ArticlePloS one2018
Prediction model for pancreatic cancer risk in the general Japanese population.
Article in PloS one, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 3 of them syntheses that pooled it.
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Who cites it
26 citing papers in PubMed, 3 syntheses or guidelines pooled it, 53 citations in OpenAlex.
- Diagnostic Risk Prediction Models for Upper Gastrointestinal Cancers: A Systematic Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Pooled it
- Role of Polygenic Risk Score in Cancer Precision Medicine of Non-European Populations: A Systematic Review.Current oncology (Toronto, Ont.) · 2022Pooled it
- Genome-wide association meta-analysis identifies GP2 gene risk variants for pancreatic cancer.Nature communications · 2020Pooled it
- Oxidative balance score, genetic susceptibility, and the risk of pancreatic cancer: a population-based cohort study.Nutrition journal · 2026Article
- Polygenic scores for risk of pancreatic ductal adenocarcinoma: evaluation of novel and published models.NPJ precision oncology · 2026Article
- Associations Between Obesity, Diabetes Mellitus, and Pancreatic Cancer in the Japanese Population: A Mendelian Randomization Study.Cancer science · 2026Article
- Leveraging the Electronic Health Record for Early Detection of Pancreatic Cancer Among 9.4 Million US Veterans.Clinical and translational gastroenterology · 2026Article
- Combining genetic and non-genetic factors to predict the risk of pancreatic cancer in patients with new-onset diabetes mellitus.BMC medicine · 2025Article
- Review
- Article
- Sex-Related Differences in Pancreatic Ductal Adenocarcinoma Progression and Response to Therapy.International journal of molecular sciences · 2024Review
- A Simple Clinical Scoring System to Determine the Risk of Pancreatic Cancer in the General Population.Diagnostics (Basel, Switzerland) · 2024Article
- Identification of Pancreatic Cancer Germline Risk Variants With Effects That Are Modified by Smoking.JCO precision oncology · 2024Article
- Association of genetic risk and lifestyle with pancreatic cancer and their age dependency: a large prospective cohort study in the UK Biobank.BMC medicine · 2023Article
- An Integrative Pancreatic Cancer Risk Prediction Model in the UK Biobank.Biomedicines · 2023Article
- Do Polygenic Risk Scores Add to Clinical Data in Predicting Pancreatic Cancer? A Scoping Review.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2023Article
- Predicting 10-Year Risk of Pancreatic Cancer Using a Combined Genetic and Clinical Model.Gastro hep advances · 2023Article
- Establishment of a mouse model of pancreatic cancer using human pancreatic cancer cell line S2-013-derived organoid.Human cell · 2022Article
- Susceptibility loci for pancreatic cancer in the Brazilian population.BMC medical genomics · 2021Article
- Artificial Intelligence and Early Detection of Pancreatic Cancer: 2020 Summative Review.Pancreas · 2021Review
Corrections and comments
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Authors and funding
25 authors at 11 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Genome-wide association studies (GWASs) have identified many single nucleotide polymorphisms (SNPs) that are significantly associated with pancreatic cancer susceptibility. We sought to replicate the associations of 61 GWAS-identified SNPs at 42 loci with pancreatic cancer in Japanese and to develop a risk model for the identification of individuals at high risk for pancreatic cancer development in the general Japanese population. The model was based on data including directly determined or imputed SNP genotypes for 664 pancreatic cancer case and 664 age- and sex-matched control subjects. Stepwise logistic regression uncovered five GWAS-identified SNPs at five loci that also showed significant associations in our case-control cohort. These five SNPs were included in the risk model and also applied to calculation of the polygenic risk score (PRS). The area under the curve determined with the leave-one-out cross-validation method was 0.63 (95% confidence interval, 0.60-0.66) or 0.61 (0.58-0.64) for versions of the model that did or did not include cigarette smoking and family history of pancreatic cancer in addition to the five SNPs, respectively. Individuals in the lowest and highest quintiles for the PRS had odds ratios of 0.62 (0.42-0.91) and 1.98 (1.42-2.76), respectively, for pancreatic cancer development compared with those in the middle quintile. We have thus developed a risk model for pancreatic cancer that showed moderately good discriminatory ability with regard to differentiation of pancreatic cancer patients from control individuals. Our findings suggest the potential utility of a risk model that incorporates replicated GWAS-identified SNPs and established demographic or environmental factors for the identification of individuals at increased risk for pancreatic cancer development.
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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.