ArticleBMC cancer2025
Development and internal validation of a lymphoma-specific nomogram for predicting venous thromboembolism: a retrospective cohort of 790 patients.
Article in BMC cancer, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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.
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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.
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Who cites it
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictors and Risk Assessment Models for Venous Thromboembolism in Patients Diagnosed with Lymphoma: A Systematic Review.Current oncology (Toronto, Ont.) · 2026Pooled it
- Risk Assessment for Venous Thrombosis in Lymphoma and Emerging Biomarkers.International journal of molecular sciences · 2026Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
backgroundThromboembolism (TE) is a serious complication in lymphoma, driving excess morbidity and mortality. Existing prediction tools perform suboptimally in lymphoma-specific settings.
methodsWe retrospectively analysed 790 newly diagnosed lymphoma patients (January 2019-December 2021). Patients were randomly split 7:3 into development and internal-validation cohorts. Forty-eight candidate predictors were screened with LASSO, followed by multivariable Cox modelling to construct a nomogram. Discrimination and calibration were assessed at 6, 12 and 24 months using time-dependent ROC analysis and bootstrap calibration.
resultsTE occurred in 77/790 patients (9.8%). Independent predictors were ECOG performance status, prior venous thromboembolism (VTE), coronary artery disease, central venous catheterisation, and APTT category. The nomogram showed good discrimination: AUCs were 0.813, 0.818 and 0.733 at 0.5, 1.0 and 2.0 years in the development cohort, and 0.724, 0.731 and 0.659 in the validation cohort. Conventional scores performed poorly in this population (e.g., at 1 year ThroLy 0.587 vs. Khorana 0.527). Calibration plots indicated close agreement between predicted and observed risks. Patients who experienced TE had poorer overall survival, with the greatest divergence in survival curves occurring within the first six months after diagnosis.
conclusionsThis lymphoma-specific model improves TE risk stratification and can inform individualised prophylaxis and early monitoring. External, multi-centre validation is warranted to confirm generalisability.
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