Original Article Frequency of Beta Thalassemia Trait in Pediatric Age Group in a Tertiary Care Hospital in South India B.N. Krishnamurthy 1, S.R.Niveditha 2 *, Poornima Shankar 3 1 Dept of Pathology, Sri Jayadeva Institute of Cardiovascular Sciences and Research, Bengaluru, India 2 Dept of Pathology, Kempegowda Institute of Medical Sciences, Bengaluru, India 3 Dept of Pediatrics, Kempegowda Instiute of Medical Sciences, Bengaluru, India Keywords: Discriminant Functions, Beta Thalassemia Trait, Hb Electrophoresis, Paediatric Age Group ABSTRACT Background: Approximately 3% of world s population carry β-thalassemia genes. The prevention of birth of Beta Thalassemia major children lies in effectively screening the carriers. Prevalence of β-thalassemia trait (BTT) varies from 3.5% to 14.9% in India. The objective of the present study was to study the frequency of BTT in pediatric age group at a medical college hospital in Bengaluru and compare the effectiveness of various discriminant functions( DFs) in predicting BTT in microcytic cases. Methods: From January-2010 to June-2011, 574 pediatric cases with MCV<80fl were screened for possible BTT with five DFs ie., Mentzer index ( DF1), Shine and Lal (DF2), Srivastava Index (DF3), RDW index (DF4 ) and Green and King index (DF5). Cases with 2 positive DFs were subjected to haemoglobin electrophoresis on agarose gel at ph 8.6. Cases with HbA 2 levels 4.0%, were diagnosed as BTT. Result: About 195 cases showed positivity for at least two of the DFs suggesting BTT, among whom HbA 2 level 4.0 was seen in 119 cases ( frequency of 19.76%). Cases with BTT, majority (55.63%) showed normocytic normochromic blood picture with a mean HbA 2 of 5.22± 0.79%, mean RBC count of 4.94±0.48 x 10 12 /l and mean Haemoglobin of 11.38±1.86 gms/dl. DF2, DF4 and DF5 showed greater sensitivity ( 85.84%, 85.85% & 82.3% respectively). Conclusion: Frequency of BTT was 19.76% among pediatric age group with microcytosis. DF2, DF4 and DF5 along with routine hemogram data in microcytic cases could effectively discriminate between BTT and non-btt. Being a community based hospital catering predominantly to vokkaliga community, the high frequency of BTT could reflect the increased prevalence, thereby creating a need for awarenesss and conducting regular screening programmes to detect BTT. *Corresponding author: Dr S.R.Niveditha, Professor, Dept of Pathology, Kempegowda Institute of Medical sciences, BSK 2nd Stage, Bengaluru-560070, India Phone: +91-9845485544 E-mail: srniveditha@gmail.com This work is licensed under the Creative commons Attribution 4.0 License. Published by Pacific Group of e-journals (PaGe)
Original Article A-144 Introduction β-thalassemia is the commonest inherited haemoglobinopathy all over the world 1 and is the most common single gene disorder in our country.in India every year over 9000 Thalassemic children are born and, an estimated annual average consumption of 27 units of blood and 4, 00,000 Rupees worth of drugs are needed to manage each β-thalassemia patient according to the recommended standards. Hence the financial burden induced is tremendous especially in a resource restricted country like India. The most effective approach to reduce the disease incidence is, implementation of carrier screening programs, offering genetic counselling, prenatal diagnosis and selective termination of affected fetuses. 