Evidence map›Paper›PMID 21514219›Full record

SynthesisThe Lancet. Oncology2011

Genetic variants associated with breast-cancer risk: comprehensive research synopsis, meta-analysis, and epidemiological evidence.

Ben Zhang, Alicia Beeghly-Fadiel, Jirong Long, Wei Zheng

Abstract readMeta-AnalysisReview
In one paragraph

Synthesis in The Lancet. Oncology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 146 papers, 15 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
146citing papers in PubMed, 15 pooled it
–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

146 citing papers in PubMed, 15 syntheses or guidelines pooled it.

  1. Pooled it
  2. Systematic Review and Meta-Analysis of Lifestyle and Reproductive Factors Associated with Risk of Breast Cancer in Asian Women.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2024
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  5. Association of miRNA biosynthesis genesBioscience reports · 2018
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  15. Fine-mapping CASP8 risk variants in breast cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2012
    Pooled it
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86 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

4 authors.

Ben ZhangDivision of Epidemiology, Department of Medicine, Vanderbilt University School of Medicine, Nashville, TN, USA.
Alicia Beeghly-Fadiel
Jirong Long
Wei Zheng

Funding

Shanghai Breast Cancer StudyR01CA064277 · NCI · VANDERBILT UNIVERSITY · PI SHU, XIAO-OU · 1996 to 2012
$4.8M
Cancer Risk Reduction and Diet: A Cohort Study of WomenR37CA070867 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2009 to 2013
$4.7M
Consortium Study to Identify Breast Cancer Susceptibility LociR01CA148667 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI LONG, JIRONG, ZHENG, WEI · 2011 to 2015
$3.3M
Genetic Factors for Breast Cancer- A genome Wide StudyR01CA124558 · NCI · VANDERBILT UNIVERSITY · PI ZHENG, WEI · 2008 to 2012
$3.1M
NCI NIH HHS R01 CA064277NCI NIH HHS R01 CA124558NCI NIH HHS R01 CA148667NCI NIH HHS R37 CA070867
6 · The paper itself

Abstract

backgroundMore than 1000 reports have been published in the past two decades on associations between variants in candidate genes and risk of breast cancer. Results have been generally inconsistent. We did a literature search and meta-analyses to provide a synopsis of the current understanding of the genetic architecture of breast-cancer risk.

methodsA systematic literature search for candidate-gene association studies of breast-cancer risk was done in two stages, using PubMed on or before Feb 28, 2010. A total of 24,500 publications were identified, of which 1059 were deemed eligible for inclusion. Meta-analyses were done for 279 genetic variants in 128 candidate genes or chromosomal loci that had at least three data sources. Variants with significant associations by meta-analysis were assessed using the Venice criteria and scored as having strong, moderate, or weak cumulative evidence for an association with breast-cancer risk.

findings51 variants in 40 genes showed significant associations with breast-cancer risk. Cumulative epidemiological evidence of an association was graded as strong for ten variants in six genes (ATM, CASP8, CHEK2, CTLA4, NBN, and TP53), moderate for four variants in four genes (ATM, CYP19A1, TERT, and XRCC3), and weak for 37 variants. Additionally, in meta-analyses that included a minimum of 10,000 cases and 10,000 controls, convincing evidence of no association with breast-cancer risk was identified for 45 variants in 37 genes.

interpretationWhereas most genetic variants assessed in previous candidate-gene studies showed no association with breast-cancer risk in meta-analyses, 14 variants in nine genes had moderate to strong evidence for an association. Further evaluation of these variants is warranted.

fundingUS National Cancer Institute.

Indexed as

MutationAntigens, CDAromataseAtaxia Telangiectasia Mutated ProteinsBreast NeoplasmsCaspase 8Cell Cycle ProteinsCheckpoint Kinase 2CTLA-4 AntigenDNA-Binding ProteinsEvidence-Based MedicineFemaleGenetic Predisposition to DiseaseHumansNuclear ProteinsProtein Serine-Threonine KinasesAntigens, CDAromataseAtaxia Telangiectasia Mutated ProteinsATM protein, humanCASP8 protein, humanCaspase 8Cell Cycle ProteinsCheckpoint Kinase 2CHEK2 protein, humanCTLA-4 AntigenCTLA4 protein, humanDNA-Binding ProteinsNBN protein, humanNuclear ProteinsProtein Serine-Threonine KinasesTelomeraseTERT protein, humanTP53 protein, humanTumor Suppressor Protein p53Tumor Suppressor ProteinsX-ray repair cross complementing protein 3

Identifiers

PMID21514219
PMCPMC3114278

What OpenQuestion holds

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LicenceTDM
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.