Series C from Royal Statistical Society Contact information at EDIRC.
Bibliographic data for series maintained by Wiley Content Delivery ().