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Verfasst von:Haller, Bernhard [VerfasserIn]   i
 Ringleb, Peter A. [VerfasserIn]   i
Titel:Investigation of age-treatment interaction in the SPACE trial using different statistical approaches
Verf.angabe:Bernhard Haller, Hans-Henning Eckstein, Peter A. Ringleb & Kurt Ulm
Jahr:2019
Jahr des Originals:2018
Umfang:13 S.
Fussnoten:Gesehen am 03.06.2019 ; Published online: 17 Dec 2018
Titel Quelle:Enthalten in: Journal of applied statistics
Ort Quelle:Abingdon [u.a.] : Taylor & Francis, Taylor & Francis Group, 1974
Jahr Quelle:2019
Band/Heft Quelle:46(2019), 9, Seite 1689-1701
ISSN Quelle:1360-0532
Abstract:Selection of treatments to fit the specific needs for a certain patient is one major challenge in modern medicine. Personalized treatments rely on established patient-treatment interactions. In recent years, various statistical methods for the identification and estimation of interactions between relevant covariates and treatment were proposed. In this article, different available methods for detection and estimation of a covariate-treatment interaction for a time-to-event outcome, namely the standard Cox regression model assuming a linear interaction, the fractional polynomials approach for interaction, the modified outcome approach, the local partial-likelihood approach, and STEPP (Subpopulation Treatment Effect Pattern Plots) were applied to data from the SPACE trial, a randomized clinical trial comparing stent-protected angioplasty (CAS) to carotid endarterectomy (CEA) in patients with symptomatic stenosis, with the aim to analyse the interaction between age and treatment. Time from primary intervention to the first relevant event (any stroke or death) was considered as outcome parameter. The analyses suggest a qualitative interaction between patient age and treatment indicating a lower risk after treatment with CAS compared to CEA for younger patients, while for elderly patients a lower risk after CEA was observed. Differences in the statistical methods regarding the observed results, applicability, and interpretation are discussed.
DOI:doi:10.1080/02664763.2018.1558186
URL:Bitte beachten Sie: Dies ist ein Bibliographieeintrag. Ein Volltextzugriff für Mitglieder der Universität besteht hier nur, falls für die entsprechende Zeitschrift/den entsprechenden Sammelband ein Abonnement besteht oder es sich um einen OpenAccess-Titel handelt.

Volltext ; Verlag: https://doi.org/10.1080/02664763.2018.1558186
 Volltext: https://doi.org/10.1080/02664763.2018.1558186
 DOI: https://doi.org/10.1080/02664763.2018.1558186
Datenträger:Online-Ressource
Sprache:eng
Sach-SW:Covariate-treatment interaction
 individualized medicine
 non-linear interaction
 predictive covariate
 qualitative interaction
K10plus-PPN:1666637394
Verknüpfungen:→ Zeitschrift

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