Development and validation of a predictive model for chemotherapy-associated thrombosis

Abstract

Risk of venous thromboembolism (VTE) is elevated in cancer, but individual risk factors cannot identify a sufficiently high-risk group of outpatients for thromboprophylaxis. We developed a simple model for predicting chemotherapy-associated VTE using baseline clinical and laboratory variables. The association of VTE with multiple variables was characterized in a derivation cohort of 2701 cancer outpatients from a prospective observational study. A risk model was derived and validated in an independent cohort of 1365 patients from the same study. Five predictive variables were identified in a multivariate model: 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 100 g/L (10 g/dL) and/or use of erythropoiesis-stimulating agents, leukocyte count more than 11 × 109/L, and body mass index of 35 kg/m2 or more (1 point each). Rates of VTE in the derivation and validation cohorts, respectively, were 0.8% and 0.3% in low-risk (score = 0), 1.8% and 2% in intermediate-risk (score = 1-2), and 7.1% and 6.7% in high-risk (score ≥ 3) category over a median of 2.5 months (C-statistic = 0.7 for both cohorts). This model can identify patients with a nearly 7% short-term risk of symptomatic VTE and may be used to select cancer outpatients for studies of thromboprophylaxis.