COMPARATIVE ANALYSIS OF PREDICTIVE MODELS FOR THROMBOEMBOLIC EVENTS IN LYMPHOMA PATIENTS

Abstract

Introduction: Actual guidelines recommend Padua and Khorana score for thromboembolic (TE) risk estimation for cancer patients in general. These existing models are quite limited for designation of lymphoma patients for TE events, as their development is not based on features specific for hematological patients. The aim of this study was to compare diagnostic performance of these suggested predictive models, as well as Thrombosis lymphoma (Throly) score, developed by our group, which is more specific for lymphoma patients. Methods: The study population included all consecutive patients with a histological confirmed diagnosis of non-Hodgkin lymphoma (NHL), Hodgkin lymphoma (HL), and chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL), who were treated in the Lymphoma Departments of Clinical Center Serbia and Clinical Center Kragujevac. From January 2006 to December 2014, data were prospectively collected and entered into the institutional Lymphoma database. The study population was divided based on a split-sample random method into the model developing and validation cohorts. The ThroLy model was developed using data solely from a derivation cohort, which included 1236 patients. Variables were evaluated by univariate logistic regression analysis, while the model was developed using a stepwise multivariate logistic regression analysis. Once a final model was defined, patients were divided into low risk and at risk groups. The final model was assessed in the validation cohort (584 patients). The studied population was also divided, based on Khorana and Padua score, into low risk and at risk groups. Results: The incidence of thromboembolism was 81 (5.3%) in the newly diagnosed patients and 18 (6.2%) in relapsed patients. Overall, 35.4% (35/99) of the patients with thromboembolism experienced the event before the start of chemotherapy. The majority of patients (64.6%) had TE events during chemotherapy or within 3 months after chemotherapy. Cohorts were balanced regarding the incidence of events (5.3% and 5.5% in derivation and validation cohort, respectively). For patients classified at risk according to ThroLy score in derivation cohort, the model produced negative predictive value (NPV) of 98.5%, positive predictive value (PPV) of 25.1%, sensitivity of 75.4%, and specificity of 87.5%. In validation cohort PPV for Throly score was 28.9%. Padua and Khorana score had PPV of 15.5% and 14.8% in derivation, and 11.5% and 14.8% in validation cohort, respectively. Conclusion: Lymphoma patients are at increased risk of thromboembolic events but thromboprophylaxis in these patients is largely underused. ThroLy score is more specific for lymphoma patients than suggested Padua and Khorana score, but external validation in large prospective cohort studies is required. Keywords: Hodgkin lymphoma (HL); non-Hodgkin lymphoma (NHL).