2 Prevalence of BTT varies from 3.5-14.9% in various regions of India, 1 however most of the Indian studies are based in northern India 1,2,. To the best of our knowledge we did not find any studies regarding prevalence of BTT in Karnataka in pediatric age group and hence this study was formulated to study the frequency of BTT at department of pathology, Kempegowda institute of Medical sciences, Bengaluru. Aims and Objectives: To screen all children in the age group of 6 months to 18 years with microcytosis (MCV<80fl) for possible BTT with a set of discriminant indices (DFs). To diagnose BTT in children with two positive DFs by haemoglobin electrophoresis. To examine the diagnostic accuracy of the discriminations indices (Mentzer s, Shine and Lal, Srivastava, RDW (RDWI) and Green and King) in the diagnosis of BTT. Materials and Methods All pediatric ( 6 months to 18 yrs) blood samples received in the department of pathology for routine hemogram were run on coulter (ABX Pentra-60-HORIBA ABX Diagnostics). Samples with microcytosis ie >80fl were separated and included in study population (n=574) after obtaining informed consent. Mentzer s, Shine and Lal s, Srivastava s, RDW and Green and King s Indices were calculated. The discrimination limits (cut-off point), which suggested BTT and NON-BTT were as suggested in table 1. Those cases positive for at least 2 of the above discriminant functions were further subjected to haemoglobin electrophoresis (Horizontal electrophoresis tank and power supply by Helena Laboratories, Beaumount, Texas) on agarose gel at alkaline ph (8.6)using the SAS-MX alkaline Hb-10 kit. 8 Quantitation of HbA 2 was done by an automated densitometer scanner using HELENA software. Cases with HbA 2 4.0% were considered diagnostic for BTT. The relative percentages of each haemoglobin type on the gel could be determined by densitometry of the completed gel at 595nm. (fig 1) Fig. 1: Agarose gel plate showing prominent HbA2 bands ( 4.0%) in all samples except sample no. 5 Statistical methods: Chi-square test was used to test the significance of proportions of lab parameters between BTT and NON-BTT diagnosed based on electrophoresis. Student t test (independent) was used to find the significance of mean values of lab parameters and discriminant functions to differentiate between BTT and NON-BTT. The Odd s ratio was used to find the strength of relationship of BTT and lab parameters. The multivariate Logistic Regression was used to find the significant predictors among lab parameters and discriminant functions of BTT Statistical software: Microsoft Excel 2010 has been used to generate descriptive statistics. The statistical software namely STATA 10.0 IC FOR WINDOWS (COLLEGE STATION, TEXAS USA) was used for the univariate and multivariate analyses. Result Of the 574 cases of microcytosis, around 39.9% of study population were in 1-5 years age group followed by 29.62% in the age group >10 years. The study population consisted of 59% males and 41% females. Majority were Hindus (78.22%) by religion followed by Muslims (19.52%) and Christians (1.92%). Possible BTT was suggested in 195 (34%) out of 574 cases of microcytosis, in whom at least two of the five DFs were beyond the cut off limits. All these 195 cases were subjected to Hb electrophoresis. Of these, 113cases (n=195) showed http://www.pacificejournals.com/aabs
A-145 AABS; 3(2): 2016 increased HbA 2 in the range of 4.01 to 7.39% and mean 5.22 ± 0.79%. The HbA 2 levels in non-btt group ranged between 0.3-3.97 with a mean of 3.01 ± 0.77. The prevalence of Beta thalassemia trait was 19.69% in the present study.the highest prevalence was observed in Muslims (31/112). As the study population contained majority of Hindus (78.22%) it is but obvious that prevalence of BTT was seen in good number in the same group (79/449) The RBC count was >5.0 million/cu mm in 43.36% of BTT cases while only 9.33% of Non-BTT cases showed increased red cell count, which was statistically significant (p value <0.0001). Mean RBC count was significantly more in BTT (4.94x 10 12 cells/l) when compared to NON-BTT (4.44x 10 12 cells/l). However the haemoglobin was above 10 gm% in 85% of BTT cases(mean of 11.65g/dl ). MCH was lower i.e. <26.5 pg in 84.96% cases of BTT with a significant p value of <0.01. RDW was significantly lower in 64.60% of i.e., in 73/113 BTT cases. Hence high RBC count, low MCH and low RDW levels were