Thalassemia Reports (Jun 2012)

The Thal-index with the BTT prediction.exe to discriminate β-thalassaemia traits from other microcytic anaemias

  • Ahangama Arachchige Nilanga Nishad,
  • Arunasalam Pathmeswaran,
  • Ananda Rajitha Wickramasinghe,
  • Anuja Premawardhena

DOI
https://doi.org/10.4081/thal.2012.e1
Journal volume & issue
Vol. 2, no. 1
pp. e1 – e1

Abstract

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Several attempts have been made previously to differentiate β-thalassaemia trait (BTT) from other microcytic anaemias using formulae with red cell (RC) parameters. Presently available formulae have low sensitivity and specificity. We wanted to develop a more precise algorithm, which could be used in situations where the gold-standard test for thalassaemia diagnosis: the high performance liquid chromatography (HPLC) is not available. The study was carried out prospectively from November 2008 to March 2010 from randomly collected blood samples with a mean cell volume (MCV) of less than 80 fL. HbA2 measured by HPLC was used to diagnose BTT. We used Fishers stepwise linear discriminant function analysis to develop an algorithm with RC parameters. Calculated new index Thal-index was then subjected to receiver operating characteristic curve analysis to identify best cutoff to discriminate BTT from other microcytic blood films. Software was developed to predict the BTT status (BTT prediction.exe). New index, referred to as the Thal-index, was calculated using discriminant function analysis and is given as Thal-index=[(0.615xMCV) +(0.518xmean corpuscular hemoglobin)+ (0.446xred cell distribution width)]. A value of 59 for Thal-index has 90% sensitivity and 85% specificity for differentiating BTT from other microcytic anaemias. This showed better sensitivity and specificity compared to other formulae presently used (i.e., Mentzer in Eshani, et al.). Our study gives a better answer to set-up where HPLC is not available. Although this cannot replace HPLC, BTT prediction.exe is useful to predict instantly and is the first ever computer program available for this function. 先前已利用含红细胞（RC）参数的公式做出若干尝试，以鉴别β-地中海贫血（BTT）和其他小红细胞性贫血。目前可用公式的敏感度和特异度均低。我们想要开发更精确的算法，在地中海贫血诊断的金标准测试法（即高效液相色谱法（HPLC））无法使用的情况下使用。2008年11月至2010年3月期间，我们按照预期对随机采集的血液样本（平均细胞体积（MCV）低于80fL）进行了本项研究。经高效液相色谱法测定的HbA2用于诊断β-地中海贫血。我们利用Fishers逐步线性判别函数分析法开发一种含有红细胞参数的算法。计算出的新指标（地中海贫血指标）通过受试者操作特征曲线分析来确定区分β-地中海贫血和其他小红细胞血涂片的最佳捷径。开发软件预测β-地中海贫血状态（BTT预测.exe）。利用判别函数分析法计算新指标（即地中海贫血指标），得出以下公式：地中海贫血指标 = [(0.615 x平均细胞体积) + (0.518 x 红细胞平均血红蛋白量) + (0.446 x 红细胞体积分布宽度)]。指标值为59的地中海贫血指标用于区分β-地中海贫血和其他小红细胞性贫血时含90%敏感度和85%特异度。相较于目前使用的其他公式（即Mentzer in Eshani公式 等），这种公式具有更高的敏感度和特异度。本研究得出一个在高效液相色谱法无法使用的情况下使用的更好公式。尽管不能替代高效液相色谱法，但BTT预测.exe对于即时预测很有帮助，也是迄今为止对该功能有效的计算机程序。

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