PB1433 - Performance of established risk assessment models for the prediction of VTE in patients with cancer receiving systemic anti-cancer therapies – results from a contemporary perspective cohort study

Tuesday, June 25, 2024

13:45 – 14:45 ICT

Room: Exhibition Hall

Presenting Author(s)

NV

Nikola Vladic

PhD Student
Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna
Vienna, Wien, Austria

Co-Author(s)

Cornelia Englisch, MD

PhD Student
Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna
Vienna, Wien, Austria
Florian Moik

Physician
Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna
Graz, Steiermark, Austria
AB

Anna Berghoff

Professor
Division of Oncology, Department of Medicine I, Medical University of Vienna
Vienna, Wien, Austria
MP

Matthias Preusser

Professor
Division of Oncology, Department of Medicine I, Medical University of Vienna
Vienna, Wien, Austria
Ingrid Pabinger

Professor
Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna
Vienna, Wien, Austria
Cihan Ay, MD

Professor
Division of Hematology and Hemostaseology, Department of Medicine I, Medical University of Vienna
Vienna, Wien, Austria

Background: Patients with cancer face a substantial risk of venous thromboembolism (VTE). To identify patients with cancer at high risk of VTE and for implementing effective thromboprophylaxis, several risk assessment models have been previously developed. The development of novel anti-cancer therapies including immune checkpoint inhibitors (ICI) might affect VTE risk and risk prediction.

Aims: We aimed to evaluate the performance of five published risk assessment models in a prospective observational cohort study of patients with cancer initiating systemic anti-cancer therapies, including ICI.

Methods: The c-statistics for 6-months VTE risk discrimination of the Khorana, PROTECHT, COMPASS-CAT, CONKO, and the score by Ang Li et al. (JCO 2023) were calculated.

Results: 625 patients (51% women) with a median age of 61 (interquartile range [IQR]: 52-69) years were included. The most common cancer types were lung, (23.8%), breast (12.6%) and pancreatic (9.6%). The most frequent anti-cancer therapies initiated after study inclusion were chemotherapy (43.7%), combination of chemotherapy and ICI (17.6%), and ICI monotherapy (15%). At the time of inclusion, 390 (62.3%) patients had metastatic disease. During an observation period of 6 months, 55 patients were diagnosed with VTE (cumulative incidence 8.8%, 95% confidence interval [CI]: 6.5-11.1; figure 1). The discriminatory performance of all five scores was modest, with the best c-statistic value seen with the PROTECHT score, while the COMPASS-CAT score showed the lowest AUC value (c-statistics [95% CI]: PROTECHT: 0.6 [0.52-0.68], CONKO: 0.58 [0.5-0.66], Ang Li et al.: 0.58 [0.5-0.66], Khorana: 0.58 [0.5-0.66], and COMPASS-CAT: 0.56 [0.48-0.64]; Figure 2).

Conclusion(s): Previously reported risk scores demonstrated poor discriminatory performance in our contemporary cohort of patients with cancer initiating systemic anti-cancer therapies, including ICI. The modest discriminatory abilities of these models highlight the need for further optimization of VTE risk prediction in contemporary oncology patient populations, including those receiving novel anti-cancer therapies.