significantly associated with BTT. (table2) On peripheral smear examination majority of BTT cases (55.63%) presented with normocytic normochromic blood picture followed by uniform microcytosis.target cells and basophilic stippling were also positively associated with BTT. Although this association is significant, the small numbers of subjects hint towards random occurrence of this association. Association of Discriminant Functions: (table 3) All the discriminant functions were positively associated with BTT with significant p values. The most sensitive DF was found to be DF4 and DF2 with sensitivity of 85.85% and 85.84%, respectively,however the specificity of DF2 was lower (31.02%). Srivastava index (DF3) showed highest specificity (94.36%), but lowest sensitivity (15.93%). Lowest false positivity (3.47%) was seen with DF3 whereas DF2 showed highest false positivity (68.98%). The DF4 showed highest PPV (53.30%) whereas DF2 showed lowest PPV (22.99%). The DF4 showed highest NPV (95.92%) followed closely by DF5(94.92%). Multivariate Logistic Regression: (table 4) The diagnostic values are obtained independently and will not account for the interaction between the parameters. Hence multivariate logistic regression analysis was done to evaluate the best combination of DFs to screen cases of BTT. All DFs were significantly associated with BTT. Subjects having DF1<13 were 5.09 times more at risk of having BTT compared to those with DF1 13. Subjects having DF4 220 were 7.74times more at risk having BTT compared to those with DF4>220 while subjects having DF5<65 were 4.50 times more at risk having BTT compared to those with DF1 65. Discussion The classic heterozygote carrier of BTT is usually asymptomatic. 1 The diagnosis is made through evaluation of positive family history or during population screening. 9 Though family history of thalassemia is important, a significant number of patients do not have previously affected family members. 10 Given the seriousness of homozygous β-thalassemia, population/risk group screening for BTT is important to enable family screening and genetic counseling.1 In this direction, an algorithm was used in the present study to segregate cases of non-btt and possible BTT by simple, cost effective screening tests like the discriminant indices using the red cell indices. 11 England and Fraser suggested that DFs should only be used when BTT is suspected in individuals with microcytosis of <80fl. 12 It has been proposed that electronic measurement of MCV<80fl should be used as a screening test for BTT as per the BCSH General Hematology Task Force guide lines for investigation of the α and β thalassemia traits. 13 Nishi Madan, Meera Sikka et al in 1999 studied 463 BTT cases and 40 controls and found sensitivity of MCV<80fl to be 98.21% and MCV<70fl to be 89.3%. 1 Hence in the present study all the pediatric cases with MCV<80fl were screened for possibility of BTT. About 1.5% to 3% of world population carries the β-thalassemia gene. The overall prevalence of BTT in India is about 3.3% 14 to 4.05%, 15 however the distribution Table 1 Discrimination Limits (cut off points) for BTT and NON-BTT Discrimination Functions BTT NON-BTT Mentzer index(mi) 3 MI =MCV/RBC <13 >13 Shine and Lal (S&L) 4 S & L = (MCV) 2 xmchx0.01 <1530 >1530 Srivastava Index 5 S = MCH/RBC <3.8 >3.8 RDW Index(RDWI) 6 RDWI = MCV x RDW/RBC 220 > 220 Green and King index (G&K) 7 G&K = (MCV) 2 x RDW/100xHb <65 >65 MCV Mean Corpuscular Volume. RBC Red Blood Cell count, MCH Mean Corpuscular Haemoglobin, RDW Red Cell Distribution Width, Hb Haemoglobin Annals of Applied Bio-Sciences, Vol. 3; Issue 2: 2016 e-issn: 2349-6991; p-issn: 2455-0396
