Alfa Thalassemia Intermedia (HbH disease): How the New Information Provided by the Routine Hematology Analysers May Help in Its Differential Diagnosis or Flagging
Authors: Barella Susanna , Simon-Lopez Ramon , Gaetano Nicola Di , Galanello Renzo 
Published: October 2019

Abstract
Abstract 5180
Alpha-thalassemia (α-thalassemia) has two clinically significant forms: hemoglobin Bart hydrops fetalis (Hb Bart) syndrome and hemoglobin H (HbH) disease. HbH disease is characterized by microcytic hypochromic hemolytic anemia, hepatosplenomegaly, mild jaundice, and sometimes thalassemia-like bone changes.

Diagnostic of Alfa Thalassemia:
Classic testing for α-thalassemia includes: hematologic testing of red blood cell indices, peripheral blood smear, supravital stain to detect RBC inclusion bodies, and qualitative and quantitative hemoglobin analysis. HBA1, the gene encoding α1-globin, and HBA2, the gene encoding α2-globin, are the two genes most commonly associated with α-thalassemia. Molecular genetic testing of HBA1 and HBA2 detects deletions in about 90% and point mutations in about 10% of affected individuals.

Objective:
Recently have been developed new parameters and information in the new automated hematology analyzer called DxH8008™ from Beckman Coulter as @MSCV, @RSF, @MAF, @LHD% and many morphological parameters for RBC and Reticulocytes calles Cell Population Data. All this parameters may be used to create flagging for laboratory use only (LUO) or Research use only (RUO). The purpose of this study is to investigate the possible use or utility of this new information for the screening/flagging of Alfa Thalassemia.

Patient and Methods:
We have collected 129 patients with Alfa Thalassemia Intermedia (HbH disease). All of them were confirmed by red cell morphology, Hgb Electroforesis, cromatography in liquid phase in human whole blood for the determination of Hemoglobin A2, F, A1c, and identification of abnormal hemoglobins and DNA analysis (DNA Analysis by GAP-PCR). We have compared these patients with a control group (184 individuals) and with other anemias (see Table 1).

Results:
Using ROC analysis, the best parameters differentiating the HbH Disease from the normals were: RDW (AUC 1. 000), @LHD(AUC 1. 000), @MAF(AUC 1. 000), @MCNRET (AUC 1. 000), MCV (AUC 0. 999), @MCRET (AUC 0. 999), @RSF (AUC 0. 998), HGB (AUC 0. 996), @MSCV (AUC 0. 995).
Using ROC analysis, the best parameters differentiating the HbH Disease from other anemias (excluding normals) were: @LHD(AUC 0. 957), @MCNRET (AUC 0. 946), @MCRET (AUC 0. 902), @MAF(AUC 0. 873), MCV (AUC 0. 869).
Using logistic regression we found a discrminant function that permits to differentiate/flag perfectly the patients with HbH disease from other anemias, and of course from normals: AUC 0. 996) Sensitivity: 91. 47% Specificity 94. 68% with a percent of cases correctly classified of: 93. 67 %.

Disclosures:
Simon-Lopez: Beckman Coulter: @LHD, @MAF, @RSF, @LHD, @MAF, @RSF Patents & Royalties, Employment. Di Gaetano:Instrumentation Laboratory spa: Work for a distributor of Beckman Coulter Instruments in Italy Other. Galanello:Novartis: Research Funding, Speakers Bureau; Apopharma: Research Funding, Speakers Bureau; Ferrokin: Research Funding.