Evidence map›Paper›PMID 35064782›Full record

ArticleInternational journal of epidemiology2022

Circulating proteins and risk of pancreatic cancer: a case-subcohort study among Chinese adults.

Christiana Kartsonaki, Yuanjie Pang, Iona Millwood, Ling Yang, Yu Guo, Robin Walters, Jun Lv, Michael Hill, Canqing Yu, Yiping Chen and 8 more

Open access · hybridAbstract read
In one paragraph

Article in International journal of epidemiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.

0numbers the graph read from it
0cells of the map it votes in
17citing papers in PubMed
1.6field-weighted citation impact, top 13% 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

17 citing papers in PubMed, 22 citations in OpenAlex.

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  5. Proteomics in pancreatic cancer.Biomarker research · 2025
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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

18 authors at 5 institutions in 2 countries.

Christiana KartsonakiClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Yuanjie PangDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.ORCID 0000-0002-4826-8861
Iona MillwoodClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Ling YangClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Yu GuoCKB Project Department, Chinese Academy of Medical Sciences, Beijing, China.
Robin WaltersClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Jun LvDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Michael HillClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Canqing YuDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.ORCID 0000-0002-0019-0014
Yiping ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Xiaofang ChenNCDs Prevention and Control Department, Pengzhou CDC, Pengzhou City, Sichuan Province, China.
Eric O'NeillDepartment of Oncology, University of Oxford, Oxford, UK.
Junshi ChenNHD Key Laboratory of Food Safety Risk Assessment, China National Center for Food Safety Risk Assessment, Beijing, China.
Ruth C TravisCancer Epidemiology Unit (CEU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Robert ClarkeClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID 0000-0002-9802-8241
Liming LiDepartment of Epidemiology and Biostatistics, School of Public Health, Peking University, Beijing, China.
Zhengming ChenClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.
Michael V HolmesClinical Trial Service Unit & Epidemiological Studies Unit (CTSU), Nuffield Department of Population Health, University of Oxford, Oxford, UK.ORCID 0000-0001-6617-0879
University of Oxford · GBPeking University · CNChina National Center for Food Safety Risk Assessment · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNJohn Radcliffe Hospital · GB

Funding

British Heart Foundation FS/18/23/33512Cancer Research UK 16896Cancer Research UK 29017Cancer Research UK 29186Cancer Research UK A17720Medical Research Council MC_U137686851Medical Research Council MC_UU_00017/1Medical Research Council MC_UU_12026/2Pancreatic Cancer UK FLF2015_06_OXFORDPancreatic Cancer UK RIF2016_A10Wellcome Trust 088158Wellcome Trust 104085Wellcome Trust 212946/Z/18/Z
6 · The paper itself

Abstract

backgroundPancreatic cancer has a very poor prognosis. Biomarkers that may help predict or diagnose pancreatic cancer may lead to earlier diagnosis and improved survival.

methodsThe prospective China Kadoorie Biobank (CKB) recruited 512 891 adults aged 30-79 years during 2004-08, recording 702 incident cases of pancreatic cancer during 9 years of follow-up. We conducted a case-subcohort study measuring 92 proteins in 610 cases and a subcohort of 623 individuals, using the OLINK immuno-oncology panel in stored baseline plasma samples. Cox regression with the Prentice pseudo-partial likelihood was used to estimate adjusted hazard ratios (HRs) for risk of pancreatic cancer by protein levels.

resultsAmong 1233 individuals (including 610 cases), several chemokines, interleukins, growth factors and membrane proteins were associated with risk of pancreatic cancer, with adjusted HRs per 1 standard deviation (SD) of 0.86 to 1.86, including monocyte chemotactic protein 3 (MCP3/CCL7) {1.29 [95% CI (confidence interval) (1.10, 1.51)]}, angiopoietin-2 (ANGPT2) [1.27 (1.10, 1.48)], interleukin-18 (IL18) [1.24 (1.07, 1.43)] and interleukin-6 (IL6) [1.21 (1.06, 1.38)]. Associations between some proteins [e.g. matrix metalloproteinase-7 (MMP7), hepatocyte growth factor (HGF) and tumour necrosis factor receptor superfamily member 9 [TNFRSF9)] and risk of pancreatic cancer were time-varying, with higher levels associated with higher short-term risk. Within the first year, the discriminatory ability of a model with known risk factors (age, age squared, sex, region, smoking, alcohol, education, diabetes and family history of cancer) was increased when several proteins were incorporated (weighted C-statistic changed from 0.85 to 0.99; P for difference = 4.5 × 10-5), although only a small increase in discrimination (0.77 to 0.79, P = 0.04) was achieved for long-term risk.

conclusionsSeveral plasma proteins were associated with subsequent diagnosis of pancreatic cancer. The potential clinical utility of these biomarkers warrants further investigation.

Indexed as

Pancreatic NeoplasmsAdultBiomarkersChinaHumansProspective StudiesRisk FactorsBiomarkersbiomarkersearly diagnosisPancreatic cancerproteomicsrisk prediction

Identifiers

PMID35064782
PMCPMC9189974
OpenAlexW4206109487

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Registered trials

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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.