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Development and validation of a clinical prediction model for cancer-associated venous thromboembolism in two independent prospective cohorts
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Abstract
Background
Venous thromboembolism (VTE) is a frequent complication of cancer, however the risk is highly variable among individuals depending on various factors, including types of cancer. To enable a personalized risk prediction of VTE we developed and externally validated a clinical prediction model for cancer-associated VTE.
Methods
The prospective Vienna Cancer and Thrombosis Study (CATS, n=1,423) was used for model development, and the prospective Multinational cohort study to Identify Cancer patients at risk of VTE (MICA, n=832) was used for external validation. Primary outcome was objectively confirmed VTE at 6 months. The cumulative 6-month VTE risk was 5·7% in CATS (95% CI: 4·5-6·9), and 6·3% (95%CI: 4·7-8·2) in MICA. Tumor sites were categorized into low/intermediate, high, and very high VTE categories. Predictive variables were selected from a broad set of clinical and laboratory factors.
Findings
The final prediction model included two variables: tumor site category (hazard ratio for “high” vs. “low/intermediate”, and “very high” versus “high” VTE-risk tumor site=1·96 (95% CI: 1·41-2·72, p=0·0001). and D-Dimer (hazard ratio per doubling=1·32, 95% CI: 1·12-1·56, p=0·001). The C-Indices of the model were 0·66 (95%: 0·63-0·67) in internal validation (CATS), and 0·68 (95%: 0·62-0·74) in external validation (MICA), respectively. The clinical prediction model was adequately calibrated in both cohorts.
Interpretation
An externally-validated clinical prediction model incorporating only one clinical factor (tumor site category) and one biomarker (D-Dimer) predicts the risk of VTE in ambulatory patients with solid cancers. This simple model considerably improves on previous models for predicting cancer-associated VTE, and can aid physicians in selecting patients who will likely benefit from thromboprophylaxis.