SULM – Schweizerische Union für Labormedizin | Union Suisse de Médecine de Laboratoire | Swiss Union of Laboratory Medicine

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SBA S. BRUNNER-AGTEN1, TY T. YAMAMOTO2, KY K. YAMADA2, CS CH. STEUER1, ARH A.R. HUBER1

1Kantonsspital Aarau AG, Institut für Labormedizin, Tellstrasse 25, CH-5001 Aarau, 2Technology Development., Sysmex Coporation, 4-4-4 Takatsukadai, Nishi-ku, Kobe 651-2271, Japan

Iron deficiency anemia (IDA), alpha- or beta-thalassemia (THA) and combinations thereof are the two most prevalent causes of microcytic anemia. The nowadays multiple laboratory approach for the differentiation between those two diseases includes determination of iron parameters, hemoglobin electrophoresis and molecular analysis, which is laboursome, time-consuming and expensive. Therefore a rapid, simple, cost efficient and reliable method would be of great value. Based on different red cell components measurable by a novel technology developed by Sysmex (Kobe, Japan), we performed a pilot study to test feasability of the novel approach for differentiation of normal from IDA and/or THA with a small but very well defined patient collective.
Together with classic well known red cell parameters a new parameter called “erythrocyte fluorescence rate” abbreviated with F% was calculated by the use of fluorescence area number and RBC area number. Sensitivity and specificity of F% was compared with well-known formulas used for the discrimination of normal, IDA and THA samples. Based on these results, the cut-off value for F% was determined at 0.44. This cut-off leads to an almost perfect specificity and sensitivity comparing IDA with THA samples. Further sensitivity and specificity of F% is very high for the discrimination between normal and THA as well as normal and IDA samples. If using F% in function of MCH, discrimination between IDA stage 2 & 3 and THA (alpha- and beta-thalassemia) is well possible. Putting the cut-off at 1.13 best sensitivity and specificity is achieved.
Looking at the ROC curves and the AUC's of the F% and the conventional formulas one can see, that the F% is the most powerful parameter for the discrimination between IDA and alpha- and beta-thalassemia, with perfect discrimination with an AUC of 1.00 between IDA and beta-thalassemia. Statistical analysis showed significance in the differences between F% and the conventional formulas.
Based on the results of this feasibility study, we suggest, that using the novel approach proper discrimination between IDA and THA, needs to be checked on a larger scale, again well defined patient collective.

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