一种用于纤维化前骨髓纤维化生存预测和事件监测的多状态模型
A multistate model of survival prediction and event monitoring in prefibrotic myelofibrosis
原文发布日期:2020-10-14
DOI: 10.1038/s41408-020-00368-1
类型: Article
开放获取: 是
英文摘要:
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Among 382 patients with WHO-defined prefibrotic myelofibrosis (pre-PMF) followed for a median of 6.9 years, fibrotic or leukemic transformation or death accounts for 15, 7, and 27% of cases, respectively. A multistate model was applied to analyze survival data taking into account intermediate states that are part of the clinical course of pre-PMF, including overt PMF and acute myeloid leukemia (AML). Within this multistate framework, multivariable models disclosed older age (>65 years) and leukocytosis (>15 × 109/L) as predictors of death and leukemic transformation. The risk factors for fibrotic progression included anemia and grade 1 bone marrow fibrosis. The outcome was further affected by high molecular risk (HMR) but not driver mutations. Direct transition to overt PMF, AML, or death occurred in 15.2, 4.7, and 17.3% of patients, respectively. The risk of AML was the highest in the first 5 years (7%), but leveled off thereafter. Conversely, the probability of death from overt PMF or AML increased more rapidly over time, especially when compared to death in the pre-PMF state without disease progression. The probability of being alive with pre-PMF status decreased to 70 and 30% at 10 and 20 years, respectively. This study highlights the aspects of the clinical course and estimates of disease progression in pre-PMF.
在382名世界卫生组织定义的预纤维化骨髓纤维化(pre-PMF)患者中,中位随访时间为6.9年,纤维化或白血病转化或死亡分别占病例的15%、7%和27%。应用多状态模型分析生存数据,考虑了预-PMF临床过程中的中间状态,包括显性PMF和急性髓系白血病(AML)。在此多状态框架内,多变量模型揭示年龄较大(>65岁)和白细胞增多(>15×10^9/L)是死亡和白血病转化的预测因子。纤维化进展的风险因素包括贫血和1级骨髓纤维化。结果进一步受高危分子风险(HMR)影响,但不受驱动突变影响。直接转化为显性PMF、AML或死亡的患者分别占15.2%、4.7%和17.3%。AML风险在前5年最高(7%),但此后趋于平稳。相反,从显性PMF或AML死亡的概率随时间增加更快,尤其是与未疾病进展的pre-PMF状态死亡相比。存活且处于pre-PMF状态的概率在10年和20年分别降至70%和30%。本研究突出了预-PMF的临床过程方面并估计了疾病进展。
A multistate model of survival prediction and event monitoring in prefibrotic myelofibrosis
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