Thrombophilia gene mutations predict venous thromboembolism in ambulatory cancer patients receiving chemotherapy

Genetic factors, risk prediction and AI application of thrombotic diseases

In thrombotic diseases, coagulation, anticoagulation, and fibrinolysis are three key physiological processes that interact to maintain blood in an appropriate state within blood vessels. When these processes become imbalanced, such as excessive coagulation or reduced anticoagulant function, it can lead to the formation of blood clots. Genetic factors play a significant role in the onset of thrombotic diseases and exhibit regional and ethnic variations. The decision of whether to initiate prophylactic anticoagulant therapy is a matter that clinicians must carefully consider, leading to the development of various thrombotic risk assessment scales in clinical practice. Given the considerable heterogeneity in clinical diagnosis and treatment, researchers are exploring the application of artificial intelligence in medicine, including disease prediction, diagnosis, treatment, prevention, and patient management. This paper reviews the research progress on various genetic factors involved in thrombotic diseases, analyzes the advantages and disadvantages of commonly used thrombotic risk assessment scales and the characteristics of ideal scoring scales, and explores the application of artificial intelligence in the medical field, along with its future prospects.

Inherited thrombophilia gene mutations and risk of venous thromboembolism in patients with cancer: A systematic review and meta-analysis

In the general population, individuals with an inherited thrombophilia have a higher risk of thrombosis, but the effect of inherited thrombophilia on the risk of cancer-associated venous thromboembolism (VTE) remains controversial. Our objective was to determine the risk of VTE in cancer patients with inherited thrombophilia. We conducted a systematic review and meta-analysis of studies reporting on VTE after a cancer diagnosis in adult patients who were tested for inherited thrombophilia. In September 2022, we searched Medline, EMBASE, and Cochrane Central. Two reviewers screened the abstracts/full texts and assessed study quality using the Quality in Prognostic Studies tool. We used Mantel-Haenszel random-effects models to estimate pooled odds ratios (OR) of VTE and 95% confidence intervals (95%CI). We included 37 and 28 studies in the systematic review and meta-analysis, respectively. Most studies focused on specific cancer types and hematologic malignancies were rare. The risk of VTE was significantly higher in cancer patients with non-O (compared with O) blood types (OR: 1.56 [95% CI: 1.28-1.90]), Factor V Leiden, and Prothrombin Factor II G20210A mutations compared with wild types (OR: 2.28 [95% CI: 1.51-3.48] and 2.14 [95% CI: 1.14-4.03], respectively). Additionally, heterozygous and homozygous methylenetetrahydrofolate reductase C677T had ORs of 1.50 (95% CI: 1.00-2.24) and 1.38 (95% CI: 0.87-2.22), respectively. Among those with Plasminogen-Activator Inhibitor-1 4G/5G, Vascular Endothelial Growth Factor (VEGF) A C634G, and VEGF C2578A mutations, there was no significant association with VTE. In conclusion, this meta-analysis provided evidence that non-O blood types, Factor V Leiden, and Prothrombin Factor II G20210A mutations are important genetic risk factors for VTE in cancer patients.

Novel Insights in Venous Thromboembolism Risk Assessment Methods in Ambulatory Cancer Patients: From the Guidelines to Clinical Practice

Many cancer patients will experience venous thromboembolism (VTE) at some stage, with the highest rate in the initial period following diagnosis. Novel cancer therapies may further enhance the risk. VTE in a cancer setting is associated with poor prognostic, a decreased quality of life, and high healthcare costs. If thromboprophylaxis in hospitalized cancer patients and perioperative settings is widely accepted in clinical practice and supported by the guidelines, it is not the same situation in ambulatory cancer patient settings. The guidelines do not recommend primary thromboprophylaxis, except in high-risk cases. However, nowadays, risk stratification is still challenging, although many tools have been developed. The Khrorana score remains the most used method, but it has many limits. This narrative review aims to present the current relevant knowledge of VTE risk assessment in ambulatory cancer patients, starting from the guideline recommendations and continuing with the specific risk assessment methods and machine learning models approaches. Biomarkers, genetic, and clinical features were tested alone or in groups. Old and new models used in VTE risk assessment are exposed, underlining their clinical utility. Imaging and biomolecular approaches to VTE screening of outpatients with cancer are also presented, which could help clinical decisions.