Volume 43, Issue 4 pp. 866-872
ORIGINAL ARTICLE

Cell count-based parameters and algorithms for thalassaemia trait screening in the southern Chinese population

Jialong Xu

Jialong Xu

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

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Yeru Yang

Yeru Yang

Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China

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Huanbin Zhou

Huanbin Zhou

Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China

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Xiaoxin Huang

Xiaoxin Huang

Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China

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Bizhen Chen

Bizhen Chen

Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China

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Nuan Chen

Nuan Chen

Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China

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Yinge Wu

Corresponding Author

Yinge Wu

Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, Shantou, China

Correspondence

Yinge Wu, Department of Laboratory Medicine, The First Affiliated Hospital of Shantou University Medical College, 57 Changping Road, Shantou, Guangdong, China.

Email: [email protected]

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First published: 06 January 2021
Jialong Xu, Yeru Yang and Huanbin Zhou contributed equally to this research and are co-first authors.

Abstract

Introduction

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.

Methods

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.

Results

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.

Conclusion

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.

CONFLICT OF INTEREST

The authors declare they have no conflicts of interest.

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