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Critical appraisal of discriminant formulas for distinguishing thalassemia from iron deficiency in patients with microcytic anemia

  • Eloísa Urrechaga EMAIL logo and Johannes J.M.L. Hoffmann
Published/Copyright: February 9, 2017
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Clinical Chemistry and Laboratory Medicine (CCLM)
From the journal Clinical Chemistry and Laboratory Medicine (CCLM) Volume 55 Issue 10

Abstract

Background:

Many discriminant formulas have been reported for distinguishing thalassemia trait from iron deficiency in patients with microcytic anemia. Independent verification of several discriminant formulas is deficient or even lacking. Therefore, we have retrospectively investigated discriminant formulas in a large, well-characterized patient population.

Methods:

The investigational population consisted of 2664 patients with microcytic anemia: 1259 had iron deficiency, 1196 ‘pure’ thalassemia trait (877 β- and 319 α-thalassemia), 150 had thalassemia trait with concomitant iron deficiency or anemia of chronic disease, and 36 had other diseases. We investigated 25 discriminant formulas that only use hematologic parameters available on all analyzers; formulas with more advanced parameters were disregarded. The diagnostic performance was investigated using ROC analysis.

Results:

The three best performing formulas were the Jayabose (RDW index), Janel (11T), and Green and King formulas. The differences between them were not statistically significant (p>0.333), but each of them had significantly higher area under the ROC curve than any other formula. The Jayabose and Green and King formulas had the highest sensitivities: 0.917 both. The highest specificity, 0.925, was found for the Janel formula, which is a composite score of 11 other formulas. All investigated formulas performed significantly better in distinguishing β- than α-thalassemia from iron deficiency.

Conclusions:

In our patient population, the Jayabose RDW index, the Green and King formula and the Janel 11T score are superior to all other formulas examined for distinguishing between thalassemia trait and iron deficiency anemia. We confirmed that all formulas perform much better in β- than in α-thalassemia carriers and also that they incorrectly classify approximately 30% of thalassemia carriers with concomitant other anemia as not having thalassemia. The diagnostic performance of even the best formulas is not high enough for making a final thalassemia diagnosis, but in countries with limited resources, they can be helpful in identifying those patients who need further examinations for genetic anemia.

Keywords: diagnostic performance; discriminant formula; iron deficiency anemia; microcytic erythrocytes; thalassemia
Corresponding author: Dr. Eloísa Urrechaga, Hematology Laboratory, Hospital Galdakao-Usansolo, 48960 Galdakao, Vizcaya, Spain, Phone: +34 94 400 7000, Fax: +34 94 400 7102

  1. Author contributions: All the authors have accepted responsibility for the entire content of this submitted manuscript and approved submission.

  2. Research funding: None declared.

  3. Employment or leadership: None declared.

  4. Honorarium: None declared.

  5. Competing interests: The funding organization(s) played no role in the study design; in the collection, analysis, and interpretation of data; in the writing of the report; or in the decision to submit the report for publication.

References

1. Auerbach M, Adamson JW. How we diagnose and treat iron deficiency anemia. Amer J Hematol 2016;91:31–8.10.1002/ajh.24201Search in Google Scholar

2. England JM, Fraser PM. Differentiation of iron deficiency from thalassaemia trait by routine blood-count. Lancet 1973;1:449–52.10.1016/S0140-6736(73)91878-3Search in Google Scholar

3. Mentzer Jr WC. Differentiation of iron deficiency from thalassaemia trait. Lancet 1973;1:882.10.1016/S0140-6736(73)91446-3Search in Google Scholar

4. Srivastava PC. Differentiation of thalassaemia minor from iron deficiency. Lancet 1973;2:155–6.Search in Google Scholar

5. Shine I, Lal S. A strategy to detect β thalassaemia minor. Lancet 1977;1:692–4.10.1016/S0140-6736(77)92128-6Search in Google Scholar

6. Bessman JD, Feinstein DI. Quantitative anisocytosis as a discriminant between iron deficiency and thalassemia minor. Blood 1979;53:288–93.10.1182/blood.V53.2.288.288Search in Google Scholar

