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Using a Blood Test and Software Tool to Guide Treatment for Venous Thromboembolism

Trial Status: active

This clinical trial evaluates whether a special blood test can be used with an algorithmic software tool to predict the likelihood of venous thromboembolism (VTE) in cancer patients and to make recommendations about whether a patient can stop taking anticoagulant medications. VTE is a disorder in which a blood clot (called a thrombus) forms in a blood vessel and may travel to another site in the body, such as the lungs, via the blood stream. Patients with cancer are at risk of developing cancer-associated VTE and are commonly prescribed anticoagulants, though the optimal duration of anticoagulation therapy for cancer-associated VTE is unknown. Studies have shown that a special type of deoxyribonucleic acid (DNA) called circulating tumor DNA (ctDNA), which can be measured in a patient's blood, is associated with risk of developing VTE and may be predictive of whether or not a patient needs to continue on anticoagulation therapy. In this trial, patients have a VTE risk score calculated, based on a machine learning or artificial intelligence algorithm, using their ctDNA test results. An algorithm is a set of instructions that a computer system uses to learn from data, find patterns, and make predictions or decisions. Based on their risk score, patients may be instructed to continue or discontinue their anticoagulation therapy. This ctDNA algorithm-based risk score may be an effective way to predict future VTE and make recommendations regarding the need for anticoagulation therapy in patients with cancer.