Evidence map›Paper›PMID 39126459›Full record

ArticleJournal of gastroenterology2024

The risk stratification and predictive performance of a new combined polygenic risk score for hepatocellular carcinoma.

Chengxiao Yu, Yuchen Tang, Maojie Liu, Xin Xu, Xinyuan Ge, Hongxia Ma, Guangfu Jin, Hongbing Shen, Ci Song, Zhibin Hu

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Article in Journal of gastroenterology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

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0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
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

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3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

10 authors.

Chengxiao Yu *Health Management Center, The First Affiliated Hospital of Nanjing Medical University, Nanjing, Jiangsu, 210029, People's Republic of China.
Yuchen Tang *Department of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Maojie LiuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Xin XuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Xinyuan GeDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Hongxia MaDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Guangfu JinDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Hongbing ShenDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China.
Ci SongDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China. songci@njmu.edu.cn.ORCID 0000-0001-6483-9372
Zhibin HuDepartment of Epidemiology, Center for Global Health, School of Public Health, Nanjing Medical University, Nanjing, Jiangsu, 211166, People's Republic of China. zhibin_hu@njmu.edu.cn.

Funding

China Postdoctoral Science Foundation 2021M701757Chinese Academy of Medical Sciences 2019RU038Jiangsu Funding Program for Excellent Postdoctoral Talent 2022ZB416National Natural Science Foundation of China 82204122Natural Science Foundation of Jiangsu Higher Education Institutions 22KJB330002Natural Science Foundation of Jiangsu Province BK20190652Natural Science Foundation of Jiangsu Province BK20220320Science and Technology Young Scientific and Technological Talents Project of Jiangsu Province 2021-50
6 · The paper itself

Abstract

backgroundRecent genome-wide association studies (GWASs) in liver diseases have generated some polygenic risk scores (PRSs), but their predictive effectiveness on hepatocellular carcinoma (HCC) risk assessment remains unclear.

methodsHere, we constructed a novel combined polygenic risk score and evaluated its increment to the well-established risk model. We used 15 HCC-associated genetic loci from two PRSs and FinnGen GWAS data to calculate a PRS-combined score and to fit the related PRS model in the UK Biobank cohort (N = 436,162). The PRS-combined score was further assessed for risk stratification for HCC integrating with the recommended clinical risk scores.

resultsThe PRS-combined model achieved a better AUC (0.657) than that of PRS-HFC (0.637) and PRS-cirrhosis (0.645). The top 20% of the PRS-combined distribution had a 3.25 increased risk of HCC vs. the middle decile (45-55%). At the population level, the addition of PRS-combined to the CLivD score significantly increased the C-statistic (from 0.716 to 0.746) and provided a remarkable improvement in reclassification (NRI = 0.088) at the 10-year risk threshold of 0.2%. In clinic, additional assessment of PRS-combined would reclassify 34,647 intermediate-risk participants as high genetic risk, corresponding to an increase of 63.92% (62/97) of the HCC events classified at high risk using the Fibrosis-4 alone.

conclusionsThe PRS may enhance HCC risk prediction effectiveness in the general population and refine risk stratification of the conventional clinical indicator.

Indexed as

Carcinoma, HepatocellularGenome-Wide Association StudyLiver NeoplasmsAdultAgedCohort StudiesFemaleGenetic Predisposition to DiseaseGenetic Risk ScoreHumansMaleMiddle AgedMultifactorial InheritancePolymorphism, Single NucleotidePredictive Value of TestsRisk AssessmentCohort studyHCCHCC screeningPredictive modelPRS

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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.