7. Ricerca BM, Storti S, d’Onofrio G, Mancini S, Vittori M, Campisi S, et al. Differentiation of iron deficiency from thalassaemia trait: a new approach. Haematologica 1987;72:409–13.Search in Google Scholar

8. Green R, King R. A new red cell discriminant incorporating volume dispersion for differentiating iron deficiency anemia from thalassemia minor. Blood Cells 1989;15:481–95.Search in Google Scholar

9. Makris PE. Utilization of a new index to distinguish heterozygous thalassemic syndromes: comparison of its specificity to five other discriminants. Blood Cells 1989;15:497–507.Search in Google Scholar

10. Das Gupta A, Hegde C, Mistri R. Red cell distribution width as a measure of severity of iron deficiency in iron deficiency anemia. Ind J Med Res 1994;100:177–83.Search in Google Scholar

11. Jayabose S, Giamelli J, Levondoglu-Tugal O, Sandoval C, Ozkaynak F, Visintainer PL. Differentiating iron deficiency anemia from thalassemia minor by using an RDW-based index. J Ped Hematol Oncol 1999;21:314.10.1097/00043426-199907000-00040Search in Google Scholar

12. Telmissani OA, Khalil S, George TR. Mean density of hemoglobin per liter of blood: a new hematologic parameter with an inherent discriminant function. Lab Hematol 1999;5:149–52.Search in Google Scholar

13. Huber AR, Ottiger C, Risch L, Regenass S, Hergersberg M, Herklotz R. Thalassämie-Syndrome: Klinik und Diagnose. Schweiz Mediz Forum 2004;4:947–52.Search in Google Scholar

14. Cohan N, Ramzi M. Evaluation of sensitivity and specificity of Kerman index I and II in screening beta thalassemia minor. Sci J Iranian Blood Transf Org 2008;4:297–302.Search in Google Scholar

15. Sirdah M, Tarazi I, Al Najjar E, Al Haddad R. Evaluation of the diagnostic reliability of different RBC indices and formulas in the differentiation of the beta-thalassaemia minor from iron deficiency in Palestinian population. Int J Lab Hematol 2008;30:324–30.10.1111/j.1751-553X.2007.00966.xSearch in Google Scholar PubMed

16. Ehsani MA, Shahgholi E, Rahiminejad MS, Seighali F, Rashidi A. A new index for discrimination between iron deficiency anemia and beta-thalassemia minor: results in 284 patients. Pakist J Biol Sci 2009;12:473–5.10.3923/pjbs.2009.473.475Search in Google Scholar PubMed

17. Janel A, Roszyk L, Rapatel C, Mareynat G, Berger MG, Serre-Sapin AF. Proposal of a score combining red blood cell indices for early differentiation of beta-thalassemia minor from iron deficiency anemia. Hematology 2011;16:123–7.10.1179/102453311X12940641877849Search in Google Scholar PubMed

18. Keikhaei B. A new valid formula in differentiating iron deficiency anemia from ß-thalassemia trait. Pakist J Med Sci 2010;26:368–73.Search in Google Scholar

19. Nishad AA, Pathmeswaran A, Wickramasinghe AR, Premawardhena A. The Thal-index with the BTT prediction.exe to discriminate β-thalassaemia traits from other microcytic anaemias. Thalass Rep 2012;2:e1–2.10.4081/thal.2012.e1Search in Google Scholar

20. Wongprachum K, Sanchaisuriya K, Sanchaisuriya P, Siridamrongvattana S, Manpeun S, Schlep FP. Proxy indicators for identifying iron deficiency among anemic vegetarians in an area prevalent for thalassemia and hemoglobinopathies. Acta Haematol 2012;127:250–5.10.1159/000337032Search in Google Scholar PubMed

21. Dharmani P, Sehgal K, Dadu T, Mankeshwar R, Shaikh A, Khodaiji S. Developing a new index and its comparison with other CBC-based indices for screening of beta thalassemia trait in a tertiary care hospital. Int J Lab Hematol 2013;35:118.Search in Google Scholar

22. Pornprasert S, Panya A, Punyamung M, Yanola J, Kongpan C. Red cell indices and formulas used in differentiation of β-thalassemia trait from iron deficiency in Thai school children. Hemoglobin 2014;38:258–61.10.3109/03630269.2014.930044Search in Google Scholar PubMed

