Discrimination index of microcytic anemia in young soldiers: a single institutional analysis

Distinguishing Iron Deficiency Anemia From Beta-Thalassemia Trait: Comparative Analysis of CRUISE Index and Other Traditional Diagnostic Indices

Introduction Iron deficiency anemia and beta-thalassemia trait are two common and important differentials of microcytic hypochromic anemia. Various discrimination indices using two or more common complete blood cell count (CBC) parameters have been used to distinguish between the two since 1973. Recently, a new discriminant index, the CRUISE index, was proposed in the year 2019. The efficacy of various older indices along with the CRUISE index was evaluated for patients in our geographical area. Materials and method Ours was a laboratory-based, cross-sectional study where 100 patients, based on inclusion and exclusion criteria, with microcytic hypochromic anemia were evaluated for CBC parameters along with serum ferritin and hemoglobin-high performance liquid chromatography (Hb HPLC). A total of eight discrimination indices namely, Mentzer, Srivastava, Shine & Lal, Green & King, RDWI, England & Fraser, Kerman I and CRUISE index were used and evaluated for their diagnostic efficacy using different statistical parameters. ROC curves were obtained and a new cut-off value was proposed for our population. Data was analysed using Microsoft Excel (Microsoft® Corp., Redmond, WA, USA) and SPSS v29.0.2.0 (20) (IBM Corp., Armonk, NY, USA). Results Out of the total 100 cases, 39 were beta-thalassemia trait and 61 were iron deficiency anemia cases. The average age was 36.7 (±12.7 SD) years. Among the 73 females, 43 were diagnosed as iron deficiency anemia (IDA) and 30 as beta-thalassemia trait (BTT) cases. Among the 27 males, 18 were diagnosed as IDA and nine as BTT cases. The mean values were significantly lower in IDA patients for mean corpuscular volume (MCV) (p=.008), mean corpuscular haemoglobin (MCH) (p=.003), and mean corpuscular haemoglobin concentration (MCHC) (p=.003) and significantly higher for red cell distribution width (RDW) (p=.020). The mean ferritin levels in cases of IDA were 7.61 (±3.75) mcg/L and in BTT were 87.09 (±66.77 SD) mcg/L. The mean HbA2 levels in IDA cases were 2.75% (±0.41% SD) and BTT cases were 5.57% (±0.73% SD). CRUISE index revealed the highest AUC (0.934), YI (76.21) and accuracy (90%) followed by the Mentzer index with a diagnostic accuracy of 81%. Shine & Lal index revealed the lowest AUC (0.710), YI (3.28) and accuracy (41%). Conclusion CRUISE index, which was recently proposed, was ranked 1st in terms of AUC, YI, and accuracy and was considered 2nd best in terms of sensitivity for differentially diagnosing the two conditions. Mentzer index, a commonly used index, also revealed a high diagnostic accuracy in our study for differentiating BTT from IDA. CRUISE index being a novel index, more research work needs to be carried out in various other geographical setups to evaluate the efficacy of this index.

Comparison of screening indicators for different types of thalassemia carriers in Hunan Province

Background

Carrier screening is the most effective method to block the occurrence of thalassemia. However, due to differences in race and genotype, MCV, MCH, HbA2 and other indicators are far from each other. The purpose of this study is to evaluate the common screening indicators of a, b and ab-compound thalassemia carriers in Hunan Province, and try to use the relevant formulas in the existing literature to predict and distinguish different types of thalassemia carriers.

Methods

Receiver operating characteristic curve (ROC curve) combined with Youden index was utilized to analyze results of blood routine examination, hemoglobin electrophoresis, and literature-related formulas for 1111 a-thalassemia carriers, 464 b-thalassemia carriers and 24 ab-thalassemia carriers.

Multi-criteria decision making to validate performance of RBC-based formulae to screen [Formula: see text]-thalassemia trait in heterogeneous haemoglobinopathies

BACKGROUND

India has the most significant number of children with thalassemia major worldwide, and about 10,000-15,000 children with the disease are born yearly. Scaling up e-health initiatives in rural areas using a cost-effective digital tool to provide healthcare access for all sections of people remains a challenge for government or semi-governmental institutions and agencies.

