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A B S T R A C T Thrombotic events are a major cause of morbidity and mortality in cancer. selleckchem While the association of venous thromboembolic events with cancer is well documented, in recent years arterial events (i.e. acute myocardial infarction and ischemic strokes) have also emerged as relatively common complications among cancer patients. In hematological malignancies incorporating a heterogeneous group of diseases, the prediction of thrombosis occurrence and/or recurrence is challenging, due to unique disease characteristics. Furthermore, the treatment of thrombosis in these patients is often complicated because of disease- or therapy-related thrombocytopenia. In addition, patients with hematological cancers are poorly represented in randomized control clinical trials; hence, evidence-based guidelines are limited. This review will discuss the incidence of venous and arterial thrombotic events in common myeloid and lymphoproliferative diseases. Several new mechanisms contributing to cancer- associated thrombosis will be elaborated. The complicated issue of risk assessment and management of venous thrombosis in patients with hematological malignancies will be delineated.A B S T R A C T Important progress has been made in the development of risk assessment models (RAM) for the identification of outpatients on anticancer treatment at risk of venous thromboembolism (VTE). Since the breakthrough publication of the original Khorana risk score (KRS) more than 10 years ago, a new generation of KRS-based scores have been developed, including the Vienna Cancer and Thrombosis Study, PROTECHT, CONKO, ONCOTEV, TicOnco and the CATS/MICA score. Among these the CATS/MICA score showed that a simplified score composed of only two calibrated predictors, the type of cancer and the D-dimer levels, offers a user-friendly tool for the evaluation of cancer-associated thrombosis (CAT) risk. The COMPASS-CAT score is the first that introduced a more synthetic approach of risk evaluation by combining cancer-related predictors with patient comorbidity in a score which is designed for the types of cancer frequently seen in the community (i.e. breast, lung colon or ovarian cancers) and has been externally validated in independent studies. The Throly score is registered as part of the same group as it has a similar structure to the COMPASS-CAT score and is applicable in patients with lymphoma. The incorporation of specific biomarkers of hypercoagulability to the RAM for CAT offers the possibility to perform a precision medicine approach in the prevention of CAT. The improvement of RAM for CAT with artificial intelligence methodologies and deep learning techniques is the challenge in the near future.Cancer patients have a four- to sevenfold increased risk of developing cancer-associated thrombosis (CAT), which is associated with a strong increase in morbidity and mortality. Not all cancer patients receive thromboprophylaxis as this may lead to adverse events in a cancer population that is already at increased risk for major bleedings. Different risk prediction models have been developed to identify cancer patients at high risk of developing CAT that may be selected for thromboprophylaxis. However, risk models using the currently established biomarkers and clinical parameters perform poorly, particularly when validated in independent cohorts. Discovery of new and better biomarkers are therefore urgently needed. This review describes how aberrations in the genetic profile of the tumor and host influence a hypercoagulable state, and explores how these can be used as novel biomarker to improve CAT risk prediction.Cancer patients present with abnormalities of coagulation tests, reflecting a hypercoagulable state, often asso- ciated with a high incidence of thrombotic complications and poor disease prognosis. Different degrees of blood clotting abnormalities are described in diverse cancers, depending on tumor types and stage. The mechanisms of hemostasis that are critically involved in thrombosis are also implicated in tumor progression, angiogenesis, and metastatic spread. In this review, we summarize the results of published studies and focus on ongoing research and future directions of clotting factors and clotting activation bioproducts as biomarkers for cancer disease diagnosis and in cancer risk prediction.

The mechanisms surrounding cancer-associated venous thromboembolism (VTE) are not well characterized. AVERT, a randomized placebo controlled thromboprophylaxis study in ambulatory cancer patients, provides a unique opportunity to gain insights into thrombotic mechanism(s).

All available citrated platelet-free plasma samples collected at the point of randomization from individuals enrolled in the AVERT study were evaluated for the expression of D-dimer, soluble P-selectin (sP- selectin), active plasminogen activator inhibitor 1 (aPAI-1), clot lysis time (CLT) and activated factor XIa-C1 inhibitor complex (FXIa-C1). We compared the differential expression of sP-selectin, aPAI-1, CLT and FXIa-C1 among individual tumor types with normal controls. We evaluated the impact of disease type (hematologic versus solid organ malignancy) and stage (metastatic versus non-metastatic) on individual biomarker expression.

We included 449 AVERT participants in this analysis. Baseline expression of the selected thrombosis biomarkers differed significantly by individual tumor type compared with normal controls. Levels of aPAI-1, CLT, FXIa-C1 and sP-selectin were significantly elevated in individuals with lymphoma compared to individuals with non-metastatic solid organ malignancies (p<0.05). Individuals with metastatic solid organ disease had elevated levels of D-dimer and sP-selectin compared to those with non-metastatic disease (p<0.05).

Among a cohort of ambulatory patients at intermediate to high risk of VTE, these exploratory findings suggest that baseline activation of coagulation and fibrinolysis pathways vary significantly by tumor type and disease stage.

Among a cohort of ambulatory patients at intermediate to high risk of VTE, these exploratory findings suggest that baseline activation of coagulation and fibrinolysis pathways vary significantly by tumor type and disease stage.