ArticleNature medicine2024
DNA liquid biopsy-based prediction of cancer-associated venous thromboembolism.
Article in Nature medicine, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers, 1 of them a synthesis that pooled it.
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Who cites it
25 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Research trends and hotspots of circulating tumor DNA in colorectal cancer: a bibliometric study.Frontiers in oncology · 2025Pooled it
- High-quantity capture of heterogeneous circulating tumor cellsMaterials today. Bio · 2026Article
- Molecular sampling limits of ctDNA detection in clinical plasma samples.The journal of liquid biopsy · 2026Article
- Review
- Liquid biopsies reveal dual compartments of cancer risk from tumor and host-derived mutations.Bioinformatics (Oxford, England) · 2026Article
- Development of novel plasma proteomic biomarkers for cancer-associated thrombosis in an advanced cancer cohort.Journal of thrombosis and haemostasis : JTH · 2026Article
- Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- The COMPASS-CAT risk assessment model for predicting in-hospital venous thromboembolism in patients with breast, lung, colorectal, and ovarian cancer: A retrospective cohort study.The Journal of international medical research · 2026Article
- Plasma proteomics improves thrombosis prediction in patients with cancer and identifies targetable IL-17-driven endothelial activation.Science translational medicine · 2026Article
- Tumor Whole-Genome Sequencing for Prediction of Venous Thromboembolism in Patients With Metastasized Solid Cancer.Circulation. Genomic and precision medicine · 2026Article
- Prediction of cancer-associated thrombosis by machine learning: results from the Vienna Cancer and Thrombosis Study.ESMO open · 2026Article
- Extracellular vesicle and particle biomarkers in cancer: a machine learning blueprint for liquid biopsy.Journal of nanobiotechnology · 2026Review
- When Cancer Clots: An Extensive Radiologic Analysis of Cancer-Associated Thromboembolism.Cancers · 2026Review
- Empowering AI data scientists using a multi-agent LLM framework with self-evolving capabilities for autonomous, tool-aware biomedical data analyses.Nature biomedical engineering · 2026Article
- Review
- Revisiting low-molecular-weight heparin for venous thromboembolism: from pharmacology to precision dosing and implementation.Frontiers in pharmacology · 2026Review
- [Lung Cancer with Pulmonary Embolism: Evidence-based Progress in Anticoagulation Assessment and Management].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2025Review
- From multi-omics to deep learning: advances in cfDNA-based liquid biopsy for multi-cancer screening.Biomarker research · 2025Review
- A Comprehensive Oncological Biomarker Framework Guiding Precision Medicine.Biomolecules · 2025Review
- Implementation of circulating tumor DNA (ctDNA) testing in precision oncology: A four-year experience from a tertiary cancer center in India.The journal of liquid biopsy · 2025Article
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Authors and funding
27 authors.
Funding
Abstract
Cancer-associated venous thromboembolism (VTE) is a major source of oncologic cost, morbidity and mortality. Identifying high-risk patients for prophylactic anticoagulation is challenging and adds to clinician burden. Circulating tumor DNA (ctDNA) sequencing assays ('liquid biopsies') are widely implemented, but their utility for VTE prognostication is unknown. Here we analyzed three plasma sequencing cohorts: a pan-cancer discovery cohort of 4,141 patients with non-small cell lung cancer (NSCLC) or breast, pancreatic and other cancers; a prospective validation cohort consisting of 1,426 patients with the same cancer types; and an international generalizability cohort of 463 patients with advanced NSCLC. ctDNA detection was associated with VTE independent of clinical and radiographic features. A machine learning model trained on liquid biopsy data outperformed previous risk scores (discovery, validation and generalizability c-indices 0.74, 0.73 and 0.67, respectively, versus 0.57, 0.61 and 0.54 for the Khorana score). In real-world data, anticoagulation was associated with lower VTE rates if ctDNA was detected (n = 2,522, adjusted hazard ratio (HR) = 0.50, 95% confidence interval (CI): 0.30-0.81); ctDNA
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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.