METHODS

We compared the performance of a recently developed formula SCS[Formula: see text] and its web application SUSOKA with 42 discrimination formulae presently available in the literature. 6,388 samples were collected from the Postgraduate Institute of Medical Education and Research, Chandigarh, in North-Western India. Performances of the formulae were evaluated by eight different measures: sensitivity, specificity, Youden's Index, AUC-ROC, accuracy, positive predictive value, negative predictive value, and false omission rate. Three multi-criteria decision-making (MCDM) methods, TOPSIS, COPRAS, and SECA, were implemented to rank formulae by ensuring a trade-off among the eight measures.

RESULTS

MCDM methods revealed that the Shine & Lal and SCS[Formula: see text] were the best-performing formulae. Further, a modification of the SCS[Formula: see text] formula was proposed, and validation was conducted with a data set containing 939 samples collected from Nil Ratan Sircar (NRS) Medical College and Hospital, Kolkata, in Eastern India. Our two-step approach emphasized the necessity of a molecular diagnosis for a lower number of the population. SCS[Formula: see text] along with the condition MCV[Formula: see text] 80 fl was recommended for a higher heterogeneous population set. It was found that SCS[Formula: see text] can classify all BTT samples with 100% sensitivity when MCV[Formula: see text] 80 fl.

CONCLUSIONS

We addressed the issue of how to integrate the higher-ranked formulae in mass screening to ensure higher performance through the MCDM approach. In real-life practice, it is sufficient for a screening algorithm to flag a particular sample as requiring or not requiring further specific confirmatory testing. Implementing discriminate functions in routine screening programs allows early identification; consequently, the cost will decrease, and the turnaround time in everyday workflows will also increase. Our proposed two-step procedure expedites such a process. It is concluded that for mass screening of BTT in a heterogeneous set of data, SCS[Formula: see text] and its web application SUSOKA can provide 100% sensitivity when MCV[Formula: see text] 80 fl.

Novel Decision Tool for More Severe α-Thalassemia Genotypes Screening with Functional Loss of Two or More α-Globin Genes: A Diagnostic Test Study

After the exclusion of iron deficiency and β-thalassemia, molecular research for α-thalassemia is recommended to investigate microcytic anemia. Aiming to suggest more efficiently the molecular analysis for individuals with a greater chance of having a symptomatic form of the disease, we have developed and validated a new decision tool to predict the presence of two or more deletions of α-thalassemia, increasing considerably the pre-test probability. The model was created using the variables: the percentage of HbA₂, serum ferritin and mean corpuscular volume standardized by age. The model was trained in 134 patients and validated in 160 randomly selected patients from the total sample. We used Youden's index applied to the ROC curve methodology to establish the optimal odds ratio (OR) cut-off for the presence of two or more α-globin gene deletions. Using the OR cut-off of 0.4, the model's negative predictive value (NPV) was 96.8%; the cut-off point accuracy was 85.4%; and the molecular analysis pre-test probability increased from 25.9% to 65.4% after the use of the proposed model. This tool aims to assist the physician in deciding when to perform molecular studies for the diagnosis of α-thalassemia. The model is useful in places with few financial health resources.

Performance analysis of machine learning algorithms and screening formulae for β-thalassemia trait screening of Indian antenatal women

BACKGROUND

Currently, more than forty discrimination formulae based on red blood cell (RBC) parameters and some supervised machine learning algorithms (MLAs) have been recommended for β-thalassemia trait (BTT) screening. The present study was aimed to evaluate and compare the performance of 26 such formulae and 13 MLAs on antenatal woman data with a recently developed formula SCS_BTT, which is available for evaluation in over seventy countries as an Android app, called SUSOKA[16].

