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Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosisResearch in context

Authors :
Xiaoshuang Feng
David C. Muller
Hana Zahed
Karine Alcala
Florence Guida
Karl Smith-Byrne
Jian-Min Yuan
Woon-Puay Koh
Renwei Wang
Roger L. Milne
Julie K. Bassett
Arnulf Langhammer
Kristian Hveem
Victoria L. Stevens
Ying Wang
Mikael Johansson
Anne Tjønneland
Rosario Tumino
Mahdi Sheikh
Mattias Johansson
Hilary A. Robbins
Source :
EBioMedicine, Vol 92, Iss , Pp 104623- (2023)
Publication Year :
2023
Publisher :
Elsevier, 2023.

Abstract

Summary: Background: To evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis. Methods: We measured up to 1159 proteins in blood samples from 708 participants in 6 cohorts. Samples were collected within 3 years prior to lung cancer diagnosis. We used Cox proportional hazards models to identify proteins associated with overall mortality after lung cancer diagnosis. To evaluate model performance, we used a round-robin approach in which models were fit in 5 cohorts and evaluated in the 6th cohort. Specifically, we fit a model including 5 proteins and clinical parameters and compared its performance with clinical parameters only. Findings: There were 86 proteins nominally associated with mortality (p

Details

Language :
English
ISSN :
23523964
Volume :
92
Issue :
104623-
Database :
Directory of Open Access Journals
Journal :
EBioMedicine
Publication Type :
Academic Journal
Accession number :
edsdoj.5ce7e1861f4b77bc42b53f8ccbc532
Document Type :
article
Full Text :
https://doi.org/10.1016/j.ebiom.2023.104623