Department of Malignant Hematology, H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA.
Leuk Lymphoma. 2022 Jun;63(6):1281-1291. doi: 10.1080/10428194.2021.2018579. Epub 2021 Dec 21.
Myelodysplastic syndromes (MDS) form a clinically and molecularly heterogeneous disease group. Precise risk stratification remains crucial for choosing optimal management strategies. Several conventional prognostic scoring systems have been developed and validated in the MDS population. These risk models divide patients into prognostic subgroups based on clinical and cytogenetic characteristics. Lack of dynamicity, variable risk estimate across models, and heterogeneity within intermediate-risk group are the limitations of traditional models like IPSS-R, with questionable relevance of these scoring systems in treated MDS patients. Recent progress in next-generation sequencing techniques has improved understanding of the distribution and prognostic importance of recurrent genetic mutations in MDS. Early studies have suggested that incorporating mutations in risk stratification could supplement IPSS-R in further refining the model's performance in predicting overall survival and risk of transformation to acute myeloid leukemia and should translate into a molecularly driven prognostication approach in the near future.
骨髓增生异常综合征（MDS）是一组临床表现和分子特征均具有异质性的疾病。精确的风险分层对于选择最佳的治疗策略仍然至关重要。已经在 MDS 患者中开发和验证了几种传统的预后评分系统。这些风险模型根据临床和细胞遗传学特征将患者分为预后亚组。传统模型（如 IPSS-R）的局限性在于缺乏动态性、不同模型之间的风险估计差异以及中间风险组内的异质性，这些评分系统在治疗后的 MDS 患者中的相关性值得怀疑。下一代测序技术的最新进展提高了人们对 MDS 中反复出现的遗传突变的分布和预后意义的认识。早期研究表明，将突变纳入风险分层中可以补充 IPSS-R，进一步提高该模型预测总生存期和向急性髓系白血病转化风险的性能，并且在不久的将来应该转化为一种基于分子的预后方法。
