| Title: | Prothrombotic genetic variants and cancer-associated venous thromboembolism: defining thrombotic risk across tumor types. |
| Journal: | Haematologica |
| Published: | 7 May 2026 |
| Pubmed: | https://pubmed.ncbi.nlm.nih.gov/42095241/ |
| DOI: | https://doi.org/10.3324/haematol.2026.300579 |
| URL: | https://haematologica.org/article/download/14165/80276 |
Publication 20143
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Abstract
Cancer-associated venous thromboembolism (CAT) is a major cause of mortality in cancer patients. Prothrombotic genetic variants increase venous thromboembolism risk in the general population, but contribution to CAT remains unclear, particularly within different tumor types. We sought to determine whether the presence of thrombophilic variants influence relative and absolute CAT risk, and may be utilised in thromboprophylaxis decision-making. We evaluated 398,053 UK Biobank participants, of whom 42,122 developed cancer. A panel of seven thrombophilic variants (ABO, FGG, FXI, FVL, PTM, SLC44A2 and TSPAN15) were evaluated using multistate models, and 2-year absolute risk was estimated using Aalen- Johansen methods. We report hazard ratios (HRs) adjusting for age, sex, and body mass index. CAT incidence was 7.82% versus 2.08% in non-cancer participants. In the non-cancer population, all seven variants were associated with a higher risk of VTE. In patients with cancer, FVL conferred the highest risk (HR 1.81 for one risk allele; HR 5.75 for two risk alleles), followed by SLC44A2 (HR 1.51 for one risk allele, 1.53 for two risk alleles). Genetic effects were greatest in high-risk cancers, including pancreatic and lung cancers. For FVL heterozygotes, 2-year absolute VTE risk approximately doubled in several malignancies, including 5.17% to 9.26% in colorectal cancer and from 4.16% to 10.59% in lymphoma. In conclusion, thrombophilic variants, particularly FVL and SLC44A2, significantly increase the relative risk of CAT, with the largest effects in high-risk cancers. FVL has a marked impact on absolute CAT risk. Integrating genetic variants with clinical predictors can improve personalized thromboprophylaxis strategies.</p>
9 Authors
- Hannah Stevens
- William W H Ho
- Manika Singh
- Rodrigo Canovas
- Ruidong Xiang
- Huyen Tran
- Fumihiko Takeuchi
- Karlheinz Peter
- James D McFadyen
1 Application
| Application ID | Title |
|---|---|
| 55469 | Aetiology and prediction of cardiometabolic diseases, their comorbidities and complications |
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