23. Sirachainan N, Iamsirirak P, Charoenkwan P, Kadegasem P, Wongwerawattanakoon P, Sasanakul W, et al. New mathematical formula for differentiating thalassemia trait and iron deficiency anemia in thalassemia prevalent area: a study in healthy school-age children. Southeast J Trop Med Publ Health 2014;45:174–82.Search in Google Scholar

24. Bordbar E, Taghipour M, Zucconi BE. Reliability of different RBC indices and formulas in discriminating between beta-thalassemia minor and other microcytic hypochromic cases. Mediterr J Hematol Infect Dis 2015;7:e2015022.10.4084/mjhid.2015.022Search in Google Scholar

25. d’Onofrio G, Zini G, Ricerca BM, Mancini S, Mango G. Automated measurement of red blood cell microcytosis and hypochromia in iron deficiency and beta-thalassemia trait. Arch Pathol Lab Med 1992;116:84–9.Search in Google Scholar

26. Robertson EP, Pollock A, Yau KS, Chan LC. Use of Technicon H*1 technology in routine thalassaemia screening. Med Lab Sci 1992;49:259–64.Search in Google Scholar

27. Vicinanza P, Catalano L, Franco F, Vaccaro E, Cancellario S, Vicinanza M, et al. Two new HDW-based indexes to identify ß-thalassemia trait. Lab Hematol 2002;8:193–9.Search in Google Scholar

28. Noronha JF, Grotto HZ. Measurement of reticulocyte and red blood cell indices in patients with iron deficiency anemia and beta-thalassemia minor. Clin Chem Lab Med 2005;43:195–7.Search in Google Scholar

29. Agorasti A, Trivellas T, Papadopoulos V, Konstantinidou D. Innovative parameters RET-Y, sTfR, and sTfR-F index in patients with microcytic, hypochromic anemia–their special value for hemoglobinopathies. Lab Hematol 2007;13:63–8.10.1532/LH96.06044Search in Google Scholar PubMed

30. Sudmann ÅA, Piehler A, Urdal P. Reticulocyte hemoglobin equivalent to detect thalassemia and thalassemic hemoglobin variants. Int J Lab Hematol 2012;34:605–13.10.1111/j.1751-553X.2012.01442.xSearch in Google Scholar PubMed PubMed Central

31. Urrechaga E. The new mature red cell parameter, low haemoglobin density of the Beckman-Coulter LH750: clinical utility in the diagnosis of iron deficiency. Int J Lab Hematol 2010;32:e144–50.10.1111/j.1751-553X.2008.01127.xSearch in Google Scholar PubMed

32. Ng EH, Leung JH, Lau YS, Ma ES. Evaluation of the new red cell parameters on Beckman Coulter DxH800 in distinguishing iron deficiency anaemia from thalassaemia trait. Int J Lab Hematol 2015;37:199–207.10.1111/ijlh.12262Search in Google Scholar PubMed

33. Trivedi DP, Shah HA. Discriminant functions in distinguishing beta-thalassemia trait and iron deficiency anemia: the value of the RDW-SD. Internet J Hematol 2011;7:1–13.Search in Google Scholar

34. Williams C. The use of the automated parameter RDW-SD as a discriminator of both alpha and beta thalassaemia trait from iron deficiency. Austral J Med Sci 2011;32:95.Search in Google Scholar

35. Winichagoon P, Kumbunlue R, Sirankapracha P, Boonmongkol P, Fucharoen S. Discrimination of various thalassemia syndromes and iron deficiency and utilization of reticulocyte measurements in monitoring response to iron therapy. Blood Cells Molec Dis 2015;54:336–41.10.1016/j.bcmd.2015.01.010Search in Google Scholar PubMed

36. Bessman JD, McClure S, Bates J. Distinction of microcytic disorders: comparison of expert, numerical-discriminant, and microcomputer analysis. Blood Cells 1989;15:533–40.Search in Google Scholar

37. Houwen B. The use of inference strategies in the differential diagnosis of microcytic anemia. Blood Cells 1989;15:509–32.Search in Google Scholar

