Evidence map›Paper›PMID 38698686›Full record

ArticleCancer medicine2024

A polygenetic risk score combined with environmental factors better predict susceptibility to hepatocellular carcinoma in Chinese population.

Yuanlin Zou, Jicun Zhu, Caijuan Song, Tiandong Li, Keyan Wang, Jianxiang Shi, Hua Ye, Peng Wang

Abstract read
In one paragraph

Article in Cancer medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing 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

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

5 citing papers in PubMed.

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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

8 authors.

Yuanlin ZouDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0002-2366-8906
Jicun ZhuDepartment of Pharmacy, The First Affiliated Hospital of Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0002-3434-7630
Caijuan SongThe Institution for Chronic and Noncommunicable Disease Control and Prevention, Zhengzhou Center for Disease Control and Prevention, Zhengzhou, Henan Province, China.ORCID 0009-0000-4021-3981
Tiandong LiDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0002-5465-9797
Keyan WangHenan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0002-7241-1656
Jianxiang ShiHenan Key Laboratory of Tumor Epidemiology and State Key Laboratory of Esophageal Cancer Prevention & Treatment, Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0002-4346-3895
Hua YeDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0003-3657-2417
Peng WangDepartment of Epidemiology and Statistics, College of Public Health, Zhengzhou University, Zhengzhou, Henan Province, China.ORCID 0000-0003-4666-9706

Funding

National Science and Technology Major Project 2018ZX10302205Zhengzhou Major Project for Collaborative Innovation 18XTZX12007
6 · The paper itself

Abstract

aimsThis study aimed to investigate environmental factors and genetic variant loci associated with hepatocellular carcinoma (HCC) in Chinese population and construct a weighted genetic risk score (wGRS) and polygenic risk score (PRS).

methodsA case-control study was applied to confirm the single nucleotide polymorphisms (SNPs) and environmental variables linked to HCC in the Chinese population, which had been screened by meta-analyses. wGRS and PRS were built in training sets and validation sets. Area under the curve (AUC), net reclassification improvement (NRI), integrated discrimination improvement (IDI), Akaike information criterion (AIC), and Bayesian information criterion (BIC) were applied to evaluate the performance of the models.

resultsA total of 13 SNPs were included in both risk prediction models. Compared with wGRS, PRS had better accuracy and discrimination ability in predicting HCC risk. The AUC for PRS in combination with drinking history, cirrhosis, HBV infection, and family history of HCC in training sets and validation sets (AUC: 0.86, 95% CI: 0.84-0.89; AUC: 0.85, 95% CI: 0.81-0.89) increased at least 20% than the AUC for PRS alone (AUC: 0.63, 95% CI: 0.60-0.67; AUC: 0.65, 95% CI: 0.60-0.71).

conclusionsA novel model combining PRS with alcohol history, HBV infection, cirrhosis, and family history of HCC could be applied as an effective tool for risk prediction of HCC, which could discriminate at-risk individuals for precise prevention.

Indexed as

Carcinoma, HepatocellularGenetic Predisposition to DiseaseLiver NeoplasmsPolymorphism, Single NucleotideAgedCase-Control StudiesChinaEast Asian PeopleFemaleGene-Environment InteractionHumansMaleMiddle AgedMultifactorial InheritanceRisk AssessmentRisk Factorsgenetic risk scorehepatocellular carcinomapolygenic risk scorepredictive modelsrisk factors

Identifiers

PMID38698686
PMCPMC11066500

What Socratic holds

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LicenceCC BY
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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 Socratic graph.