A Novel Algorithm Using Cell Population Data (VCS Parameters) as a Screening Discriminant between Alpha and Beta Thalassemia Traits

Abstract

Thalassemia is one of the major inherited haematological disorders in the Southeast Asia region. This study explored the potential utility of red blood cell (RBC) parameters and reticulocyte cell population data (CPD) parameters in the differential diagnosis of α and β-thalassaemia traits as a rapid and cost-effective tool for screening of thalassemia traits. In this study, a total of 1597 subjects (1394 apparently healthy subjects, 155 subjects with α-thalassaemia trait, and 48 subjects with β-thalassaemia trait) were accrued. The parameters studied were the RBC parameters and reticulocyte CPD parameters derived from Unicel DxH800. A novel algorithm named αβ-algorithm was developed: (MN-LMALS-RET × RDW) − MCH) to discriminate α from β-thalassaemia trait with a cut-off value of 1742.5 [AUC = 0.966, sensitivity = 92%, specificity = 90%, 95% CI = 0.94–0.99]. Two prospective studies were carried: an in-house cohort to assess the specificity of this algorithm in 310 samples comprising various RBC disorders and in an interlaboratory cohort of 65 α-thalassemia trait, and 30 β-thalassaemia trait subjects to assess the reproducibility of the findings. We propose the αβ-algorithm to serve as a rapid, inexpensive surrogate evaluation tool of α and β-thalassaemia in the population screening of thalassemia traits in geographic regions with a high burden of these inherited blood disorders.

The exploration of cell population data in clinical use: Beyond infectious diseases

“…This could discriminate the α from the β ‐thalassemia trait. The respective sensitivity and specificity values were 92% and 90%, with the AUC value reaching 0.97 with a cut‐off value of 1742.5 [66]. CPD deserves further exploration for potential clinical applications.…”

New logarithm-based discrimination formula for differentiating thalassemia trait from iron deficiency anemia in pregnancy

“…Although the 10 hematological parameters of TT and IDA in this study were statistically different, considering the current laboratory blood cell detection methods, only RBC, Hb, and HCT are the measurement results, while MCV, MCH, MCHC, RDW-CV are calculated from the previous values. And some studies have found that MCV does not accurately reflect erythropoiesis [ 49 ]. In any progressive iron depletion, the latest red blood cell volume is the smallest, while thalassemia is not iron deficient, so its red blood cell MCV does not change It has also been found that MCV is not a good indicator to distinguish TT from IDA [ 50 ].…”

Novel Decision Tool for More Severe α-Thalassemia Genotypes Screening with Functional Loss of Two or More α-Globin Genes: A Diagnostic Test Study

“…In China, a model was described associating some indices of red blood cells with Hb A 2 levels to differentiate β-thalassemia, α-thalassemia, and iron deficiency [ 31 ]. An algorithm has been developed to differentiate between α-thalassemia and β-thalassemia traits (αβ-algorithm), especially in geographic regions with large numbers of individuals with these inherited blood disorders [ 32 ].…”