Original Article A-146 1, 19-21, 25, 29, 30-33. Table 2: Mean pattern of various lab parameters in BTT in different studies Study No.of cases (n) Hb (g/dl) RBC (x10 12 /l) MCV fl MCH Pg MCHC % RDW% Das Gupta et at (1994) n=56 11.2±1.4 5.6±0.7 64.5±3.7 20±1.2 31.2±0.94 15.1±1.2 Mohamed M et al (1999) n=382 11.3±1.45 5.45±0.71 64.81±4.72 20.75±1.64-16.06±0.97 KhinEi Han et al (1992) n=133 11.5±1.6 5.9±1.0 62.7±12.1 19.9±3.5 29.3±2.2 - Nishi Madan et al (1999) n=337 11.6±1.6 5.56±0.76 64.7±4.8 20.6±3.6 - - (p<0.0001) (p<0.0001) Demir A et al (2002) n=37 10.88±0.82 5.4±0.41 61.66±3.98 20.54±2.03 32.38±1.09 14.91±1.13 Ahmed Suliman (2006) n=307 12±1.6 6.53±0.75 61±6.8 20.2±2.4 - - Rathod DA et al (2007) n=170 10.34±0.015 5.52±0.07 62.99±0.52 18.83±0.20-15.58±0.28 Rao et al (2009) n=145 10.3±2.1 5.06±0.9 68.6±7.4 20.5±2.6 28.3±1.8 - Patel Jet al (2009) n=70 10.14 5.37 63.15 18.75 29.92 15.04 Nishi Madan et al (2010) n=449 10.9±1.1 5.5±0.6 62±7 19.8±2.1 31.7±2.5 - Present study n-113 11.65±1.71 4.94±0.48 69.01±7.37 23.62±3.27 34.17±1.89 14.91±2.63 Table 3: Diagnostic values of Discriminant Functions with respect to Electrophoresis Discriminant Functions Diagnostic values in relation to Electrophoresis Sensitivity(%) Specificity (%) PPV NPV DF1(<13) MCV/RBC 30.97 92.62 50.72 84.55 DF2(<1530)(MCV)2xMCHX0.01 85.84 29.50 22.99 89.47 DF3(<3.8) MCH/RBC 15.93 94.36 40.91 82.08 DF4( 220) MCVxRDW/RBC 85.85 81.56 53.30 95.92 DF5(<65) (MCV)2xRDW/100xHb 82.3 81.13 51.67 94.92 Table 4: Multivariate Logistic Regression for BTT for Discriminant Functions Model Parameters Adjusted Odds Ratio Estimates of Multivariate Logistic Regression Model 95% Confidence Interval P value Lower Higher DF1(Mentzer) 5.09 1.66 15.64 0.00 DF2 (shine & Lal) 1.97 0.98 3.95 0.06 DF3 (srivastava) 0.22 0.06 0.80 0.02 DF4 (RDW index) 7.74 3.35 17.87 <0.0001 DF5(<65)Green and King index 4.50 2.04 9.93 <0.0001 of β thalassemia gene is not uniform in the Indian subcontinent and therefore has varying frequency in different regions. Different authors have recorded the prevalence of BTT in various geographic areas of India.(table 5) The prevalence of BTT in our study was 19.69% and is in the range of prevalence as studied by various authors in India, in the recent times, as shown above. Prevalence of BTT in general population in Karnataka has not been studied by many authors. In a hospital based study at our institute in the year 2006 24 the frequency of BTT was 6.8% in general population. A multicentre trial by D Mohanty et al in 2013 included Bengaluru as one of the centers to address this issue. In their study including Kolkata, Dibrugarh, Ludhiana, Mumbai and Vadodara, Bengaluru was also one of the centers. 23 They recorded a prevalence of 2.16% in Bengaluru with highest prevalence among Jains(9.6%), followed by Rajputs(6.3%), sunni muslims(5.8%), Shiya muslims(6.3%) and vokkaligas (2.1%). It is interesting to note that in a general population, Vokkaligas recorded a rate of 2.1%, however our hospital caters predominantly to vokkaliga community thereby increasing the frequency rate. Prevalence of BTT in pediatric age group has been studied by few authors( Demir et al, 25-58.7%, Ambekar et al 26-0.5%, A Earley et al 27-21%,Nishi Madan 21-2.68% in Mumbai and 5.47% in Delhi children).to the best of our knowledge we could not find any literature regarding the prevalence of BTT in pediatric age group, in Karnataka http://www.pacificejournals.com/aabs
A-147 AABS; 3(2): 2016 so as to compare. However Madan N et al recorded a frequency of 6.5% BTT in school going children in Delhi who originally hailed from Karnataka. 21 In a diverse country like India, the frequency of BTT has 72, 100, been found to vary in various religions and sub castes. 