ArticleCancer medicine2024
Predicting Pancreatic Cancer in New-Onset Diabetes Cohort Using a Novel Model With Integrated Clinical and Genetic Indicators: A Large-Scale Prospective Cohort Study.
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 8 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
8 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Performance of risk prediction models for pancreatic cancer in patients with new-onset diabetes: a systematic review and meta-analysis.Frontiers in oncology · 2026Pooled it
- Article
- Progress, challenges, and future directions of pancreatic cancer surveillance in high-risk populations.Communications medicine · 2026Review
- The silent epidemic within the pandemic: pathophysiology and prediction of post-COVID-19 diabetes.Journal of translational medicine · 2026Review
- Prediction of Pancreatic Cancer Risk in Patients with New-Onset Diabetes.Visceral medicine · 2025Review
- Development of scoring models to predict early pancreatic cancer risk in new-onset diabetes mellitus patients.Hepatobiliary surgery and nutrition · 2025Article
- Can AI Be Useful in the Early Detection of Pancreatic Cancer in Patients with New-Onset Diabetes?Biomedicines · 2025Review
- New-onset diabetes as an emerging risk group for early detection of pancreatic cancer: current evidence, clinical challenge, and future directions.Frontiers in gastroenterology (Lausanne, Switzerland) · 2025Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
introductionIndividuals who develop new-onset diabetes have been identified as a high-risk cohort for pancreatic cancer (PC), exhibiting an incidence rate nearly 8 times higher than the general population. Hence, the targeted screening of this specific cohort presents a promising opportunity for early pancreatic cancer detection. We aimed to develop and validate a novel model capable of identifying high-risk individuals among those with new-onset diabetes.
methodsEmploying the UK Biobank cohort, we focused on those developing new-onset diabetes during follow-up. Genetic and clinical characteristics available at registration were considered as candidate predictors. We conducted univariate regression analysis to identify potential indicators and used a 5-fold cross-validation method to select optimal predictors for model development. Five machine learning algorithms were used for model development.
resultsAmong 12,735 patients with new-onset diabetes, 100 (0.8%) were diagnosed with PC within 2 years. The final model (area under the curve, 0.897; 95% confidence interval, 0.865-0.929) included 5 clinical predictors and 24 single nucleotide polymorphisms. Two threshold cut-offs were established: 1.28% and 5.26%. The recommended 1.28% cut-off, based on model performance, reduces definitive testing to 13% of the total population while capturing 76% of PC cases. The high-risk threshold is 5.26%. Utilizing this threshold, only 2% of the population needs definitive testing, capturing nearly half of PC cases.
conclusionsWe, for the first time, combined clinical and genetic data to develop and validate a model to determine the risk of pancreatic cancer in patients with new-onset diabetes using machine learning algorithms. By reducing the number of unnecessary tests while ensuring that a substantial proportion of high-risk patients are identified, this tool has the potential to improve patient outcomes and optimize healthcare sources.
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.