Cancer is a diverse group of potentially fatal diseases characterised by uncontrolled cell growth, which can manifest in any part of the body. Early detection and treatment are crucial for improving survival rates.

Cancer is also associated with an increased risk of thromboembolism. After cancer itself, venous thromboembolism (VTE) is the second most common cause of death in patients with active cancer (1). One in five patients with cancer experiences a thromboembolic event, and one in five patients with VTE has cancer. The association between cancer and thrombosis has been demonstrated in many studies involving various cancer types and sites (2, 3).

The type of cancer, including the site at which the tumour develops, has a major impact on the thromboembolic risk profile, with cancers such as pancreatic and stomach cancer posing a very high thrombotic risk for patients. In addition to cancer type, many contributors to the VTE risk of patients with cancer have been described, ranging from patient characteristics to tumour- and treatment-related risk factors (Fig. 1).

Figure 1: Risk factors and predictors for VTE in patients with cancer. CAR-T cell = chimeric antigen receptor-T cell; TAT = thrombin-antithrombin complex; ETP = endogenous thrombin potential; VEGF = vascular endothelial growth factor; MPV = mean platelet volume.

Anticancer treatments and therapies have evolved and have dramatically improved survival rates in recent years. However, they can also carry a significant thrombotic risk, as described, for instance, for checkpoint inhibitor therapy (4) and long recognised for chemotherapy (5). Therefore, cancer- and treatment-related thrombotic risks require constant assessment and management to avoid potentially life-threatening complications following the diagnosis of cancer and the initiation of subsequent therapy.

Thrombotic risk assessment in cancer

Plasma D-dimer is a reliable and accessible laboratory parameter for assessing thrombosis. Consequently, the thrombotic risk prediction model Vienna CATScore uses plasma D-dimer levels to identify patients with cancer who have the highest thrombotic risk and may require antithrombotic measures, such as direct oral anticoagulation (3).

The Vienna CATScore uses tumour site and D-dimer levels as continuous variables to predict VTE risk. This prediction model and the older, well-known Khorana Score (6) have recently been compared and validated in prospective clinical studies (7, 8). Although both models demonstrated efficacy in identifying patients at increased risk of VTE and usefulness in clinical practice, the CATScore showed better discriminatory capacity for VTE (7).

For patients with cancer identified as having a high thrombotic risk, the American Society of Hematology (ASH) has provided guidance and recommendations on when and how to implement thromboprophylaxis using low-molecular-weight heparins (LMWH). Direct oral anticoagulants (DOACs) are also recommended anticoagulants (9).

(https://catscore.shinyapps.io/catscore/)

References

[1] Ay C, et al. (2017): Cancer-associated venous thromboembolism: Burden, mechanisms, and management. Thromb Haemost 2017; 117(02): 219–230. doi: 10.1160/TH16-08-0615

[2] Kim AS, et al. (2020): Mechanisms and biomarkers of cancer-associated thrombosis. Transl Res. 2020 Nov; 225: 33–53. doi: 10.1016/j.trsl.2020.06.012.

[3] Pabinger I, et al. (2018): A clinical prediction model for cancer-associated venous thromboembolism: a development and validation study in two independent prospective cohorts. Lancet Haematol. 2018 Jul;5(7): e289–e298. doi: 10.1016/S2352-3026(18)30063-2.

[4] Fawaz H, et al. (2025): Exploring the Emerging Association Between Immune Checkpoint Inhibitors and Thrombosis. J. Clin. Med. 2025, 14(10): 3451. doi: 10.3390/jcm14103451.

[5] Grover SP, et al. (2021): Cancer Therapy–Associated Thrombosis. Arterioscler Thromb Vasc Biol. 2021 Apr;41(4): 1291–1305. doi: 10.1161/ATVBAHA.120.314378.

[6] Khorana AA, et al. (2008): Development and validation of a predictive model for chemotherapy-associated thrombosis. Blood. 2008 May 15;111(10): 4902–4907. doi: 10.1182/blood-2007-10-116327.

[7] Verzeroli C, et al. (2023): Utility of the Khorana and the new-Vienna CATS prediction scores in cancer patients of the HYPERCAN cohort. J Thromb Haemost. 2023 Jul;21(7): 1869–1881. doi: 10.1016/j.jtha.2023.03.037.

[8] Englisch C, et al. (2025): The Vienna CATScore for predicting cancer-associated venous thromboembolism: an external validation across multiple time points. ESMO Open. 2025 Feb;10(2): 104130. doi: 10.1016/j.esmoop.2024.104130.

[9] Lyman GH, et al. (2021): American Society of Hematology 2021 guidelines for management of venous thromboembolism: prevention and treatment in patients with cancer. Blood Adv. 2021 Feb 23;5(4): 927–974. doi: 10.1182/bloodadvances.2020003442.

SEED: The clinical utility of D-dimer testing in cancer patients

An extrinsic or intrinsic trigger of the coagulation cascade concludes in the generation of thrombin, which then converts fibrinogen into fibrin monomers comprised of a so-called ‘E’ domain and two ‘D’ domains. The fibrin monomers are covalently crosslinked and consequently stabilised via thrombinactivated factor XIII to form an insoluble and stable fibrin clot.

Download

Haemostasis

Expect the best

See our haemostasis solutions

Scientific Calendar 2026

See already now what’s coming for the whole year

Explore more