Prognostic indicators and scoring systems for predicting outcome in patients with myelodysplastic syndromes.

Carlo Aul, Aristoteles Giagounidis, Michael Heinsch, Ulrich Germing, Arnold Ganser
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Abstract

A number of clinical, laboratory, morphological and genetic factors are useful to predict the natural course of Myelodysplastic syndromes (MDS). The identification of these factors resulted in the development of scoring systems that aid to differentiate high risk patients from those with a better prognosis. At the initial approach towards a patient with MDS the clinician will take into account the individual's age and performance score, and the morphological characteristics of the peripheral blood and bone marrow, including number of dysplastic lineages and blast count, as proposed by the new World Health Organization classification. Some laboratory features like the neutrophil and platelet count and the lactate dehydrogenase levels are of additional independent prognostic importance. Finally, the karyotype of the malignant hematopoietic cells is a very strong prognostic variable and therefore mandatory in the assessment of patients with MDS. By using part of the above-mentioned factors, the International Prognostic Scoring System has proven reliable in grouping MDS patients into one of four risk categories and can be used in the stratification of patients in therapeutic trials. With the avenue of more sophisticated molecular techniques like gene expression profiling, it might become possible not only to predict the natural course of the disease more precisely, but also to identify patient populations that are prone to respond to specific drugs especially designed for specific genetic lesions.

预测骨髓增生异常综合征患者预后的预后指标和评分系统。
许多临床、实验室、形态学和遗传因素有助于预测骨髓增生异常综合征(MDS)的自然病程。这些因素的识别导致了评分系统的发展,有助于区分高风险患者和预后较好的患者。在初始治疗MDS患者时,临床医生将考虑患者的年龄和表现评分,以及外周血和骨髓的形态学特征,包括发育不良谱系的数量和原细胞计数,这些都是世界卫生组织提出的新分类。一些实验室特征,如中性粒细胞和血小板计数和乳酸脱氢酶水平是额外的独立预后的重要性。最后,恶性造血细胞的核型是一个非常强的预后变量,因此在MDS患者的评估中是强制性的。通过使用上述部分因素,国际预后评分系统已被证明可以可靠地将MDS患者分为四种风险类别之一,并可用于治疗试验中的患者分层。随着基因表达谱等更复杂的分子技术的发展,不仅可以更精确地预测疾病的自然病程,而且还可以确定容易对特定遗传病变的特定药物产生反应的患者群体。
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