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全血细胞计数及相关研究参数在骨髓增生异常综合征检测中的应用

Complete Blood Counts and Research Parameters in the Detection of Myelodysplastic Syndromes.

作者信息

Urrechaga Eloísa, Fernández Mónica, Aguirre Urko

机构信息

Laboratory, Galdakao-Usansolo Hospital, 48960 Galdakao, Spain.

Hematology, Hospital Universitario Araba, 01009 Vitoria-Gasteiz, Spain.

出版信息

Diagnostics (Basel). 2024 Jun 21;14(13):1322. doi: 10.3390/diagnostics14131322.

Abstract

UNLABELLED

The diagnosis of Myelodysplastic syndromes (MDS) is frequently challenging, especially in terms of the distinction from the other non-neoplastic causes of cytopenia. Currently, it is based on the presence of peripheral blood cytopenias, peripheral blood and bone marrow dysplasia/blasts, and clonal cytogenetic abnormalities, but MDS diagnostic features are polymorphic and non-specific. We investigated the utility of complete blood count (CBC) and research parameters (RUO) from the analyzer BC 6800 Plus (Mindray Diagnostics) to discriminate MDS-related cytopenia.

METHODS

100 samples from healthy individuals were used to establish the values of research parameters in normal subjects. A retrospective study was conducted including 66 patients diagnosed with MDS, 90 cytopenic patients due to other diseases (cancer patients receiving therapy, aplastic anemia, other hematological malignancies) and 50 with macrocytic anemia. The Wilcoxon test was applied to detect statistical differences among the groups of patients, considering < 0.05 significant. The diagnostic performance of the RUO parameters for discriminating MDS among cytopenias was evaluated using receiver operating characteristic (ROC) curve analysis. Amultivariable logistic regression model was performed to identify the potential predictors for having MDS. The area under curve (AUC) and the Hosmer-Lemeshow test of the model were assessed. The performance of the model was verified in a prospective study including 224 cytopenic patients (validation group).

RESULTS

In the MDS group, the mean cell volume (MCV), percentage of macrocytic red cells (MAC), red cell distribution width (RDW) and immature platelets fraction (IPF) had increased values compared to the cytopenic and normal patients, while platelets, red and white cell counts, Neu X (related to the cytoplasmic complexity of neutrophils), Neu Y (related to nucleic acid content) and Neu Z (related to cell size) were lower ( < 0.001). Neu X, Neu Y, and Neu Z showed higher AUC for detecting MDS > 0.80; MAC, RDW and IPF AUC > 0.76. The multivariable model demonstrated that Neu X and Neu Y could be used in the recognition of MDS, AUC 0.88. In the validation group, 89.0% of the MDS patients were well classified.

CONCLUSION

MDS are common malignant disorders with a poor prognosis, and early diagnosis is warranted for optimal benefit from treatment. RUO gain insights to detect dysplasia of MDS and could be used in the differential diagnosis of MDS from cytopenias of other etiologies.

摘要

未标注

骨髓增生异常综合征(MDS)的诊断常常具有挑战性,尤其是在与其他血细胞减少的非肿瘤性病因相鉴别方面。目前,其诊断基于外周血细胞减少、外周血和骨髓发育异常/原始细胞以及克隆性细胞遗传学异常的存在,但MDS的诊断特征具有多态性且非特异性。我们研究了迈瑞医疗BC 6800 Plus血细胞分析仪的全血细胞计数(CBC)和研究参数(RUO)在鉴别MDS相关血细胞减少方面的效用。

方法

使用100例健康个体的样本确定正常受试者的研究参数值。进行了一项回顾性研究,纳入66例诊断为MDS的患者、90例因其他疾病导致血细胞减少的患者(接受治疗的癌症患者、再生障碍性贫血、其他血液系统恶性肿瘤)以及50例大细胞性贫血患者。应用Wilcoxon检验检测患者组间的统计学差异,P<0.05具有显著性。使用受试者工作特征(ROC)曲线分析评估RUO参数在血细胞减少中鉴别MDS的诊断性能。进行多变量逻辑回归模型以识别患MDS的潜在预测因素。评估模型的曲线下面积(AUC)和Hosmer-Lemeshow检验。在一项纳入224例血细胞减少患者的前瞻性研究(验证组)中验证模型的性能。

结果

在MDS组中,与血细胞减少患者和正常患者相比,平均红细胞体积(MCV)、大红细胞百分比(MAC)、红细胞分布宽度(RDW)和未成熟血小板分数(IPF)的值升高,而血小板、红细胞和白细胞计数、Neu X(与中性粒细胞胞质复杂性相关)、Neu Y(与核酸含量相关)和Neu Z(与细胞大小相关)较低(P<0.001)。Neu X、Neu Y和Neu Z在检测MDS方面显示出较高的AUC>0.80;MAC、RDW和IPF的AUC>0.76。多变量模型表明,Neu X和Neu Y可用于识别MDS,AUC为0.88。在验证组中,89.0%的MDS患者得到了良好分类。

结论

MDS是常见的恶性疾病,预后较差,早期诊断对于从治疗中获得最佳益处是必要的。RUO有助于检测MDS的发育异常,可用于MDS与其他病因引起的血细胞减少的鉴别诊断。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/7317/11240308/e669abce8b40/diagnostics-14-01322-g001.jpg

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