103,106 In the present study 78.22% of patients were Hindus. We could not correlate the frequency with various sub castes due to non-availability of records. BTT cases generally have mild anemia with mild decrease in Hb value (table 2). In the present study mean RBC count was higher in BTT as compared to non-btt, the mean MCV count and mean MCH were lower and comparable to the findings in other studies. However mean MCHC showed no difference as compared to non-btt. In the present study mean RDW count was 14.91 ± 2.63% in BTT as compared to 15.36 ± 2.75% in non-btt confirming that the red cells in cases of BTT are indeed microcytic homogeneous. BTT results from mutations affecting single beta-globin locus.the mutations generally reduce the output of beta globin RNA and therefore the synthesis of beta globin but does not produce structurally abnormal haemoglobin. Therefore given the same amount of haemoglobin, red cells show microcytosiswith mild anisocytosis in BTT compared to IDA in peripheral smear. Target cells and basophilic stippling are encountered mpre frequently in BTT. 34 peripheral blood film examination usually reveals microcytosiswith mild anisocytosis),target cells and fine basophilic stippling than with IDA given the same level of anemia. 34,35 In the present study majority of the cases presented with normocytic, normochromic blood picture followed by uniform microcytic hypochromic blood picture without anisocytosis. BTT cases with microcytic hypochromic red cells showing mild anisocytosis were a minority. BTT cases showed good number of target cells while basophilic stippling was uncommon. The findings of peripheral smears were in concordance with other studies 13,33 in the literature. The various mathematical formulae using RBC indices have been proposed to differentiate BTT from IDA and to screen for BTT in patients with microcytic anemia 1. In the present study 574 pediatric cases with microcytosis (MCV<80fl), were screened with the various DFs. At least two of the five DF s were positive in 195 cases (33.97%) which suggested BTT. Shine and Lal &RDW indices were the most sensitive DFs(85.84%& 85.85%). Srivastav(DF3) and Mentzer s (DF1) were the DFs with highest specificity (94.36%& 92.62% respectively). With a high sensitivity, DF 2&4 are good screening tests while DF 3&1 are good diagnostic tests due to their high specificity compared to other DFs.(table3) Mulltivariate logistic regression analysis showed, DFs 1, 2, 3 and 4 were associated with higher risk of BTT with reference to their respective categories. DF3 was however associated with lower risk of BTT and this correlates very well with a very low sensitivity observed in our study. To our knowledge there is no published literature on multivariate logistic regression analysis of DFs to validate our results. In conclusion, differentiation of BTT from NON-BTT has important clinical implications in hematology and medicine. The present study demonstrates that a set of linear discriminant functions (DF2 and DF4) using routine hemogram data can effectively discriminate between BTT from non-btt. The diagnosis of BTT relies on an accurate estimation of HbA 2 levels. A raised HbA 2 level ( 3.9%) 39 preferably by Hb electrophoresis on cellulose acetate or by HPLC is the gold standard for the diagnosis of BTT. HbA2 estimation by scanning densitometry is not recommended due to overestimation. 28 However as a pilot study, we performed Electrophoresis on agarose gel at alkaline ph on 195 (2 or more DF positive) cases, after screening 574 microcytic cases. Chopra et al 18 studied 1032 patients of anemia and conducted electrophoresis on all the cases with alkaline buffered agarose gel and later quantified the various bands using densitometer as in our study. A total of 176 cases were found to be BTT with a cut off >3.5% of HbA 2. The cut off levels of HbA2 to label one as carrier of BTT varies between various studies ranging from >3.0%, >3.5%, >3.9% to >4.0%. Mohamed M et al 30 in 1999 conducted study on 382 patients of which 34 patients were diagnosed as BTT based on Hb electrophoresis on cellulose acetate (CAE). HbA 2 values more than 3.5% on elution were diagnosed as BTT. Desai S.N. et al 43 in 1998 included 95 cases for comparison of CAE electrophoresis with Fast Protein Liquid Chromatography (FPLC). They found both techniques were equally comparable and reproducible. 