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AuthorAbdulMajeed, Jazeel
AuthorKhatib, Malkan
AuthorDulli, Mohamad
AuthorSioufi, Stephanie
AuthorAl-Khulaifi, Azhar
AuthorStone, Jennifer
AuthorFuruya-Kanamori, Luis
AuthorOnitilo, Adedayo A.
AuthorDoi, Suhail A.R.
Available date2024-03-13T13:38:03Z
Publication Date2024
Publication NameCancer Epidemiology
ResourceScopus
ISSN18777821
URIhttp://dx.doi.org/10.1016/j.canep.2023.102521
URIhttp://hdl.handle.net/10576/53033
AbstractBackground: In oncology clinical trials, there is the assumption that randomization sufficiently balances confounding covariates and therefore average treatment effects are usually reported. This paper explores the wider benefits provided by conditioning on covariates for reasons other than mitigation of confounding. Methods: We reanalyzed the data from primary randomized controlled trials listed in two meta-analyses to explore the significance of conditioning on smoking status in terms of the effect magnitude of treatment on progression free survival in non-small cell lung cancer. Results: The reanalysis revealed that conditioning on smoking status using sub-group analyses provided the closest empiric estimate of individual treatment effect based on smoking status and significantly reduced the heterogeneity of treatment effect observed across studies. In addition, smoking status was determined to be a modifier of the effect of treatment. Conclusion: Conditioning on prognostic covariates in randomized trials in oncology helps generate the closest empiric estimates of individual treatment benefit, addresses heterogeneity due to varying covariate distributions across trials and facilitates future decision making as well as evidence synthesis. Conditioning using sub-group analyses also allows examination for effect modification in meta-analysis.
SponsorThis work was made possible by Program Grant #NPRP-BSRA01-0406-210030 from the Qatar National Research Fund . The findings herein reflect the work, and are solely the responsibility of the authors.
Languageen
PublisherElsevier
SubjectConditional estimate' Covariate adjustment' Meta-analysis' Oncology' Randomized trial' Subgroup
TitleUse of conditional estimates of effect in cancer epidemiology: An application to lung cancer treatment
TypeArticle
Volume Number88
dc.accessType Abstract Only


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