ArticleJournal of thrombosis and haemostasis : JTH2025
Circulating tumor DNA predicts venous thromboembolism in patients with cancers.
Article in Journal of thrombosis and haemostasis : JTH, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Biomarkers of Hypercoagulability and Thromboinflammation in Cervical Cancer-Associated Thrombosis: A Systematic Review with Translational Insights from Breast Cancer.International journal of molecular sciences · 2026Pooled it
- Review
- Development of novel plasma proteomic biomarkers for cancer-associated thrombosis in an advanced cancer cohort.Journal of thrombosis and haemostasis : JTH · 2026Article
- Prediction of cancer-associated thrombosis by machine learning: results from the Vienna Cancer and Thrombosis Study.ESMO open · 2026Article
- Review
- Revisiting low-molecular-weight heparin for venous thromboembolism: from pharmacology to precision dosing and implementation.Frontiers in pharmacology · 2026Review
- Advancements in programmed cell death research in antitumor therapy: a comprehensive overview.Apoptosis : an international journal on programmed cell death · 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
13 authors.
Funding
Abstract
backgroundDespite rapid advances in liquid biopsy for circulating tumor DNA (ctDNA), its prognostic value for venous thromboembolism (VTE) in patients with cancer is underexplored, particularly in underserved and minoritized populations.
objectivesTo evaluate the role of ctDNA in risk stratification for cancer-associated VTE.
methodsWe analyzed data from 1038 cancer patients who underwent ctDNA measurement for oncologic care at a large safety-net hospital system in the United States. We investigated the association between ctDNA and VTE after adjusting for cancer type, stage, treatment, and time from initial diagnosis using Fine-Gray models. We further assessed the discrimination of the genetic, clinical-only, and combined models using the area under the time-dependent receiver operating characteristic curve (AUC).
resultsThe presence of pathogenic ctDNA was independently associated with VTE after adjusting for clinical variables. Independent of tumor type, the number of pathogenic ctDNA mutations was predictive of future VTE risk (adjusted subdistribution hazard ratios of 2.75, 1.94, and 1.38 for ≥3, 2, and 1 pathogenic mutation, respectively, compared with none; P < .0001). The association was primarily driven by mutations in KRAS, PTEN, CDKN2A, NF1, and EGFR genes. Compared with the clinical-only model (AUC, 0.71; 95% CI, 0.64-0.76), the combined clinical and ctDNA model had a numerically higher time-dependent AUC (AUC, 0.74; 95% CI, 0.67-0.80).
conclusionctDNA testing may serve as an adjunctive tool to clinical risk assessment models in cancer patients to improve personalized VTE risk assessment and management.
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.