METHODS

A diagnostic database of 2942 antenatal females were collected from PGIMER, Chandigarh, India and was used for this analysis. The data set consists of hypochromic microcytic anemia, BTT, Hemoglobin E trait, double heterozygote for Hemoglobin S and BTT, heterozygote for Hemoglobin D Punjab and normal subjects. Performance of the formulae and the MLAs were assessed by Sensitivity, Specificity, Youden's Index, and AUC-ROC measures. A final recommendation was made from the ranking obtained through two Multiple Criteria Decision-Making (MCDM) techniques, namely, Simultaneous Evaluation of Criteria and Alternatives (SECA) and TOPSIS.

RESULTS

It was observed that Extreme Learning Machine (ELM) and Gradient Boosting Classifier (GBC) showed maximum Youden's index and AUC-ROC measures compared to all discriminating formulae. Sensitivity remains maximum for SCS_BTT. K-means clustering and the ranking from MCDM methods show that SCS_BTT, Shine & Lal and Ravanbakhsh-F4 formula ensures higher performance among all formulae. The discriminant power of some MLAs and formulae was found considerably lower than that reported in original studies.

CONCLUSION

Comparative information on MLAs can aid researchers in developing new discriminating formulae that simultaneously ensure higher sensitivity and specificity. More multi-centric verification of the formulae on heterogeneous data is indispensable. SCS_BTT and Shine & Lal formula, and ELM and GBC are recommended for screening BTT based on MCDM. SCS_BTT can be used with certainty as a tangible cost-saving screening tool for mass screening for antenatal women in India and other countries.

Clinical utility of Abbott Alinity hq extended red blood cell parameters in differentiating β-thalassemia trait and iron deficiency anemia

INTRODUCTION

The objective of the study was to evaluate the performance of the Abbott Alinity hq advanced multi angle polarized scatter separation (MAPSS^TM )-based optical RBC technology, for the differentiation between iron deficiency anemia (IDA) and β-thalassemia carrier status.

METHODS

Four hundred and sixty-four samples were analyzed. 228 were healthy controls, 30 were β-thalassemia carriers, and 40 were IDA. Receiver operating characteristics analysis evaluated the performance of red cell parameters and mathematical formulas.

RESULTS

RBC concentration was the most efficient discriminant (area under the curve; AUC of 0.963, Youden Index of 0.88) followed by red blood cell distribution width in size distribution (AUC of 0.960 and YI of 0.86), and red blood cell distribution width coefficient of variation (AUC of 0.924, and YI of 0.74). The absolute reticulocyte concentration showed good diagnostic efficiency, with AUC of 0.808. Hemoglobin distribution width, the %CV of directly measured cellular hemoglobin concentration, and CHCr, the average hemoglobin concentration of reticulocytes have emerged as novel discriminating parameters, with AUC of 0.749 and 0.785, respectively. The England and Fraser index was the best discriminating mathematical formula based on Youden Index of 0.91. The Ricerca, red blood cell distribution width index, Green and King, and Mentzner Index formulas also showed strong discriminative power. The Shine and Lal index, together with the recent mathematical formula M/H, (ratio of percent microcytic and hypochromic red blood cells) demonstrated moderate performance with AUC of 0.796 and 0.740, respectively.

CONCLUSION

Extended red cell analysis delivered by the advanced optical technology on the Alinity hq hematology analyzer has efficient diagnostic utility in the initial discrimination of the two most common microcytic anemias: IDA and β-thalassemia trait.

Differential diagnosis of thalassemia and iron deficiency anemia in pregnant women using new formulas from multidimensional analysis of red blood cells

Background

Iron deficiency anemia (IDA) and thalassemia trait (TT) are the most common conditions of microcytic hypochromic anemia (MHA) in pregnant women. We used the BC-6800Plus analyzer to study the utility of erythrocyte and reticulocyte parameters for distinguishing TT from IDA in pregnant women.

Methods

A total of 454 anemic pregnant women, including 340 with IDA, 66 with β-thalassemia trait (β-TT) and 48 with α-thalassemia trait (α-TT), were included. Multiple comparisons among groups were performed, and diagnostic performance of parameters was determined using receiver operating characteristic (ROC) curve analysis, with P<0.05 indicating statistical significance.

