Dr. Lucy Norris

Venous thromboembolism(VTE) is the leading cause of non cancer death in cancer patients. Patients are particularly at risk during chemotherapy where rates of up to 20% have been reported. Guidelines recommend primary prophylaxis with direct oral anticoagulants(DOACs) in intermediate/high risk patients undergoing chemotherapy following risk assessment with a validated risk score(Khorana score). However, the Khorana score performs poorly in lung, ovarian and gastric cancers and relies on a single assessment at the start of therapy. The development of VTE is a dynamic process which cannot be accurately represented by a single risk assessment. Our data suggests that markers of procoagulant activity are implicated in chemotherapy associated VTE and could be measured serially as predictive biomarkers. This may provide a more effective method of identifying patients at risk of VTE and facilitate targeted prophylaxis. Prophylaxis with DOACs carries a risk of bleeding hence decisions regarding prophylaxis should be shared between doctor and patient. However, studies have shown that cancer patients receive limited information about VTE risk and tools to aid decision making in this area are lacking. Cost is also a consideration for both the health service and the patient. In this study we will: " measure procoagulant biomarker levels serially during chemotherapy as dynamic predictors of VTE. " investigate the prothrombotic mechanisms involved in chemotherapy associated VTE. " identify patient needs and priorities for shared decision making with regard to prophylaxis during chemotherapy " perform a cost benefit analysis of biomarker screening and targeted VTE prophylaxis during chemotherapy This study aims is to develop dynamic predictive biomarkers for VTE during chemotherapy and to understand patient priorities with regard to VTE prevention during chemotherapy. Identification of high risk patients and increased understanding or patient priorities and costs will lead to effective shared decision between doctor and patient ultimately reducing the burden of VTE in cancer.

Development of preliminary findings investigating the role of aPC pathway in the aetiology of ovarian cancer

Venous thromboembolism (VTE) is a common cause of death in patients with solid tumours. Cancer itself causes a hypercoagulable state, in addition chemotherapy and surgery enhance the risk. Gynaecological cancers have been associated with high rates of VTE which is excacerbated by pelvic surgery and chemotherapy. A recent study in our centre showed that one third of VTE in ovarian cancer patients occurs within 5 days of surgery despite heparin prophylaxis. Recently, clinical risk models have been developed to predict VTE in patients undergoing chemotherapy, these models have been shown to be more powerful when combined with haemostatic biomarkers. Thrombus formation is complex in cancer and is thought to result from a release of procoagulant material from the tumour combined with damage to the endothelium as a result of chemotherapy and surgery. Global tests of hypercoagulability which capture these effects are therefore attractive as determinants of thrombotic risk. Calibrated automated thrombograpy (CAT) is a recently developed global test which measures thrombin generation in plasma. Increased thrombin generation is predictive of VTE in a variety of clinical settings. The overarching aim of this project is to develop and validate a specific risk scoring model for VTE risk in gynaecological cancer patients using a combination of easily available clinical and laboratory parameters and haemostatic biomarkers. In a large population of gynaecological cancer patients, we will identify the key risk factors for VTE and use them to derive a risk score model. Based on our pilot data, we believe that a thrombin generation test may be a useful biomarker for VTE in gynaecological cancer. By understanding the mechanisms by which gynaecological cancer increases procoagulant activity, we will optimise a specific thrombin generation assay which when combined with the derived risk score model will accurately identify gynaecological cancer patients at high risk of VTE.