Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Laboratory of Molecular Cardiology, The First Affiliated Hospital of Shantou University Medical College, Shantou, China.
Int J Lab Hematol. 2021 Aug;43(4):866-872. doi: 10.1111/ijlh.13454. Epub 2021 Jan 6.
Thalassaemia trait (TT) is potential to be missed clinically, especially normocytic thalassaemia. We aimed to establish discriminant functions (DFs) and an algorithm for detecting microcytic or normocytic TT in epidemiological screening.
The receiver operating characteristics (ROC) curve analysis was used to determine the diagnostic performance of the proposed formulas in differentiating TT and nonthalassaemia (non-TT). DFs combined the two blood count parameters with the highest performance, based on the area under the curve (AUC) value, into mathematical formulas, using logistic regression. The diagnostic efficacy of DFs was subsequently evaluated in 761 participants, and reliability (including adjusted agreement [AA] and Kappa values) and validity (including sensitivity, specificity, likelihood ratio and Youden's Index) were calculated.
Among microcytic participants, the proposed DFs showed good diagnostic performance (in females: AUC = 0.892 [DF1 = 0.015 × RDW-CV/RBC - 0.096 × RDW-SD/RBC + 1.29], in males: AUC = 0.861 [DF2=-0.025 × RDW-SD/RBC - 0.035 × MCV/RBC + 1.415]). Youden's Index, AA and Kappa values for microcytic TT detection were 0.72, 0.86, and 0.72 and 0.63, 0.81 and 0.63 for females and males, respectively. In normocytic participants with RDW-CV/RBC ≤ 3.54, DF3=-0.38 × MCH-0.02 × MCHC+17.37 achieved AUC = 0.857 in females, whereas DF4 = 0.007 × MCV-0.113 × MCH+2.829 achieved AUC = 0.969 in males. The Youden's Index, AA and Kappa values for the proposed DFs for thalassaemia detection were 0.69, 0.84 and 0.67 in females, 0.76, 0.91 and 0.71 in males, respectively.
The proposed DFs performed well in the detection of TT among participants with microcytic and normocytic parameters and could be utilized in epidemiological study for TT.
地中海贫血特征（TT）在临床上可能会被遗漏，尤其是正细胞性地中海贫血。我们旨在建立判别函数（DF）和算法，用于在流行病学筛查中检测小细胞性或正细胞性 TT。
采用受试者工作特征（ROC）曲线分析确定所提出公式在区分 TT 和非地中海贫血（非-TT）方面的诊断性能。DF 基于 AUC 值，将两个具有最高性能的血液计数参数结合到数学公式中，使用逻辑回归。随后在 761 名参与者中评估了 DF 的诊断效果，并计算了可靠性（包括调整后的一致性[AA]和 Kappa 值）和有效性（包括敏感性、特异性、似然比和 Youden 指数）。
在小细胞性参与者中，所提出的 DF 表现出良好的诊断性能（女性：AUC=0.892[DF1=0.015×RDW-CV/RBC-0.096×RDW-SD/RBC+1.29]，男性：AUC=0.861[DF2=-0.025×RDW-SD/RBC-0.035×MCV/RBC+1.415]）。小细胞性 TT 检测的 Youden 指数、AA 和 Kappa 值分别为 0.72、0.86 和 0.72 以及 0.63、0.81 和 0.63 用于女性和男性。在 RDW-CV/RBC≤3.54 的正细胞性参与者中，DF3=-0.38×MCH-0.02×MCHC+17.37 在女性中获得 AUC=0.857，而 DF4=0.007×MCV-0.113×MCH+2.829 在男性中获得 AUC=0.969。用于地中海贫血检测的所提出的 DF 的 Youden 指数、AA 和 Kappa 值分别为女性 0.69、0.84 和 0.67，男性 0.76、0.91 和 0.71。
所提出的 DF 在检测小细胞性和正细胞性参数的参与者中的 TT 中表现良好，可用于 TT 的流行病学研究。