Results

Reticulocyte production index (RPI) and the average volume of mature red blood cells (MCVm) in the IDA group were significantly higher than in the β-TT and α-TT groups. Red blood cell (RBC), reticulocyte percentage (Ret%), and RPI in the IDA group were significantly lower than in the α-TT and β-TT groups. We devised MHA 1=0.42× MCH -0.57× RPI -0.08× %MICROr -9.38 to distinguish IDA from α-TT. With a cut-off value of 0.61, the area under the receiver operating characteristic curve (AUC), sensitivity, and specificity were 0.868, 90.9%, and 68.5%, respectively. We devised MHA 2=0.04× %MICROr +0.12× MCVm -13.76× Ret# -6.29 to distinguish IDA from β-TT. With a cut-off value of 0.55, the AUC, sensitivity, and specificity were 0.878, 81.3%, and 80.3%, respectively.

Conclusions

Erythrocyte indices and formulas can be used as initial methods for the differential diagnosis of TT and IDA. MHA 1 and MHA 2 were the most useful indices in the differential diagnosis of α-TT from IDA and β-TT from IDA in pregnant women.

Microcytic anemia in children: parallel screening for iron deficiency and thalassemia provides a useful opportunity for thalassemia prevention in low- and middle-income countries

Microcytic anemia in children is commonly attributed to iron deficiency without attempting to find the cause. Inadequate investigations to exclude hemoglobinopathies lead to missed opportunities for identification of thalassemia carriers. Here we aim to describe the relative contribution of iron deficiency and thalassemia to microcytic anemia in children. This hospital-based prospective study was conducted at the Colombo North Teaching Hospital, Ragama, Sri Lanka. All newly diagnosed patients with microcytic anemia were recruited and data were collected using an interviewer-administered questionnaire. Full blood count, blood film, serum ferritin, c-reactive protein, quantification of hemoglobin sub-types and α-globin genotype were performed using 4 ml of venous blood. A total of 104 children (Male- 60.5%) were recruited. Iron deficiency was the cause for anemia in 49% whilst 16% and 10% had α- and β-thalassemia trait respectively. Seven (6.7%) children had co-existing iron deficiency and thalassemia trait while two coinherited α- and β-thalassemia trait. Children with β-thalassemia trait had significantly higher red cell count and lower mean corpuscular volume compared to children with iron deficiency. However, none of the red cell parameters were significantly different between children with α-thalassemia trait and iron deficiency. Iron deficiency contributes only to half of children with microcytic anemia; one-fourth had thalassemia trait. Co-existence of iron deficiency and thalassemia trait or co-inheritance of α- and β-thalassemia trait were found in 9%. Parallel investigation of children with microcytic anemia to diagnose iron deficiency and thalassemia provides an opportunity to identify thalassemia carriers which is beneficial for thalassemia prevention.

ThalPred: a web-based prediction tool for discriminating thalassemia trait and iron deficiency anemia

Background

The hypochromic microcytic anemia (HMA) commonly found in Thailand are iron deficiency anemia (IDA) and thalassemia trait (TT). Accurate discrimination between IDA and TT is an important issue and better methods are urgently needed. Although considerable RBC formulas and indices with various optimal cut-off values have been developed, distinguishing between IDA and TT is still a challenging problem due to the diversity of various anemic populations. To address this problem, it is desirable to develop an improved and automated prediction model for discriminating IDA from TT.

Methods

We retrospectively collected laboratory data of HMA found in Thai adults. Five machine learnings, including k-nearest neighbor (k-NN), decision tree, random forest (RF), artificial neural network (ANN) and support vector machine (SVM), were applied to construct a discriminant model. Performance was assessed and compared with thirteen existing discriminant formulas and indices.

Results

The data of 186 patients (146 patients with TT and 40 with IDA) were enrolled. The interpretable rules derived from the RF model were proposed to demonstrate the combination of RBC indices for discriminating IDA from TT. A web-based tool ‘ThalPred’ was implemented using an SVM model based on seven RBC parameters. ThalPred achieved prediction results with an external accuracy, MCC and AUC of 95.59, 0.87 and 0.98, respectively.

