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Evaluation of pre-d...
Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis
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- Feng, Xiaoshuang (author)
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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- Muller, David C. (author)
- Department of Epidemiology and Biostatistics, School of Public Health, Imperial College London, London, United Kingdom; Department of Epidemiology and Biostatistics, School of Public Health, MRC-PHE, Centre for Environment and Health, Imperial College London, London, United Kingdom
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- Zahed, Hana (author)
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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- Alcala, Karine (author)
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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- Guida, Florence (author)
- Environment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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- Smith-Byrne, Karl (author)
- Cancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom
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- Yuan, Jian-Min (author)
- UPMC Hillman Cancer Centre, PA, Pittsburgh, United States; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, PA, Pittsburgh, United States
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- Koh, Woon-Puay (author)
- Healthy Longevity Translational Research Program, Yong Loo Lin School of Medicine, National University of Singapore, Singapore; Singapore Institute for Clinical Sciences, Agency for Science Technology and Research (A∗STAR), Singapore
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- Wang, Renwei (author)
- UPMC Hillman Cancer Centre, PA, Pittsburgh, United States
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- Milne, Roger L. (author)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia; Centre for Epidemiology and Biostatistics, Melbourne School of Population and Global Health, University of Melbourne, Parkville, Australia; School of Clinical Sciences at Monash Health, Monash University, Melbourne, Australia
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- Bassett, Julie K. (author)
- Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia
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- Langhammer, Arnulf (author)
- HUNT Research Center, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Levanger, Norway; Levanger Hospital, Nord-Trøndelag Hospital Trust, Levanger, Norway
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- Hveem, Kristian (author)
- HUNT Research Center, Department of Public Health and Nursing, NTNU Norwegian University of Science and Technology, Levanger, Norway; Department of Public Health and Nursing, K.G. Jebsen Centre for Genetic Epidemiology, Norwegian University of Science and Technology, Trondheim, Norway
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- Stevens, Victoria L. (author)
- Rollins School of Public Health, Emory University, GA, Atlanta, United States
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- Wang, Ying (author)
- American Cancer Society, GA, Atlanta, United States
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- Johansson, Mikael (author)
- Umeå universitet,Onkologi
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- Tjønneland, Anne (author)
- Danish Cancer Society Research Center, Copenhagen, Denmark; Department of Public Health, University of Copenhagen, Copenhagen, Denmark
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- Tumino, Rosario (author)
- Hyblean Association for Epidemiological Research, AIRE ONLUS Ragusa, Italy
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- Sheikh, Mahdi (author)
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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- Johansson, Mattias (author)
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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- Robbins, Hilary A. (author)
- Genomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France
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(creator_code:org_t)
- Elsevier, 2023
- 2023
- English.
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In: EBioMedicine. - : Elsevier. - 2352-3964. ; 92
- Related links:
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https://doi.org/10.1...
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https://umu.diva-por... (primary) (Raw object)
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Abstract
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- 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.
Subject headings
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Cancer och onkologi (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Cancer and Oncology (hsv//eng)
Keyword
- Lung cancer
- Lung cancer prognosis
- Lung cancer survival
- Protein biomarkers
Publication and Content Type
- ref (subject category)
- art (subject category)
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- By the author/editor
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Feng, Xiaoshuang
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Muller, David C.
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Zahed, Hana
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Alcala, Karine
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Guida, Florence
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Smith-Byrne, Kar ...
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show more...
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Yuan, Jian-Min
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Koh, Woon-Puay
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Wang, Renwei
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Milne, Roger L.
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Bassett, Julie K ...
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Langhammer, Arnu ...
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Hveem, Kristian
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Stevens, Victori ...
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Wang, Ying
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Johansson, Mikae ...
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Tjønneland, Anne
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Tumino, Rosario
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Sheikh, Mahdi
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Johansson, Matti ...
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Robbins, Hilary ...
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- About the subject
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- MEDICAL AND HEALTH SCIENCES
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MEDICAL AND HEAL ...
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and Clinical Medicin ...
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and Cancer and Oncol ...
- Articles in the publication
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EBioMedicine
- By the university
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Umeå University