38. Han P, Fung KP. Discriminant analysis of iron deficiency anaemia and heterozygous thalassaemia traits: a 3-dimensional selection of red cell indices. Clin Lab Haematol 1991;13:351–62.10.1111/j.1365-2257.1991.tb00299.xSearch in Google Scholar PubMed

39. Erler BS, Vitagliano P, Lee S. Superiority of neural networks over discriminant functions for thalassemia minor screening of red blood cell microcytosis. Arch Pathol Lab Med 1995;119:350–4.Search in Google Scholar

40. Eldibany MM, Totonchi KF, Joseph NJ, Rhone D. Usefulness of certain red blood cell indices in diagnosing and differentiating thalassemia trait from iron-deficiency anemia. Amer J Clin Pathol 1999;111:676–82.10.1093/ajcp/111.5.676Search in Google Scholar PubMed

41. Yeh JS, Cheng CH. Using hierarchical soft computing method to discriminate microcyte anemia. Exp Syst Appl 2005;29:515–24.10.1016/j.eswa.2005.04.012Search in Google Scholar

42. Schoorl M, Schoorl M, Linssen J, Villanueva MM, NoGuera JA, Martinez PH, et al. Efficacy of advanced discriminating algorithms for screening on iron-deficiency anemia and ß-thalassemia trait. Am J Clin Pathol 2012;138:300–4.10.1309/AJCP20UTTCAYKUDXSearch in Google Scholar PubMed

43. Barnhart-Magen G, Gotlib V, Marilus R, Einav Y. Differential diagnostics of thalassemia minor by artificial neural networks model. J Clin Lab Anal 2013;27:481–6.10.1002/jcla.21631Search in Google Scholar PubMed PubMed Central

44. Urrechaga E, Aguirre U, Izquierdo S. Multivariable discriminant analysis for the differential diagnosis of microcytic anemia. Anemia 2013;2013:Article ID 457834.10.1155/2013/457834Search in Google Scholar PubMed PubMed Central

45. Hoffmann JJ, Urrechaga E, Aguirre U. Discriminant indices for distinguishing thalassemia and iron deficiency in patients with microcytic anemia: a meta-analysis. Clin Chem Lab Med 2015;53:1883–94.10.1515/cclm-2015-0179Search in Google Scholar PubMed

46. Juncà J, Mañú-Pereira M, Radó-Trilla N, Vives-Corrons JL. Cell counter-based parameters and formulas in detection of beta-thalassemia trait. Am J Clin Pathol 2008;130:147–8.Search in Google Scholar

47. Narchi H, Basak RB. Comparison of erythrocyte indices to differentiate between iron deficiency and alpha-thalassaemias in children with microcytosis and/or hypochromia. East Mediterr Health J 2010;16:966–71.10.26719/2010.16.9.966Search in Google Scholar

48. Huang TC, Wu YY, Chen YG, Lai SW, Wu SC, Ye RH, et al. Discrimination index of microcytic anemia in young soldiers: a single institutional analysis. PLoS One 2015;10:e0114061.10.1371/journal.pone.0114061Search in Google Scholar PubMed PubMed Central

49. Urrechaga E. Discriminant value of % microcytic/% hypochromic ratio in the differential diagnosis of microcytic anemia. Clin Chem Lab Med 2008;46:1752–8.10.1515/CCLM.2008.355Search in Google Scholar PubMed

50. Urrechaga E, Borque L, Escanero JF. The role of automated measurement of red cell subpopulations on the Sysmex XE 5000 analyzer in the differential diagnosis of microcytic anemia. Int J Lab Hematol 2011;33:30–6.10.1111/j.1751-553X.2010.01237.xSearch in Google Scholar PubMed

51. Urrechaga E, Hoffmann JJ, Izquierdo S, Escanero JF. Differential diagnosis of microcytic anemia: the role of microcytic and hypochromic erythrocytes. Int J Lab Hematol 2015;37:334–40.10.1111/ijlh.12290Search in Google Scholar PubMed

52. England JM, Bain BJ, Fraser PM. Differentiation of iron deficiency from thalassaemia trait. Lancet 1973;1:1514.10.1016/S0140-6736(73)91856-4Search in Google Scholar