Conclusion

ThalPred and an interpretable rule were provided for distinguishing IDA from TT. For the convenience of health care team experimental scientists, a web-based tool has been established at http://codes.bio/thalpred/ by which users can easily get their desired screening test result without the need to go through the underlying mathematical and computational details.

Shine & Lal index as a predictor for early detection of β-thalassemia carriers in a limited resource area in Bandung, Indonesia

BACKGROUND

Thalassemia is the most common inherited disease in the world, involving α- or β-globin in red blood cells. Thalassemia cases rank fifth in the list of national catastrophic diseases in Indonesia; however, nationwide screening for thalassemia carriers is not yet mandatory. This study aimed to assess whether blood count metrics, such as the Shine & Lal index (SLI; MCV*MCV*MCH/100), might serve as a predictor to screen thalassemia carriers in a limited resource area where molecular methods are not readily available.

METHODS

During a family gathering of thalassemia patients, family members (n196) underwent a complete blood count test. Those with MCV < 80 fL and/or MCH < 27 pg and/or SLI < 1530 were further examined for Hb analysis. Only samples with HbA2 fraction > 4% or with a peak in the HbE fraction were sequenced to confirm β-globin gene mutations.

RESULTS

Of 196 family members, 117 (59.6%) had low MCV and/or low MCH and/or low SLI. The HbE fraction (mean 24.06% ± 0.95, range 22.4-26.5) was found in 27 (13.7%) cases, and all had a mutation at codon (CD)26 (c.79G > A). The mean HbA₂ fraction in these samples was 3.18% ± 0.62 (range 2.6-3.8). For samples with HbA2 > 4% (n30; 15.3%), all had mutations at IVS1nt5 (c.92 + 5 G > C; n28), CD8/9 (c.27_28insG; n1) and CD19 (c.59A > G; n1). The mean HbA₂ fraction with a mutation at IVS1nt5 (c.92 + 5 G > C) was 4.65% ± 0.77 (range 4.0-5.6). Interestingly, anaemia was only present in 25 and 57% of β-thalassemia carriers with mutations at CD26 (c.79G > A) and at IVS1nt5 (c.92 + 5 G > C), respectively.

CONCLUSIONS

The Shine & Lal index is helpful in the early screening of β-thalassemia carriers, since this index confirms mutations at CD-26 (c.79G > A) and at IVS1nt5 (c.92 + 5 G > C), which are both common mutations in Bandung, Indonesia. Further DNA analysis is a topic of interest to map variants in globin genes and their distribution across populations.

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

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.

Differentiation of beta thalassemia trait from iron deficiency anemia by hematological indices

Objective:

We aimed at finding out reliable parameter in the differentiation of iron deficiency anemia (IDA) and beta-thalassemia trait (β-TT) in the adult population subjected to Saudi Arabian Premarital Screening Program.

Methods:

A total of 620 adults (age range 21-36 years) reported during February 2012 to November 2012. Tests for serum iron and ferritin were carried out in individuals showing low hemoglobin (Hb). All the selected subjects’ samples were subjected to blood morphology, comparison of MCV, RBC count. Red Cell Distribution Width (RDW) was noted from the Coulter Report whereas Red Cell Distribution Width Index (RDWI) value was calculated for all the samples.

Results:

A total of one hundred &thirty-five individuals with hypochromic microcytic anemia having normal hemoglobin F and hemoglobin A2 < 3.2% were inducted in the study. Ninety-three were diagnosed having IDA, whereas thirty-two were having βTT. Ten individuals revealed other causes of anemia. The RBC count was higher, and MCV was much lower in βTT as compared to IDA. Both groups were subjected to RDW and RDWI, however, RDWI which showed better sensitivity and specificity for βTT.

Conclusion:

RDWI is a reliable and useful index for differentiation among IDA and βTT, as compared to RDW.