已入深夜,您辛苦了!由于当前在线用户较少,发布求助请尽量完整地填写文献信息,科研通机器人24小时在线,伴您度过漫漫科研夜!祝你早点完成任务,早点休息,好梦!

Validation of the International Prognostic Score for Thrombosis in Essential Thrombocythemia (IPSET) in Patients with Pre-Fibrotic Primary Myelofibrosis

原发性血小板增多症 医学 骨髓纤维化 内科学 真性红细胞增多症 血栓形成 单变量分析 国际预后积分系统 一致性 胃肠病学 比例危险模型 阿那格雷内酯 肿瘤科 多元分析 骨髓增生异常综合症 骨髓
作者
Paola Guglielmelli,Alessandra Carobbio,Elisa Rumi,Valerio De Stefano,Lara Mannelli,Francesco Mannelli,Giada Rotunno,Giacomo Coltro,Silvia Betti,Chiara Cavalloni,Maria Chiara Finazzi,Jüergen Thiele,Mario Cazzola,Alessandro Maria Vannucchi,Tiziano Barbui
出处
期刊:Blood [Elsevier BV]
卷期号:134 (Supplement_1): 1657-1657
标识
DOI:10.1182/blood-2019-124302
摘要

Introduction. Prefibrotic myelofibrosis (pre-PMF) is a unique entity in the 2016 WHO classification of myeloproliferative neoplasms with distinct clinical phenotype and outcome [Guglielmelli P, Blood 2017]. Compared to essential thrombocythemia (ET), pre-PMF is characterized by more pronounced disease manifestations, adverse mutation profile and worse outcome. Previous studies [Rumi E, Oncotarget 2017] showed that patients (pts) with pre-PMF present a risk of vascular events similar to ET. However, no studies performed a comprehensive assessment of risk factors for thrombosis in pre-PMF. The current study aimed to identify risk factors for thrombosis and bleeding in a large series of pre-PMF pts and explore the effectiveness of contemporary prognostic models developed specifically for ET. Patients and Methods. The study included 382 pre-PMF pts, diagnosed by 2016 WHO criteria, referred by 4 Italian Centers. Previously published methods were used to genotype JAK2, MPL, CALR, EZH2, ASXL1, IDH1/2 and SRSF2; a high molecular risk (HMR) category was defined according to Vannucchi A, [Leukemia 2013]. Thrombosis‐free survival (TFS) was determined from diagnosis to the first thrombotic event. Pts were grouped according to the conventional risk stratification system [Barbui T, JCO 2011], IPSET‐thrombosis [Barbui T, Blood 2012] and revised IPSET‐thrombosis [Barbui T, BCJ 2015]. Cox-regression model was used for univariate analysis. Harrell's concordance (C) statistic was calculated to measure the incremental accuracy of multivariable models sequentially adjusted for new predictors of thrombotic risk. A P <0.05 was considered statistically significant. Results. At diagnosis, 65 pts (17%) experienced major thrombotic events which included 35 (9%) arterial and 31 (8%) venous thromboses. With a median follow-up of 6.9 y (range 0.08-32.6), 56 (15%) pts developed an arterial or venous thrombotic event, with a total incidence rate of 1.99% pts/year (pt-y); 30 (8%) were arterial and 28 (7%) venous events with incidence rate of 1.00% pt-y and 0.95% pt-y, respectively. Splanchnic vein thrombosis (SVT) represented the most frequent venous events before/at diagnosis (26%). During the follow-up, 16% and 8% of pts experienced myelofibrotic or leukemic progression, and 105 (27%) died, with incidence rate of 2.05% pt-y, 0.95% pt-y and 3.41% pt-y, respectively. In univariate analysis, factors significant for arterial thrombosis after diagnosis were age >65y (HR 2.88; P=0.005), WBC>10x109/L (HR 2.43; P=0.026), presence of >1 generic CV risk factor (HR 2.16; P=0.047), JAK2V617F (HR 3.35; P=0.027) and HMR status (HR 13.1; P=0.027). Conversely, only history of previous thrombosis (HR 3.06; P=0.005) and previous venous event (HR 5.53; P<0.0001) retained significance for predicting venous thrombosis. Pts were effectively stratified according to IPSET and conventional risk model. The risk of thrombosis in IPSET low-, intermediate-, and high-risk