53. Sehgal K, Mansukhani P, Dadu T, Irani M, Khodaiji S. Sehgal index: a new index and its comparison with other complete blood count-based indices for screening of beta thalassemia trait in a tertiary care hospital. Indian J Pathol Microbiol 2015;58:310–5.10.4103/0377-4929.162862Search in Google Scholar PubMed

54. Yuen SC, Brown RD, Forsyth CJ, Zarkos KB. A quick differentiation between iron deficiency and thalassemia syndrome. Austral J Med Sci 1996;17:106–9.Search in Google Scholar

55. AlFadhli SM, Al-Awadhi AM, AlKhaldi D. Validity assessment of nine discriminant functions used for the differentiation between iron deficiency anemia and thalassemia minor. J Trop Pediatr 2007;53:93–7.10.1093/tropej/fml070Search in Google Scholar PubMed

56. Madan N, Sikka M, Sharma S, Rusia U, Kela K. Red cell indices and discriminant functions in the detection of beta-thalassaemia trait in a population with high prevalence of iron deficiency anaemia. Indian J Pathol Microbiol 1999;42:55–61.Search in Google Scholar

57. Miguel A, Linares M, Miguel A, Miguel-Borja JM. Red blood cell distribution width analysis in differentiation between iron deficiency and thalassemia minor. Acta Haematol 1988;80:59.10.1159/000205600Search in Google Scholar PubMed

58. Aslan D, Gumruk F, Gurgey A, Altay C. Importance of RDW value in differential diagnosis of hypochrome anemias. Am J Hematol 2002;69:31–3.10.1002/ajh.10011Search in Google Scholar PubMed

Received: 2016-9-24
Accepted: 2016-12-27
Published Online: 2017-2-9
Published in Print: 2017-8-28

©2017 Walter de Gruyter GmbH, Berlin/Boston

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https://doi.org/10.1515/cclm-2016-0856
Keywords for this article
diagnostic performance; discriminant formula; iron deficiency anemia; microcytic erythrocytes; thalassemia

Articles in the same Issue

  1. Frontmatter
  2. Editorials
  3. Reporting LDL-cholesterol levels in the era of intensive lipid management: a clarion call
  4. The challenges of genetic risk scores for the prediction of coronary heart disease
  5. Reviews
  6. Advanced lipoprotein testing for cardiovascular diseases risk assessment: a review of the novel approaches in lipoprotein profiling
  7. A review of the challenge in measuring and standardizing BCR-ABL1
  8. Mini Review
  9. Challenges in the analysis of epigenetic biomarkers in clinical samples
  10. Opinion Paper
  11. Defining a roadmap for harmonizing quality indicators in Laboratory Medicine: a consensus statement on behalf of the IFCC Working Group “Laboratory Error and Patient Safety” and EFLM Task and Finish Group “Performance specifications for the extra-analytical phases”
  12. Genetics and Molecular Diagnostics
  13. Assessment of EGFR mutation status using cell-free DNA from bronchoalveolar lavage fluid
  14. General Clinical Chemistry and Laboratory Medicine
  15. A survey of patients’ views from eight European countries of interpretive support from Specialists in Laboratory Medicine
  16. Verification of examination procedures in clinical laboratory for imprecision, trueness and diagnostic accuracy according to ISO 15189:2012: a pragmatic approach
  17. Expressing analytical performance from multi-sample evaluation in laboratory EQA
  18. A candidate reference method for serum potassium measurement by inductively coupled plasma mass spectrometry
  19. Practical motives are prominent in test-ordering in the Emergency Department
  20. Technical and clinical validation of the Greiner FC-Mix glycaemia tube
  21. Comparison of pneumatic tube system with manual transport for routine chemistry, hematology, coagulation and blood gas tests
  22. Accuracy of cerebrospinal fluid Aβ1-42 measurements: evaluation of pre-analytical factors using a novel Elecsys immunosassay
  23. Evaluation of cannabinoids concentration and stability in standardized preparations of cannabis tea and cannabis oil by ultra-high performance liquid chromatography tandem mass spectrometry
  24. Analytical performance and diagnostic accuracy of six different faecal calprotectin assays in inflammatory bowel disease
  25. Novel immunoassays for detection of CUZD1 autoantibodies in serum of patients with inflammatory bowel diseases
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  29. Reference ranges of thromboelastometry in healthy full-term and pre-term neonates
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