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

IF 4.6 Q2 MATERIALS SCIENCE, BIOMATERIALS ACS Applied Bio Materials Pub Date : 2024-01-01 DOI:10.1177/10760296241263099
Pirun Saelue, Patuma Sinthujaroen, Supaporn Suwiwat, Paramee Thongsuksai
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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.

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基于表观遗传调节器突变的血栓形成预测模型--利用复发事件的生存分析法预测重要血小板增多症患者的血栓形成
导言:原发性血小板增多症(ET)涉及巨核细胞和血小板的增殖,与血栓形成风险增加有关。我们旨在评估表观遗传调节因子突变患者的血栓形成风险,并建立一个模型来预测 ET 的血栓形成:这项队列研究纳入了2002年1月至2019年12月期间在Songklanakarind医院确诊的年龄大于15岁的ET患者。利用新一代测序技术确定了25个靶基因突变,包括体细胞驱动基因突变(JAK2、CALR、MPL)、表观遗传调节基因突变(TET2、DNMT3A、IDH1、IDH2、TET2、ASXL1、EZH2、SF3B1、SRSF2)以及与骨髓肿瘤相关的其他基因。根据临床情况和影像学检查结果确认血栓事件,并使用五种生存模型和复发事件法分析血栓风险:96名患者入选,中位随访时间为6.91年。其中,15 名患者共发生了 17 次动脉血栓事件。JAK2突变和IDH1突变患者发生血栓事件的频率最高,体细胞驱动基因突变(17.3%)和表观遗传调节基因突变(100%)患者发生血栓事件的频率最高。10年无血栓生存率为81.3%(95%置信区间:72.0-91.8%)。在所有模型的多变量分析中,IDH1突变都是血栓风险的重要因素。Prentice、William和Peterson(PWP)间隙时间模型是最合适的预测模型:结论:PWP间隙时间模型是预测ET患者血栓风险的良好模型。IDH1突变是血栓形成的重要风险因素;然而,样本量更大的进一步研究应能证实这一点并提供更多见解。
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来源期刊
ACS Applied Bio Materials
ACS Applied Bio Materials Chemistry-Chemistry (all)
CiteScore
9.40
自引率
2.10%
发文量
464
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