Publication: New bioinformatics-based discrimination formulas for differentiation of thalassemiatraits from iron deficiency anemia
Issued Date
2017-08-01
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ISSN
19437730
00075027
00075027
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2-s2.0-85038075080
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Mahidol University
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SCOPUS
Bibliographic Citation
Lab Medicine. Vol.48, No.3 (2017), 230-237
Suggested Citation
Abdul Hafeez Kandhro, Watshara Shoombuatong, Virapong Prachayasittikul, Pornlada Nuchnoi New bioinformatics-based discrimination formulas for differentiation of thalassemiatraits from iron deficiency anemia. Lab Medicine. Vol.48, No.3 (2017), 230-237. doi:10.1093/labmed/lmx029 Retrieved from: https://repository.li.mahidol.ac.th/handle/20.500.14594/41797
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Title
New bioinformatics-based discrimination formulas for differentiation of thalassemiatraits from iron deficiency anemia
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Abstract
© American Society for Clinical Pathology, 2017. All rights reserved. Thalassemia traits (TTs) and iron deficiency anemia (IDA) are the most common disorders of hypochromic microcytic anemia (HMA). The present study aimed to differentiate TTs from IDA by analyzing discrimination formulas and provides comprehensive data of hemoglobin disorders prevalent in Pakistan. Among 12 published discrimination formulas, 6 formulas-MI, EF, G&K, RDWI, R, and HHI-were the most reliable to discriminate TTs from IDA. The failure cutoff values were improved by the random forest (RF) decision-tree approach. Moreover, the Shine and Lal (S&L) formula, which completely failed to discriminate IDA from TTs with original cutoff value (<1530), improved with the use of new proposed cutoff value (<1016) and was found to successfully discriminate all cases of TTs from those with IDA. In addition, 2 newly proposed formulas discriminated TTs from IDA more reliably than the original 12 formulas assessed. The proposed formulas could play a crucial role for clinicians to discriminate between TTs and IDA.