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Biomarkers improve the risk scoring model for prediction of cancer-associated thrombosis
Abstract number: OC-TU-016
Ay1 C., Chiriac1 A.L., Dunkler2 D., Vormittag1 R., Simanek1 R., Quehenberger3 P., Zielinski4 C., Pabinger1 I.
11Department of Medicine I, Clinical Division of Haematology and Haemostaseology 22Core Unit for Medical Statistics and Informatics, Section of Clinical Biometrics 33Department of Medical and Chemical Laboratory Diagnostics 44Department of Medicine I, Clinical Division of Oncology, Medical University of Vienna, Vienna, Austria
How-to-cite Ay C, Chiriac AL, Dunkler D, Vormittag R, Simanek R, Quehenberger P, Zielinski C, Pabinger I. Biomarkers improve the risk scoring model for prediction of cancer-associated thrombosis. Journal of Thrombosis and Haemostasis 2009; Volume 7, Supplement 2: Abstract OC-TU-016
The risk of VTE in cancer patients is clearly increased. However, identifying patients that might benefit most from thromboprophylaxis is still a major challenge. Recently a risk scoring model for chemotherapy-associated VTE was developed (Khorana et al, Blood 2008;111:4902–7), incorporating clinical and laboratory parameters: site of cancer (2 points for very high risk site, 1 point for high risk site), platelet count of 350 × 109/L or more, hemoglobin less than 10 g/dL and/or use of erythropoiesis-stimulating agents, leukocyte count more than 11 × 109/L, and BMI of 35 kg/m2 or more (each 1 point). We have applied this model for prediction of cancer-associated VTE in our ongoing Vienna Cancer and Thrombosis Study (CATS), a prospective and observational cohort study of patients with newly diagnosed cancer or progression of disease after remission initiated in 2003. The risk model has been expanded including two new predictive variables previously identified in CATS: elevated soluble P-selectin (cut-off: 53.1 ng/mL) and elevated D-Dimer (cut-off: 1.44 μg/mL). Full data were available for 839 patients. During a median follow-up of 643 days, VTE occurred in 62 (7.4%) patients. In Kaplan–Meier analysis the groups according to the risk model were statistically significantly associated with occurrence of cancer-associated VTE in the CATS population (P < 0.001). The cumulative probability of developing VTE after 6 months was 1.5% in patients with score 0, 3.8% in those with score 1, 9.4% in those with score 2 and 17.7% in those with score ≥ 3. By adding elevated D-Dimer and elevated P-selectin to the risk model, the cumulative probability developing VTE after 6 months was 30.3% in patients with the highest score (score ≥ 5) as opposed to only 1.0% in patients with score 0. In conclusion, the risk scoring model by Khorana et al enables us to identify cancer patients at high or low risk of VTE. The predictive accuracy of the model can be considerably improved by including additional biomarkers such as P-selectin and D-Dimer.
Disclosure of interest: none declared.
To cite this abstract use the following format:
Journal of Thrombosis and Haemostasis 2007; Volume 5, Supplement 2: abstract number
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