43 In the present study 113cases (n=195) showed increased HbA 2 ( 3.9%) with a mean HbA 2 of 5.22± 0.79 which was higher than non BTT cases (3.01± 0.77). HbA2 levels are altered by various factors. For eg., decreased HbA2 levels are seen in cases of iron deficiency, sideroblastic anemia, silent Beta thalassemia alleles, βδ thalassemia, HbH disease, Hb Lepore and erythroleukemia while increased levels are observed in cases of megaloblastic anemia, in patients on anti-retroviral therapy and hypothyroidism. 28 Annals of Applied Bio-Sciences, Vol. 3; Issue 2: 2016 e-issn: 2349-6991; p-issn: 2455-0396
Original Article A-148 Table 5: Frequency of BTT in India by various authors Authors BTT year Balgir RS et al 16 (Orissa) 18.2% 2004 Mulchandani D et l 17 (sindhi community, Nagpur) 16.81% 2008 Chopra GS etal 18 (AFMC, New Delhi ) 17.0% 2008 Patel J et al 19 (Gujarat, India) 16.35% 2009 Rao S et al 20 ( New Delhi) 18.1% 2010 Madan N et al 21 ( Mumbai and Delhi) 4.05% 2010 Vani chandrashekar et al 22 (Chennai) 37.09% 2011 D.Mohanty et al(multicentre trial) 23 Bengaluru 2.16%(Bengaluru) 2013 Present study n=113, p=574 19.69% 2011 n = number of cases of a particular disease studied, p= number of population of a particular disease studied. Table 6: Comparison of sensitivity (Number of patients correctly classified as BTT) of BTT with other studies Studies Number of cases Sensitivity (%) DF1 DF2 DF3 DF4 DF5 George Klee et al (1976) 36 30 84.6-84.6 - - KhinEi Han et al (1992) 31 133 71.4 88.7 66.9 - - Mamatha et al (1997) 37 142 66.2 - - 55.6 - Das Gupta et al (1997) 29 56 60.0 - - - - Mohamed M et al(1999) 30 382 70.6 - - - 90.3 Nishi Madan et al (1999) 1 337 88.7 97.9 89.0 - - Demir A et al (2002) 25 63 86.0 100 60.0 100 97.0 Ntaios G et al (2007) 38 373 59.78 - - 63.8 70.06 Rathod DA et al (2007) 14 170 92.0 99.01 89.3-91.1 Niazi M et al (2010) 39 223 89.0 72.0 61.0 91.0 86.0 Present study (2011) 113 30.21 85.84 16.9 86.62 80.28 Table 7: Comparison of Mean HbA2 values in BTT cases with other studies Study Year No. of cases Mean HbA 2 % KhinEi Han et al 31 1992 133 5.7±1.3 Desai S.N. et al 43 1998 27 5.34±0.467 Mohamed M et al 30 1999 134 4.94±0.59 Ahmed Al-Suliman 32 2005 307 5.3±1.2 Rathod DA et al 2007 170 5.84±0.06 Rao et al 20 2009 145 5.5±0.6 Present study 2011 113 5.22± 0.79 The higher rate of BTT in our study may be attributed to the predominantly vokkaliga community that our hospital is catering to or to the fact that we have used scanning densitometry to quantitate HbA2 levels(following agargel electrophoresis at alkaline ph) which is known to overestimate. 28 Nutritional deficiencies affecting HbA2 like megaloblastic anemia and iron deficiency anemia, hormonal disturbances like hypothyroidism and DNA studies for co-existence of delta mutation could not done. Conclusion We conclude that the differentiation of BTT from non-btt has an important clinical implication in hematology and medicine. The present study demonstrates that set of cost http://www.pacificejournals.com/aabs
A-149 AABS; 3(2): 2016 effective screening tests like DF2, DF4 and DF5 along with routine hemogram data in microcytic cases can effectively filter probable cases of BTT so that they can be subjected to confirmatory tests like HbA 2 quantitation. Prevalence of BTT in the pediatric population attending our hospital is significant suggesting a need to create awareness about the disease and it s clinical implications highlighting the necessity to set up regular screening programmes. Practice of consanguineous marraiges are higher in southern India, hence family work-up should be performed in positive cases. Reference 1. Madan N, Meera S, Satendra S, Rusia U, Kusum Kela. Red cells Indices and Discriminant Functions in the Detection of Beta-Thalassemia Trait in a Population with High Prevalence of Iron Deficiency Anemia. Indian J Pathol Microbiol 1999;42(1) :55-61. 