Eldibany M M, Totonchi K F, Joseph N J, Rhone D
Department of Pathology, Illinois Masonic Medical Center, Chicago 60657-5193, USA.
Am J Clin Pathol. 1999 May;111(5):676-82. doi: 10.1093/ajcp/111.5.676.
Iron-deficiency anemia and thalassemia are among the most common microcytic anemias. Differentiating these anemias by means of hemogrant indices is imprecise. Powerful statistical computer programming now enables sensitive discriminant analyses to aid in the diagnosis. Laboratory results from 383 adults were examined retrospectively and grouped according to their original diagnoses: normal (n = 78); beta-thalassemia (n = 134); alpha-thalassemia (n = 106); and iron-deficiency anemia (n = 65). Statistical analysis of results evaluated only RBC indices: RBC count, hemoglobin level, mean corpuscular volume, mean corpuscular hemoglobin, and RBC distribution width. Stepwise multivariate discriminant analysis determined those indices that best differentiated the 4 groups. The Fisher linear discriminant function for each group was calculated and tested casewise. Discriminant analysis identified mean corpuscular hemoglobin, RBC count, mean corpuscular volume, and RBC distribution width as the best set of indices for differentiating the 4 diagnoses. Casewise testing of the calculated Fisher linear discriminant function resulted in mean-weighted sensitivity of 80.4%. The present study demonstrates that a set of linear discriminant functions based on routine hemogram data can effectively differentiate between alpha-thalassemia, beta-thalassemia, and iron-deficiency anemia, with a high degree of accuracy.
缺铁性贫血和地中海贫血是最常见的小细胞性贫血。通过血常规指标来区分这些贫血并不精确。强大的统计计算机程序现在能够进行敏感的判别分析以辅助诊断。对383名成年人的实验室结果进行回顾性检查，并根据他们原来的诊断进行分组：正常（n = 78）；β地中海贫血（n = 134）；α地中海贫血（n = 106）；以及缺铁性贫血（n = 65）。对结果的统计分析仅评估红细胞指标：红细胞计数、血红蛋白水平、平均红细胞体积、平均红细胞血红蛋白含量和红细胞分布宽度。逐步多变量判别分析确定了最能区分这4组的指标。计算了每组的费舍尔线性判别函数并进行逐例检验。判别分析确定平均红细胞血红蛋白含量、红细胞计数、平均红细胞体积和红细胞分布宽度是区分这4种诊断的最佳指标集。对计算出的费舍尔线性判别函数进行逐例检验，平均加权敏感度为80.4%。本研究表明，基于常规血常规数据的一组线性判别函数能够有效区分α地中海贫血、β地中海贫血和缺铁性贫血，准确率很高。
