Avilés A, Ovilla R, García L D, Rubio M E, González-Llaven J
Arch Invest Med (Mex). 1989 Jan-Mar;20(1):45-52.
A multivariate analysis of clinical, biochemical and hematologic data was performed in 138 patients with myelodysplastic syndromes (MDS) in order to evaluate their prognostic significance. The most important individual variables, isolated in a previous univariate analysis, were placed in a multiple regression modeling procedure to identify major prognostic factors. Multivariate analysis tends to identify prognostic variables containing significant predictive information. Characteristics were examined on both continuous and binary bases. The FAB classification was the first parameter entered in regression equations of both models, followed by platelet count, systemic symptoms, bone marrow blast and infection. Our analysis confirms FAB classification as the best prognostic factor in MDS. It supports the previously predictive value of platelet count, hemoglobin level and bone marrow blast and recognizes the importance of systemic symptoms and infection as prognostic characteristics in MDS.
对138例骨髓增生异常综合征（MDS）患者的临床、生化和血液学数据进行了多变量分析，以评估其预后意义。在先前的单变量分析中分离出的最重要的个体变量，被纳入多元回归建模程序，以识别主要的预后因素。多变量分析倾向于识别包含显著预测信息的预后变量。对连续和二元特征均进行了检查。FAB分类是两个模型回归方程中输入的第一个参数，其次是血小板计数、全身症状、骨髓原始细胞和感染。我们的分析证实FAB分类是MDS中最佳的预后因素。它支持血小板计数、血红蛋白水平和骨髓原始细胞先前的预测价值，并认识到全身症状和感染作为MDS预后特征的重要性。
