Thromboembolic risk in hematological malignancies

Deep vein thrombosis: a less noticed complication in hematologic malignancies and immunologic disorders

Deep vein thrombosis (DVT) is a common complication in hematologic malignancies and immunologic disorders that coagulation and inflammatory factors play a crucial role in its occurrence. The content used in this article has been obtained by PubMed database and Google Scholar search engine of English-language articles (1980-2019) using the "Deep vein thrombosis," "Hematologic malignancies," "Immunologic disorders" and "Treatment." Increased levels of coagulation factors, the presence of genetic disorders, or the use of thrombotic drugs that stimulate coagulation processes are risk factors for the development of DVT in patients with hematologic malignancies. Inflammatory and auto-anti-inflammatory factors, along with coagulant factors, play an essential role in the formation of venous thrombosis in patients with immunological disorders by increasing the recruitment of inflammatory cells and adhesion molecules. Therefore, anti-coagulants in hematologic malignancies and immunosuppressants in immune disorders can reduce the risk of developing DVT by reducing thrombotic and inflammatory activity. Considering the increased risk of DVT due to impaired coagulation and inflammation processes, analysis of coagulation and inflammatory factors have prognostic values in patients with immunologic deficiencies and hematologic malignancies. Evaluation of these factors as diagnostic and prognostic biomarkers in the prediction of thrombotic events could be beneficial in implementing effective treatment strategies for DVT.

Prediction of venous thromboembolism in newly diagnosed patients treated for lymphoid malignancies: validation of the Khorana Risk Score

The utility of the venous thromboembolism (VTE) risk assessment model known as the Khorana Risk Score (KRS) in patients with lymphoid malignancies receiving outpatient chemotherapy is not defined. We evaluated the association of the KRS with VTE in patients treated for diffuse large B cell lymphoma (DLBCL) or Hodgkin lymphoma (HL). Retrospective analyses were performed in 428 patients, 241 of whom were newly diagnosed with DLBCL and 187 of whom had HL. During the initial therapy, 64 (15%) patients developed VTE and 56 died during follow-up. More VTE events occurred in patients with DLBCL than in patients with HL. According to the KRS, 364 (85%) and 64 (15%) patients were considered to be at intermediate risk and high risk of VTE development, respectively. The high-risk KRS patients were more often diagnosed with HL than DLBCL (19 vs. 10%, P = 0.0143). The KRS did not discriminate between high- and intermediate-risk patients with respect to VTE occurrence (17 vs. 15%, P = 0.5868). In our patients, the KRS did not adequately predict VTE (positive predictive value 15%, negative predictive value 82% and C statistic 0.51). In the multivariate analysis, bulky disease (OR 2.34; 95% CI 1.62-3.36, P < 0.0001), poor prognostic disease (OR 1.32; 95% CI 1.01-1.74, P = 0.049) and DLBCL histological subtype (OR 1.61; 95% CI 1.17-2.19, P = 0.003) were all significantly associated with the VTE development. In this cohort of patients with lymphoid malignancies, the KRS did not adequately stratify or predict VTE events in patients at a higher risk of VTE. This finding suggests the need for the development of a disease-specific VTE assessment model.

Identification of target gene of venous thromboembolism in patients with lymphoma via microarray analysis

Patients with lymphoma are at high risk of developing venous thromboembolism (VTE). The purpose of the present study was to identify the target gene associated with VTE for patients with lymphoma. Microarray data was downloaded from the gene expression omnibus database (GSE17078), which comprised the control group, 27 normal blood outgrowth endothelial cell (BOEC) samples, and the case group, 3 BOEC samples of venous thrombosis with protein C deficiency. Differentially expressed genes (DEGs) were identified by the Limma package of R. Gene ontology (GO) and Kyoto encyclopedia of genes and genomes (KEGG) pathway analyses were performed via the database for annotation, visualization and integrated discovery. Differentially coexpressed pairs were identified by the DCGL package of R. The subsequent protein-protein interaction (PPI) networks and gene coexpression networks were constructed by the Search Tool for the Retrieval of Interacting Genes/Proteins database, and were visualized by Cytoscape software. A total of 110 DEGs were obtained, including 73 upregulated and 37 downregulated genes. GO and KEGG pathway enrichment analyses identified 132 significant GO terms and 9 significant KEGG pathways. In total, 97 PPI pairs for PPI network and 309 differential coexpression pairs for the gene coexpression network were obtained. Additionally, the connective tissue growth factor (CTGF) gene was closely connected with other genes in the two networks. A total of 2 KEGG pathways were associated with VTE and CTGF may be the target gene of VTE in patients with lymphoma. The present study may identify the molecular mechanism of VTE, but additional clinical study is required to validate the results.