Heliyon (Oct 2024)
Accuracy of the model derived from red blood cell indices in predicting α0-thalassemia trait among non-anemic pregnant women
Abstract
Background: The study aims to establish prediction model derived from red blood cell indices to improve the accuracy of α0-thalassemia trait screening in non-anemic pregnant women. Method: A diagnostic study as secondary analysis on the prospective database was conducted. The participants were pregnant women, undergoing α0-thalassemia screening at first visit antenatal care using red blood cell indices with confirmation by PCR method. Diagnostic performance of each of red blood cell parameter and their combination derived from logistic regression analysis in predicting α0-thalassemia trait were determined. Findings: The total 587 Thai pregnant women were included in the analysis, consisting of 136 cases of α0-thalassemia trait and 451 normal controls. Diagnostic performance analysis revealed that, the mean corpuscular volume (MCV) provided a sensitivity of 98.5 % and a false positive rate of 20.2 %. While The mean corpuscular hemoglobin (MCH) provided a sensitivity of 99.3 % and a false positive rate of 15.7 %. The combined-parameters prediction model including hemoglobin (Hb), MCV, MCH, mean corpuscular hemoglobin concentration (MCHC), red cell distribution width (RDW), and red blood cell (RBC) count, demonstrated excellent diagnostic performance with an area under the curve (AUC) of 0.992, sensitivity of 99.3 %, and much lower false positive rate of 4 %. Interpretation: The combined-parameter prediction model provided excellent diagnostic performance with low false positive rate. The application of the prediction model could decrease unnecessary PCR method for α0-thalassemia testing, thereby decreasing the cost of investigation. Our proposed model can possibly have a great impact or significant change in clinical practice, especially in Southeast Asia.
