Evidence map›Paper›PMID 29492197›Full record

ArticleOncotarget2018

Development of risk prediction models for glioma based on genome-wide association study findings and comprehensive evaluation of predictive performances.

Yingjie Zhao, Gong Chen, Hongjie Yu, Lingna Hu, Yunmeng Bian, Dapeng Yun, Juxiang Chen, Ying Mao, Hongyan Chen, Daru Lu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Oncotarget, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
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

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

3 citing papers in PubMed.

  1. Article
  2. Review
  3. 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

10 authors.

Yingjie ZhaoState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.
Gong ChenNeurosurgery Department of Huashan Hospital, Fudan University, Shanghai, China.
Hongjie YuState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.
Lingna HuState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.
Yunmeng BianState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.
Dapeng YunState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.
Juxiang ChenDepartment of Neurosurgery, Changzheng Hospital, Second Military Medical University, Shanghai, China.
Ying MaoNeurosurgery Department of Huashan Hospital, Fudan University, Shanghai, China.
Hongyan ChenState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.
Daru LuState Key Laboratory of Genetic Engineering and MOE Key Laboratory of Contemporary Anthropology, Collaborative Innovation Center for Genetics and Development, Institute of Genetics, School of Life Sciences, Fudan University, Shanghai, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Over 14 common single nucleotide polymorphisms (SNP) have been consistently identified from genome-wide association studies (GWAS) as associated with glioma risk in European background. The extent to which and how these genetic variants can improve the prediction of glioma risk has was not been investigated. In this study, we employed three independent case-control datasets in Chinese populations, tested GWAS signals in dataset1, validated association results in dataset2, developed prediction models in dataset2 for the consistently replicated SNPs, refined the consistently replicated SNPs in dataset3 and developed tailored models for Chinese populations. For model construction, we aggregated the contribution of multiple SNPs into genetic risk scores (count GRS and weighed GRS) or predicted risks from logistic regression analyses (PRFLR). In dataset2, the area under receiver operating characteristic curves (AUC) of the 5 consistently replicated SNPs by PRFLR(SNPs) was 0.615, higher than those of all GRSs(ranging from 0.607 to 0.611, all

Indexed as

genetic risk scoregenome wide association studygliomaprediction risk from logistic regression analysesrisk prediction

Identifiers

PMID29492197
PMCPMC5823595

What OpenQuestion holds

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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.