Thrombotic Prediction Model Based on Epigenetic Regulator Mutations in Essential Thrombocythemia Patients Using Survival Analysis in Recurrent Events

Abstract

Introduction Essential thrombocythemia (ET) involves the proliferation of megakaryocytes and platelets and is associated with an increased risk of thrombosis. We aimed to evaluate thrombotic risks in patients with epigenetic regulator mutations and generate a model to predict thrombosis in ET. Materials and Methods This cohort study enrolled patients aged > 15 years diagnosed with ET at the Songklanakarind Hospital between January 2002 and December 2019. Twenty-five targeted gene mutations, including somatic driver mutations ( JAK2, CALR, MPL ), epigenetic regulator mutations ( TET2, DNMT3A , IDH1 , IDH2 , TET2 , ASXL1, EZH2 , SF3B1 , SRSF2 ) and other genes relevant to myeloid neoplasms, were identified using next-generation sequencing. Thrombotic events were confirmed based on clinical condition and imaging findings, and thrombotic risks were analyzed using five survival models with the recurrent event method. Results Ninety-six patients were enrolled with a median follow-up of 6.91 years. Of these, 15 patients experienced 17 arterial thrombotic events in total. Patients with JAK2 mutation and IDH1 mutation had the highest frequency of thrombotic events with somatic driver mutations (17.3%) and epigenetic regulator mutations (100%). The 10-year thrombosis-free survival rate was 81.3% (95% confidence interval: 72.0-91.8%). IDH1 mutation was a significant factor for thrombotic risk in the multivariate analysis for all models. The Prentice, William, and Peterson (PWP) gap-time model was the most appropriate prediction model. Conclusions The PWP gap-time model was a good predictive model for thrombotic risk in patients with ET. IDH1 mutation was significant risk factors for thrombosis; however, further studies with a larger sample size should confirm this and provide more insight.