ArticleJournal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer2015
Lung Cancer Risk Prediction Using Common SNPs Located in GWAS-Identified Susceptibility Regions.
Article in Journal of thoracic oncology : official publication of the International Association for the Study of Lung Cancer, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled 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.
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.
Who cites it
26 citing papers in PubMed, 1 synthesis or guideline pooled it, 46 citations in OpenAlex.
- Identification of risk loci and a polygenic risk score for lung cancer: a large-scale prospective cohort study in Chinese populations.The Lancet. Respiratory medicine · 2019Pooled it
- Precision Medicine in Lung Cancer Screening: A Paradigm Shift in Early Detection-Precision Screening for Lung Cancer.Diagnostics (Basel, Switzerland) · 2025Review
- Polygenic Risk Score Is Associated with Developing and Dying from Lung Cancer in the National Lung Screening Trial.Journal of clinical medicine · 2025Article
- Predicting Drug Resistance inDiagnostics (Basel, Switzerland) · 2025Article
- The HUNT lung-SNP model: genetic variants plus clinical variables improve lung cancer risk assessment over clinical models.Journal of cancer research and clinical oncology · 2024Article
- Exploring the Role of Vitamin D, Vitamin D-Dependent Proteins, and Vitamin D Receptor Gene Variation in Lung Cancer Risk.International journal of molecular sciences · 2024Review
- Missense variants in CYP4B1 associated with increased risk of lung cancer among Chinese Han population.World journal of surgical oncology · 2023Article
- Association of smoking and polygenic risk with the incidence of lung cancer: a prospective cohort study.British journal of cancer · 2022Article
- IPRS: Leveraging Gene-Environment Interaction to Reconstruct Polygenic Risk Score.Frontiers in genetics · 2022Article
- Genetic analysis of colorectal carcinoma using high throughput single nucleotide polymorphism genotyping technique within the population of Jammu and Kashmir.Molecular biology reports · 2021Article
- Targeting lung cancer screening to individuals at greatest risk: the role of genetic factors.Journal of medical genetics · 2021Article
- A Bayesian linear mixed model for prediction of complex traits.Bioinformatics (Oxford, England) · 2021Article
- Assessing Lung Cancer Absolute Risk Trajectory Based on a Polygenic Risk Model.Cancer research · 2021Article
- Epigenetic Inactivation of the Tumor SuppressorCancers · 2020Article
- High dimensional model representation of log likelihood ratio: binary classification with SNP data.BMC medical genomics · 2020Article
- Individual and joint contributions of genetic and methylation risk scores for enhancing lung cancer risk stratification: data from a population-based cohort in Germany.Clinical epigenetics · 2020Article
- Quantifying the Potential for Future Gene Therapy to Lower Lifetime Risk of Polygenic Late-Onset Diseases.International journal of molecular sciences · 2019Article
- A prospective study of dietary polyunsaturated fatty acids intake and lung cancer risk.International journal of cancer · 2018Article
- A Decade of GWAS Results in Lung Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2018Review
- Predictive accuracy of combined genetic and environmental risk scores.Genetic epidemiology · 2018Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors at 2 institutions in 1 country.
Funding
Abstract
introductionGenome-wide association studies (GWAS) have consistently identified specific lung cancer susceptibility regions. We evaluated the lung cancer-predictive performance of single-nucleotide polymorphisms (SNPs) in these regions.
methodsLung cancer cases (N = 778) and controls (N = 1166) were genotyped for 77 SNPs located in GWAS-identified lung cancer susceptibility regions. Variable selection and model development used stepwise logistic regression and decision-tree analyses. In a subset nested in the Pittsburgh Lung Screening Study, change in area under the receiver operator characteristic curve and net reclassification improvement were used to compare predictions made by risk factor models with and without genetic variables.
resultsVariable selection and model development kept two SNPs in each of three GWAS regions, rs2736100 and rs7727912 in 5p15.33, rs805297 and rs1802127 in 6p21.33, and rs8034191 and rs12440014 in 15q25.1. The ratio of cases to controls was three times higher among subjects with a high-risk genotype in every one as opposed to none of the three GWAS regions (odds ratio, 3.14; 95% confidence interval, 2.02-4.88; adjusted for sex, age, and pack-years). Adding a three-level classified count of GWAS regions with high-risk genotypes to an age and smoking risk factor-only model improved lung cancer prediction by a small amount: area under the receiver operator characteristic curve, 0.725 versus 0.717 (p = 0.056); overall net reclassification improvement was 0.052 across low-, intermediate-, and high- 6-year lung cancer risk categories (<3.0%, 3.0%-4.9%, ≥ 5.0%).
conclusionSpecifying genotypes for SNPs in three GWAS-identified susceptibility regions improved lung cancer prediction, but probably by an extent too small to affect disease control practice.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.