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The main venous thromboembolism (VTE) risk prediction model for ambulatory cancer patients is Khorana. Cancer thrombosis is associated with elevated thrombin generation. Its quantification is a promising method for evaluating patient's thrombotic profile.
This study aims to develop a predictive model of VTE risk in ambulatory cancer patients, combining thrombosis biomarkers (D-dimers and thrombin generation potential) with the Khorana score.
This is a prospective observational study that includes newly diagnosed cancer patients proposed for anti-tumor treatment (chemotherapy, immunotherapy or targeted therapies). Patients with disease progression are allowed if chemotherapy-free for 3 months. A 6-month mean incidence of VTE 6-10% is expected, requiring a sample size of 600 patients. Blood sample is collected at inclusion to analyze thrombosis biomarkers and blood count. The primary endpoint is the occurrence of symptomatic or incidental VTE within 6 months of inclusion. Models will follow a logistic approach with K-fold cross-validation (k=10). Model quality will be assessed with Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC). Decision for entering predictors in multivariate models will be based on p <.10 in the univariate analysis.
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The main aims will be the following:
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Lopes; Ferreira
Data sourced from clinicaltrials.gov
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