Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis
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Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis. / Feng, Xiaoshuang; Muller, David C.; Zahed, Hana; Alcala, Karine; Guida, Florence; Smith-Byrne, Karl; Yuan, Jian Min; Koh, Woon Puay; Wang, Renwei; Milne, Roger L.; Bassett, Julie K.; Langhammer, Arnulf; Hveem, Kristian; Stevens, Victoria L.; Wang, Ying; Johansson, Mikael; Tjønneland, Anne; Tumino, Rosario; Sheikh, Mahdi; Johansson, Mattias; Robbins, Hilary A.
I: EBioMedicine, Bind 92, 104623, 2023.Publikation: Bidrag til tidsskrift › Tidsskriftartikel › Forskning › fagfællebedømt
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TY - JOUR
T1 - Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis
AU - Feng, Xiaoshuang
AU - Muller, David C.
AU - Zahed, Hana
AU - Alcala, Karine
AU - Guida, Florence
AU - Smith-Byrne, Karl
AU - Yuan, Jian Min
AU - Koh, Woon Puay
AU - Wang, Renwei
AU - Milne, Roger L.
AU - Bassett, Julie K.
AU - Langhammer, Arnulf
AU - Hveem, Kristian
AU - Stevens, Victoria L.
AU - Wang, Ying
AU - Johansson, Mikael
AU - Tjønneland, Anne
AU - Tumino, Rosario
AU - Sheikh, Mahdi
AU - Johansson, Mattias
AU - Robbins, Hilary A.
N1 - Publisher Copyright: © 2023 World Health Organization
PY - 2023
Y1 - 2023
N2 - 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 < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035). Interpretation: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information. Funding: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute ( U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden ( AMP19-962), and Swedish Department of Health Ministry.
AB - 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 < 0.05), but only CDCP1 remained statistically significant after accounting for multiple testing (hazard ratio per standard deviation: 1.19, 95% CI: 1.10–1.30, unadjusted p = 0.00004). The external C-index for the protein-based model was 0.63 (95% CI: 0.61–0.66), compared with 0.62 (95% CI: 0.59–0.64) for the model with clinical parameters only. Inclusion of proteins did not provide a statistically significant improvement in discrimination (C-index difference: 0.015, 95% CI: −0.003 to 0.035). Interpretation: Blood proteins measured within 3 years prior to lung cancer diagnosis were not strongly associated with lung cancer survival, nor did they importantly improve prediction of prognosis beyond clinical information. Funding: No explicit funding for this study. Authors and data collection supported by the US National Cancer Institute ( U19CA203654), INCA (France, 2019-1-TABAC-01), Cancer Research Foundation of Northern Sweden ( AMP19-962), and Swedish Department of Health Ministry.
KW - Lung cancer
KW - Lung cancer prognosis
KW - Lung cancer survival
KW - Protein biomarkers
U2 - 10.1016/j.ebiom.2023.104623
DO - 10.1016/j.ebiom.2023.104623
M3 - Journal article
C2 - 37236058
AN - SCOPUS:85162215164
VL - 92
JO - EBioMedicine
JF - EBioMedicine
SN - 2352-3964
M1 - 104623
ER -
ID: 358229844