费城阴性mpn、MDS/ mpn和MDS在最近世卫组织变化和将分子特征纳入预后工具的背景下:单一中心经验

N. Singh, Sujeet Kumar, Avinash Gupta
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引用次数: 0

摘要

引言:世卫组织第五版髓系肿瘤分类对MDS、MDS/ mpn和mpn的定义标准和分组进行了重大修改。最近发表的文献也引用了新的风险评分系统的重要性,通过将基因组分析与血液学和细胞遗传学特征相结合,以改善患者的预后歧视,并代表了临床决策的有价值的工具。目的:了解费城阴性mpn、MDS/ mpn和MDS在本组患者中的患病率和分子谱,评价其对患者诊断、风险分层和治疗决策的影响。方法:这项回顾性观察性研究包括所有新诊断的非费城阳性MPN、MDS和MPN/MDS患者,其中完整的基线诊断工作包括全血细胞计数、骨髓形态学和活检、细胞遗传学和分子研究。结果:在我们的队列患者中最常见的实体是原发性骨髓纤维化(32.8%),MDS(32.8%)和CMML(16.4%)。在PIMF中,50%的患者是JAK2-突变,30%是三阴性(JAK-, CALR-, MPL-)。mpn中常见的表观遗传修饰因子为ASXL1、TET2和IDH2。在我们的患者中,主要的CMML分子特征是NRAS、U2AF2、SETBP1、ASXL和SH2B3。世卫组织的变化和最近引入的分子评分模型对所有这些MPN和MDS/MPN患者的诊断和风险分层没有显著影响。然而,在MDS和PIMF患者中,最近的世卫组织分型加上IPSS-M和GIPSS评分分别可以细化风险组。结论:分子谱分析有助于更好地对所有组的患者进行风险分层,并有助于制定治疗决策。然而,在资源有限的情况下,根据分子特征对患者进行分层并不总是可能的,因此,DIPSS和IPSS-R等评分模型即使在今天也能在不影响高质量护理的情况下为患者提供适当的治疗。
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Philadelphia Negative MPNs, MDS/MPNs and MDS in the Context of Recent WHO Changes and Inclusion of Molecular Signatures into Prognostic Tools: A Single Centre Experience
Introduction: The fifth edition of WHO classification of myeloid neoplasms has introduced major changes in the defining criteria and grouping of MDS, MDS/MPNs and MPNs. Recently published literature has also cited the importance of new risk-scoring systems by integrating genomic profiling with hematologic and cytogenetic characteristics, in order to improve the prognostic discrimination of patients and represents a valuable tool for clinical decision-making. Aim: To find out the prevalence and molecular spectrum of Philadelphia-negative MPNs, MDS/MPNs and MDS in our subset of patients and henceforth to evaluate the impact on diagnosis, risk stratification and treatment decision-making of patients. Methods: This retrospective observational study included all newly diagnosed patients of non-Philadelphia positive MPNs, MDS, and MPN/MDS, in whom complete baseline diagnostic work-up was available including complete blood counts, bone marrow morphology and biopsy, cytogenetic and molecular studies. Results: The most frequent entities in our cohort of patients were primary myelofibrosis (32.8%), MDS (32.8%) and CMML (16.4%). In PIMF, 50% patients were JAK2- mutated while 30% were triple negative (JAK-, CALR-, MPL-). The commoner epigenetic modifiers among MPNs were ASXL1, TET2 and IDH2. The predominant CMML molecular signatures in our patients were NRAS, U2AF2, SETBP1, ASXL and SH2B3. There was no significant effect of WHO changes and recently introduced molecular scoring models on the diagnosis and risk stratification of all these MPN and MDS/MPN patients However, in MDS and PIMF patients, recent WHO subtyping plus IPSS-M & GIPSS scoring respectively enabled refining of risk groups. Conclusion: Molecular profiling helps in better risk stratification of patients across all groups as well as in making therapeutic decisions. However, in resource constrained settings, it is not always possible to stratify patients on the basis of molecular signatures and hence, scoring models such as DIPSS and IPSS-R holds their ground strongly even today for offering appropriate therapy to patients without compromising on quality care.  
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