Transporting summary measures of relative effects from randomised trials to the treated patient population: an application to breast cancer endocrine therapy
Abstract
Randomised trials often report relative treatment effects, such as risk ratios and hazard ratios, for trial populations. Clinical decision-making, however, often benefits from estimates of absolute treatment effects in the population eligible for treatment. Trial participants may not represent this target population well, and restrictions on access to individual participant trial data can further complicate absolute effect estimation. Routine care data are often representative of the target population but may be subject to uncontrolled confounding. We consider estimation of the average treatment effect on the treated (ATT), an absolute measure, by combining a representative sample of treated routine care patients with summary measures (i.e., estimated risk or hazard ratios) from either a randomised trial or a meta-analysis of trials. Under marginal or conditional transportability assumptions, the ATT is shown to be identifiable. The implications of collapsibility of the effect measure on transportability are discussed, and plug-in estimators of the ATT are presented. Simulation studies are used to assess finite sample performance of the estimators in a range of settings. The proposed methods are applied to estimate the ATT of endocrine therapy on 15-year breast cancer mortality using results from a meta-analysis of randomised trials and England's National Disease Registration Service.
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BibTeX
@misc{shooksa2026transporting,
title = {{Transporting summary measures of relative effects from randomised trials to the treated patient population: an application to breast cancer endocrine therapy}},
author = {Bonnie E. Shook-Sa and Paul N. Zivich and Carolyn Taylor and David Dodwell and Jake Probert and Sarah C Darby and Paul McGale},
howpublished = {arXiv},
year = {2026},
month = sep,
doi = {10.48550/arxiv.2609.24305},
eprint = {2609.24305},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2609.24305},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Transporting summary measures of relative effects from randomised trials to the treated patient population: an application to breast cancer endocrine therapy
AU - Bonnie E. Shook-Sa
AU - Paul N. Zivich
AU - Carolyn Taylor
AU - David Dodwell
AU - Jake Probert
AU - Sarah C Darby
AU - Paul McGale
PY - 2026
DA - 2026/09/21
PB - arXiv
DO - 10.48550/arxiv.2609.24305
UR - https://arxiv.org/abs/2609.24305
AB - Randomised trials often report relative treatment effects, such as risk ratios and hazard ratios, for trial populations. Clinical decision-making, however, often benefits from estimates of absolute treatment effects in the population eligible for treatment. Trial participants may not represent this target population well, and restrictions on access to individual participant trial data can further complicate absolute effect estimation. Routine care data are often representative of the target population but may be subject to uncontrolled confounding. We consider estimation of the average treatment effect on the treated (ATT), an absolute measure, by combining a representative sample of treated routine care patients with summary measures (i.e., estimated risk or hazard ratios) from either a randomised trial or a meta-analysis of trials. Under marginal or conditional transportability assumptions, the ATT is shown to be identifiable. The implications of collapsibility of the effect measure on transportability are discussed, and plug-in estimators of the ATT are presented. Simulation studies are used to assess finite sample performance of the estimators in a range of settings. The proposed methods are applied to estimate the ATT of endocrine therapy on 15-year breast cancer mortality using results from a meta-analysis of randomised trials and England's National Disease Registration Service.
ER -