Evidence map›Paper›PMID 37236058›Full record

ArticleEBioMedicine2023

Evaluation of pre-diagnostic blood protein measurements for predicting survival after lung cancer diagnosis.

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 and 11 more

Open access · goldAbstract read
In one paragraph

Article in EBioMedicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
0.5field-weighted citation impact, top 30% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 2 citations in OpenAlex.

  1. Article
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

21 authors at 12 institutions in 9 countries.

Xiaoshuang FengGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France. Electronic address: fengx@iarc.who.int.
David C MullerDepartment 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.
Hana ZahedGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Karine AlcalaGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Florence GuidaEnvironment and Lifestyle Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Karl Smith-ByrneCancer Epidemiology Unit, Oxford Population Health, University of Oxford, Oxford, United Kingdom.
Jian-Min YuanUPMC Hillman Cancer Centre, Pittsburgh, PA, USA; Department of Epidemiology, Graduate School of Public Health, University of Pittsburgh, Pittsburgh, PA, USA.
Woon-Puay KohHealthy 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.
Renwei WangUPMC Hillman Cancer Centre, Pittsburgh, PA, USA.
Roger L MilneCancer 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.
Julie K BassettCancer Epidemiology Division, Cancer Council Victoria, Melbourne, Australia.
Arnulf LanghammerHUNT 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.
Kristian HveemHUNT 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.
Victoria L StevensRollins School of Public Health, Emory University, Atlanta, GA, USA.
Ying WangAmerican Cancer Society, Atlanta, GA, USA.
Mikael JohanssonDepartment of Radiation Sciences, Oncology, Umeå University, Umeå, Sweden.
Anne TjønnelandDanish Cancer Society Research Center, Copenhagen, Denmark; Department of Public Health, University of Copenhagen, Copenhagen, Denmark.
Rosario TuminoHyblean Association for Epidemiological Research, AIRE ONLUS Ragusa, Italy.
Mahdi SheikhGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Mattias JohanssonGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France.
Hilary A RobbinsGenomic Epidemiology Branch, International Agency for Research on Cancer, Lyon, France. Electronic address: robbinsh@iarc.who.int.
Centre international de recherche sur le cancer · FRNorwegian University of Science and Technology · NOAgency for Science, Technology and Research · SGAmerican Cancer Society · USCancer Council Victoria · AUEmory University · USImperial College London · GBItalian Association for Cancer Research · ITThe University of Melbourne · AUUniversity of Copenhagen · DKUniversity of Oxford · GBUniversity of Pittsburgh · US

Funding

Translating Molecular and Clinical Data to Population Lung Cancer Risk AssessmentU19CA203654 · NCI · UNIVERSITY OF NEW MEXICO HEALTH SCIS CTR · PI Christopher I. Amos, Rayjean J. Hung · 2017 to 2026
$23.7M
Prospective studies of cancer etiology and prevention in Shanghai and SingaporeR01CA144034 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YUAN, JIAN-MIN · 2010 to 2014
$7.0M
THE SINGAPORE COHORT STUDY OF DIET AND CANCERR01CA080205 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI YUAN, JIAN-MIN · 1999 to 2009
$5.3M
Cancer epidemiology cohorts in Shanghai and Singapore UM1CA182876 · NCI · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI YUAN, JIAN-MIN · 2014 to 2018
$4.3M
Cancer Research UK 29017Medical Research Council MR/S019669/1NCI NIH HHS R01 CA080205NCI NIH HHS R01 CA144034NCI NIH HHS U19 CA203654NCI NIH HHS UM1 CA182876World Health Organization 001
6 · The paper itself

Abstract

backgroundTo evaluate whether circulating proteins are associated with survival after lung cancer diagnosis, and whether they can improve prediction of prognosis.

methodsWe 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.

findingsThere 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).

interpretationBlood 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.

fundingNo 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.

Indexed as

Lung NeoplasmsAntigens, NeoplasmCell Adhesion MoleculesFranceHumansPrognosisProportional Hazards ModelsSwedenAntigens, NeoplasmCDCP1 protein, humanCell Adhesion MoleculesLung cancerLung cancer prognosisLung cancer survivalProtein biomarkers

Identifiers

PMID37236058
PMCPMC10232655
OpenAlexW4377981126

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.