categories was 0.67%, 2.05% and 2.95% pt-y, and 1.47% pt-y and 2.71% pt-y in 2-tiered thrombotic risk model. (Figure 1); in revised-IPSET, 0.54%, 2.23%, 2.44% and 2.69 %pt-y in the very low, low, intermediate- and high-risk category. When WBC>10x109/L or HMR variables were incorporated into IPSET model, the C-statistic increased significantly for the prediction of arterial events: from baseline value of 0.68 to 0.74 adding WBC and 0.91 HMR status. The proportion of pts who experienced major bleeding was 3% prior/at diagnosis,and 7% during follow-up, with total incidence rate of 0.94% pt-y. In univariate analysis, predictors for major bleeding during follow-up were age >75y (HR 3.34; P=0.011), WBC>13x109/L (HR 2.33; P=0.035), presence of >1 generic CV risk factor (HR 2.41; P=0.035), particularly hypertension (HR 2.63; P=0.016) and grade-1 fibrosis (HR 2.28; P=0.05). High platelet count and treatment, including antiplatelet and anticoagulant drugs, did not reach statistical significance. Conclusions. Overall, this study identified independent risk factors for major thrombosis and bleeding in pre-PMF. Of interest, we report that HMR status predicted for arterial thrombosis during the follow-up. Pre-PMF pts showed remarkably high rate of venous thrombosis, mostly represented by SVT. The 3-tiered IPSET prognostic model for thrombosis reliably predicted occurrence of thrombotic events in pre-PMF and should be considered as standard reference. Figure 1 Disclosures Rumi: novartis: Honoraria, Research Funding. Thiele:Shire: Research Funding; Incyte: Consultancy, Honoraria, Other: Remuneration, Research Funding; Sanofi: Consultancy, Honoraria, Other: Remuneration; Novartis: Consultancy, Honoraria, Other: Remuneration, Research Funding; AOP Orphan Pharmaceuticals: Consultancy, Research Funding. Vannucchi:Incyte: Membership on an entity's Board of Directors or advisory committees; Celgene: Membership on an entity's Board of Directors or advisory committees; Novartis: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Italfarmaco: Membership on an entity's Board of Directors or advisory committees; CTI BioPharma: Membership on an entity's Board of Directors or advisory committees, Speakers Bureau.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
2秒前
汉堡包的应助被清爽翩跹采纳,获得10
5秒前
NiceSunnyDay完成签到 ,获得积分10
7秒前
17289yuan完成签到,获得积分20
9秒前
Maple完成签到,获得积分10
11秒前
FadedTulips完成签到 ,获得积分10
13秒前
13秒前
14秒前
14秒前
今天统一了吗完成签到 ,获得积分10
15秒前
16秒前
尊敬的苡发布了新的文献求助10
17秒前
KOKORO发布了新的文献求助20
17秒前
xiatian完成签到 ,获得积分10
17秒前
所所的应助被白萝卜采纳,获得10
17秒前
呆萌井完成签到,获得积分10
18秒前
今天完成签到,获得积分10
18秒前
19秒前
19秒前
Piper发布了新的文献求助10
19秒前
19秒前
20秒前
chenhaoran完成签到,获得积分10
22秒前
23秒前
window1000发布了新的文献求助10
24秒前
25秒前
huicheng的应助被陌黎采纳,获得30
26秒前
Ventus发布了新的文献求助10
27秒前
Destiny完成签到,获得积分10
29秒前
29秒前
31秒前
健壮的从寒完成签到,获得积分10
32秒前
西西米露完成签到,获得积分10
33秒前
许靓仔完成签到,获得积分10
33秒前
冷酷惠完成签到 ,获得积分10
33秒前
34秒前
Akim的应助被KOKORO采纳,获得10
34秒前
35秒前
Piper发布了新的文献求助10
36秒前
Ventus完成签到,获得积分10
37秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Energie-Contracting 1500
Klimaschutzrecht durch den Energiesektor im Mehrebenensystem – Ein Rechtsvergleich 1000
Représentation chimique de la structure des kérogènes et des asphaltènes en fonction de leur origine et de leur degré d'évolution 900
Oncology Clinical Trials: Successful Design, Conduct, and Analysis, Second Edition 800
Ecotourism 400
Analytical Separation Science 300
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 计算机科学 工程类 有机化学 化学工程 生物化学 物理 复合材料 内科学 催化作用 光电子学 人工智能 细胞生物学 无机化学 物理化学 数学
热门帖子
关注 科研通微信公众号,转发送积分 8065705
求助须知:如何正确求助?哪些是违规求助? 9488260
关于积分的说明 21346173
捐赠科研通 7634078
什么是DOI,文献DOI怎么找? 3397674
关于科研通互助平台的介绍 2527663
邀请新用户注册赠送积分活动 2435634