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Stepwise discriminant function analysis for rapid identification of acute promyelocytic leukemia from acute myeloid leukemia with multiparameter flow cytometry

机译:多参数流式细胞术从急性髓样白血病中快速鉴别急性早幼粒细胞白血病的逐步判别函数分析

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Diagnosis of acute promyelocytic leukemia (APL) has been accelerated by multiparameter flow cytometry (MFC). However, diagnostic interpretation of MFC readouts for APL depends on individual experience and knowledge, which inevitably increases the risk of arbitrariness. We appraised the feasibility of using stepwise discriminant function analysis (SDFA) based on MFC to optimize the minimal variables needed to distinguish APL from other acute myeloid leukemia (AML) without complicated data interpretation. Samples from 327 patients with APL (n = 51) and non-APL AML (n = 276) were randomly allocated into training (243 AML) and test sets (84 AML) for SDFA. The discriminant functions from SDFA were examined by correct classification, and the final variables were validated by differential expression. Finally, additional 20 samples from patients with atypical APL and AML confusable with APL were also identified by SDFA method and morphological analysis. The weighed discriminant function reveals seven differentially expressed variables (CD2/CD9/CD11b/CD13/CD34/HLA-DR/CD117), which predict a molecular result for APL characterization with an accuracy that approaches 99 % (99.6 and 98.8 % for AML samples in training and test sets, respectively). Furthermore, the SDFA outperformed either single variable analysis or the more limited 3-component analysis (CD34/CD117/HLA-DR) via separate SDFA, and was also superior to morphological analysis in terms of diagnostic efficacy. The established SDFA based on MFC with seven variables can precisely and rapidly differentiate APL and non-APL AML, which may contribute to the urgent initiation of all-trans-retinoic acid-based APL therapy.
机译:多参数流式细胞术(MFC)加快了急性早幼粒细胞白血病(APL)的诊断。但是,针对APL的MFC读数的诊断解释取决于个人的经验和知识,这不可避免地增加了任意性的风险。我们评估了使用基于MFC的逐步判别函数分析(SDFA)来优化区分APL和其他急性髓细胞性白血病(AML)所需的最小变量而无需复杂数据解释的可行性。将327例APL(n = 51)和非APL AML(n = 276)患者的样本随机分配到SDFA训练(243 AML)和测试集(84 AML)中。通过正确分类检查了SDFA的判别功能,并通过差异表达验证了最终变量。最后,还通过SDFA方法和形态学分析从非典型APL和AML与APL混淆的患者中另外鉴定了20个样品。加权判别函数揭示了七个差异表达的变量(CD2 / CD9 / CD11b / CD13 / CD34 / HLA-DR / CD117),可预测APL表征的分子结果,其准确度接近99%(AML样品为99.6和98.8%)分别在培训和测试集中)。此外,SDFA通过单独的SDFA胜过单变量分析或更受限的3组分分析(CD34 / CD117 / HLA-DR),并且在诊断功效方面也优于形态分析。基于具有七个变量的MFC建立的SDFA可以准确快速地区分APL和非APL AML,这可能有助于紧急启动基于全反式维甲酸的APL治疗。

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