ArticleEuropace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology2025
Risk of cancer following presentation with new-onset atrial fibrillation using data from UK national databases.
Article in Europace : European pacing, arrhythmias, and cardiac electrophysiology : journal of the working groups on cardiac pacing, arrhythmias, and cardiac cellular electrophysiology of the European Society of Cardiology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Cancer as a Hidden Catalyst: Rethinking Postoperative Atrial Fibrillation After Cardiac Surgery.Journal of clinical medicine · 2026Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors.
Funding
Abstract
aimsAtrial fibrillation (AF) and cancer are both highly prevalent conditions and are known to be associated. Our aim was to identify predictors and develop models for all cancer types, in men and women, and for the four most common cancer types in the AF population using linked primary and secondary care data from the UK. METHODS AND
resultsWe included 163 549 patients diagnosed with AF between January 1998 and May 2016, and no previous history of cancer. Following TRIPOD methodology, we developed a ridge-penalized multivariable logistic regression model to predict 1-year cancer incidence after AF diagnosis, using 70% of the data for derivation and 30% for validation. Age was associated with an increased risk across all cancer types. Socioeconomic deprivation, smoking, excessive alcohol intake, family history of cancer, chronic kidney disease, anaemia, and several cancer-related symptoms and clinical signs (e.g. rectal bleeding, loss of appetite) were associated with an increased risk in one or more cancer types. The prediction models showed moderate-to-good discrimination in the validation set, with c-statistic of 0.69 (0.68-0.70) for all cancer in men, 0.63 (0.62-0.65) for all cancer in women, 0.70 (0.68-0.73) for lung cancer, 0.70 (0.66-0.73) for colorectal cancer, 0.59 (0.53-0.65) for breast cancer, and 0.78 (0.72-0.84) for prostate cancer.
conclusionMost of the identified potential risk factors for cancer in the AF population are also associated with cardiovascular disease. The 1-year cancer prediction models showed moderate to good predictive performance and may help improve the management of patients with AF.
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.