Purpose: Venous thromboembolism (VTE) is a leading cause of death among patients with cancer. The Khorana score was developed for assessing the risk of VTE in outpatients with cancer receiving chemotherapy, but its accuracy in identifying patients at high risk has been questioned. The aim of this study was to develop and validate a clinical-genetic score that improves the assessment of VTE risk in oncology outpatients within 6 months of diagnosis.
Methods: The new score was developed using the data of 364 outpatients belonging to the Spanish ONCOTHROMB 12-01 population. In this cohort, clinical data associated with the risk of VTE were collected at the time of diagnosis, including the Khorana score. These patients were also genotyped for the 51 genetic variants known to be associated with VTE. Multivariate logistic regression was performed to determine the weight of each genetic and clinical variable in relation to VTE risk, allowing a clinical-genetic risk score (the ONCOTHROMB score) to be developed. The Khorana and the ONCOTHROMB scores were then compared via the area under the receiver operating characteristic curve (AUC), calibration, and the number of patients needed to treat. The new score was then validated in a study of 263 patients in the Vienna Cancer and Thrombosis Study population.
Results: Nine genetic variants, tumor site, TNM stage, and a body mass index of > 25 kg/m were found to be associated with VTE and were used to build the ONCOTHROMB score, which better predicted the overall risk of VTE than did the Khorana score (AUC, 0.781 0.580; < .001). Similar AUC results were recorded in the validation study the Vienna Cancer and Thrombosis Study cohort involving patients with the same type of tumor (AUC for the ONCOTHROMB score the Khorana score: 0.686 0.577; < .001) and with all type of tumors (AUC for the ONCOTHROMB score the Khorana score: 0.720 0.561; < .0001).
Conclusion: The ONCOTHROMB score for VTE risk in outpatients with cancer, which takes into account both clinical and genetic variables, better identifies patients who might benefit from primary thromboprophylaxis than does the Khorana score.
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http://dx.doi.org/10.1200/JCO.22.00255 | DOI Listing |
J Blood Med
December 2024
Department of Internal Medicine, Faculty of Medicine, Universitas Airlangga, Surabaya, Indonesia.
Gallbladder adenocarcinoma has a high mortality rate, with approximately 1.7% cancer-related deaths worldwide. Cancer-associated thrombosis (CAT), including deep vein thrombosis (DVT), can significantly increase the risk of mortality within cancer patients, especially in pancreatic, brain, and intra-abdominal cancers, as well as in advanced and metastatic cancers.
View Article and Find Full Text PDFCancer Med
December 2024
Department of Hematology, The Second Affiliated Hospital of Xi'an Jiaotong University, Xi'an, Shaanxi, China.
Background: Venous thromboembolic events (VTEs) are the second-leading cause of death in cancer patients, with an incidence of 5%-17% in lymphoma patients, particularly higher in those with non-Hodgkin lymphoma (NHL). Existing risk assessment models (RAMs) like the Khorana and ThroLy scores have limitations and are inadequately validated for NHL patients. Coagulation markers such as D-dimer, thrombin-antithrombin complex (TAT), and thrombomodulin (TM) show a potential predictive value for cancer-associated VTE but lack extensive research in NHL.
View Article and Find Full Text PDFJ Blood Med
December 2024
Department of Pathology, Kampala International University Western Campus, Ishaka, Uganda.
Vascular
December 2024
Department of Surgery, Faculty of Medicine, Chiang Mai University, Chiang Mai, Thailand.
Breast Cancer
November 2024
Chongqing Cancer Multi-Omics Big Data Application Engineering Research Center, Chongqing University Cancer Hospital, Chongqing, 400030, China.
Objective: The incidence of venous thromboembolism (VTE) is significantly elevated in breast cancer patients, with a three-to-fourfold increase, and further escalates to sixfold in those undergoing chemotherapy. This study aims to identify the risk factors for VTE and develop a Nomogram risk prediction model distinct from the traditional Khorana score.
Methods: Univariate Cox regression analysis assessed the impact of each variable on the occurrence of VTE, while stepwise multivariate Cox regression analysis identified independent predictors.
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