2. Maheshwari M, Arora S, Kabra M, Menon PSN. Carrier screening and prenatal Diagnosis of Beta- Thalassemia. Indian Pediatr 1999;36:1119-1125. 3. Mentzer WC. Differentiation of iron deficiency from thalassemia trait. Lancet 1973;1 : 882. 4. Shine I, Lal S. A Strategy to detect Alpha thalassemia major. Lancet 1977; 1:692-694. 5. Srivastava PC. Differentiation of thalassemia minor from iron deficiency. Lancet 1973; 2:154-155. 6. Jayabose S, Giavanelli J, Levendoglu-Tugal O, Sandoval C, Özkaynak F, Visintainer P.Differentiating iron deficiency index. J Pediatr Hematol 1999; 21: 314. 7. Green R, King R. A new red blood cell discriminant incorporating volume dispersion for differentiating iron deficiency anaemia from thalassemia minor. Blood Cells. 1989;15:481 495 8. Barbara Wild, Barbara J. Bain: Investigation of abnormal hemoglobins and thalassemia. SM Lewis, BJ Bain, I Bates. Dacie and Lewis Practical Hematology. 10 th ed, Churchill Livingstone, 2006, 271-310 9. Caterina B, Galanellao R. Thalassemia and Related Disorders: Quntitative disorders of Hemoglobin Synthesis. John P. Gree et al. Wintrobes Clinical Hematology, 12 th edn, Lippincott Williams and Wilkins, 2009; 1083-1131 10. Louise L, Sylivia TS. Thalassemia: current approach to an old disease. Pediatr Clin N Am 2002;49:1165-1191 11. Lafferty JD, Mark A, Crowther, Mahmoud A Ali, Levine M. The evaluation of various mathematical RBC indices and their efficacy in discriminating between thalassemic and non-thalassemic microcytosis. Am J Clin Pathol 1996; 106:201-205. 12. Guidelines for investigation of the Alpha and Beta Thalassemia traits. The thalassemia Working Party of the BCSH General Hematology Task Force. J Clin Pathol 1994;47 : 289-295. 13. England JM, Fraser PM. Differentiation of iron deficiency from thalassemia trait by routine blood count. Lancet1973; 1:449-452. 14. Rathod DA, Kaur A, PatelV, Patel K, Kabrawala R, PatelV, Patel M and Shah P. Usefulness of Cell Counter Based Parameters and Formulas in Detection of β-thalassemia Trait in Areas of High Prevalence. Am J Clin Pathol 2007; 128:585-589 15. Madan N, Sharma S, Sood SK, Colah R, Bhatia HM. Frequency of β-thalassemia trait and other hemoglobinopathies in northern and western India Ind J Hum Gen. 2010;16(1).16-25 16. Balqir RS. Spectrum of haemoglobinopahies in the state of Orissa, India. A ten years cohort study. J Asso Phys India.2005:Dec;53:1021-1026. 17. Mulchandani DV, Fulare MB, Zodpey SP, Vasudeo ND. Prevalence and Some Epidemiological Factors of Beta Thalassemia Trait in Sindhi Community of Nagpur City, India.Indian Journal of Public Health. 2008;.52(1): 11-15. 18. Chopra GS, Nair V, VSM, Gupta PK, Mishra DK, Sharma A, Mathew OP. Spectrum of Haemoglobinopathies in a Tertiary CareHospital of Armed Forces. MJAFI, 2008; 64(4) ; 311-314. 19. Patel J, Patel A, Patel J, Kaur A, Patel V: Prevalence of Haemoglobinopathies in Gujarat, India: A Cross- Sectional Study. The Internet Journal of Hematology. 2009 Volume 5 Number 1.(ISSN:1540-2649 20. Rao S, Kar R, Gupta Sk, Chopra A &Saxena R. Spectrum of haemoglobinopathies diagnosed by cation exchange-hplc & modulating effects of nutritional deficiency anaemias from north India. Ind J Med Res. 2010;132;513-519. 21. Madan N, Sharma S, Sood SK, Colah R, Bhatia HM. Frequency of β-thalassemia trait and other hemoglobinopathies in northern and western India Ind J Hum Gen. 2010;16(1).16-25. 22. Chandrashekar V, Soni M. Hemoglobin Disorders in South India.International Scholarly Research Network (ISRN) Hematology Volume 2011, Article ID 748939, 6 pages, doi:10.5402/2011/748939. 23. D. Mohanty, R. B. Colah, A. C. Gorakshakar, R. Z. Patel, D. C. Master,J. Mahanta, S. K. Sharma, U. Annals of Applied Bio-Sciences, Vol. 3; Issue 2: 2016 e-issn: 2349-6991; p-issn: 2455-0396
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