A decision support scheme for beta thalassemia and HbE carrier screening

Das, Reena; Datta, Saikat; Kaviraj, Anilava; Sanyal, Soumendra Nath; Nielsen, Peter; Nielsen, Izabela; Sharma, Prashant; Sanyal, Tanmay; Dey, Kartick; Saha, Subrata

doi:10.1016/j.jare.2020.04.005

Cited by 12 publications

(11 citation statements)

References 56 publications

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“…They used all the RBC indices and achieved very good sensitivities and negative predictive values of 100% with false positive rates ranging from 20 to 40% in validation cohorts. [18] We also used all the RBC indices and wide range of haemoglobin levels (7 g/dl to 15 g/dl) to obtain satisfactory results. Our dataset also included age groups in the range of 1-75 years and is therefore more inclusive and considers the age variations of RBC indices.…”

Section: Discussionmentioning

confidence: 99%

Prevalence of β-haemoglobinopathies in Eastern India and development of a novel formula for carrier detection

et al. 2020

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Beta thalassemia is the commonest inherited monogenic disorder and India forms a major part of the thalassemia belt in the world. Effective screening programmes and proper prenatal diagnosis are the only ways to eradicate the disease. Haemoglobin high-pressure liquid chromatography (HPLC) is the screening method employed for detection of thalassemia carriers. The aim of this paper was to investigate the prevalence and demographic profiles of thalassemia carriers in Eastern India. Haemogram data was used to develop a novel haematological index for thalassemia carrier detection. This was a retrospective analysis of data collected from 21,695 individuals at thalassemia screening camps. The prevalence of the common hemoglobinopathies and their regional variations were noted. Using stepwise discriminant analysis, RBC indices were analysed to develop a novel formula to help distinguish β-thalassemia carriers from normal individuals. Out of the total population analysed, β-hemoglobinopathy carrier prevalence was around 10%. HbE was the commonest hemoglobinopathy in the region. There was no difference in the prevalence rates of thalassemia carriers amongst religious communities. The formula generated was expressed as outcome = RBCx6.59 + MCHx0.527 − (HCTx0.782 + MCHCx0.395 + RDWx0.02 + 1.365). Any integer value more than 0.5 indicated the probability of carrier status while a value less than 0.5 was normal. The formula had a negative predictive value of > 96% and an accuracy of 89%. This study provides an audit of the common β-hemoglobinopathies in Eastern India. The regional variations and prevalence of hemoglobinopathies highlighted here may guide public health efforts. The formula generated from RBC indices can be used to screen individuals prior to HPLC testing, thereby reducing overall costs of thalassemia screening in the country.

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Section: Discussionmentioning

confidence: 99%

Prevalence of β-haemoglobinopathies in Eastern India and development of a novel formula for carrier detection

et al. 2020

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“…Table 5 summarizes a comparison of the results presented in this paper with those of others in the detection of thalassaemia using Hb electrophoresis images. In a few recent studies [ 10 , 38 , 39 ], detection accuracies of 93.7% were reported, using databases consisting of a small number of images. However, in our study, we used larger datasets than others and obtained consistent results.…”

Section: Resultsmentioning

confidence: 99%

Deep Learning Assisted Automated Assessment of Thalassaemia from Haemoglobin Electrophoresis Images

Khan

Ullah

Khan³

et al. 2022

Diagnostics

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Haemoglobin (Hb) electrophoresis is a method of blood testing used to detect thalassaemia. However, the interpretation of the result of the electrophoresis test itself is a complex task. Expert haematologists, specifically in developing countries, are relatively few in number and are usually overburdened. To assist them with their workload, in this paper we present a novel method for the automated assessment of thalassaemia using Hb electrophoresis images. Moreover, in this study we compile a large Hb electrophoresis image dataset, consisting of 103 strips containing 524 electrophoresis images with a clear consensus on the quality of electrophoresis obtained from 824 subjects. The proposed methodology is split into two parts: (1) single-patient electrophoresis image segmentation by means of the lane extraction technique, and (2) binary classification (normal or abnormal) of the electrophoresis images using state-of-the-art deep convolutional neural networks (CNNs) and using the concept of transfer learning. Image processing techniques including filtering and morphological operations are applied for object detection and lane extraction to automatically separate the lanes and classify them using CNN models. Seven different CNN models (ResNet18, ResNet50, ResNet101, InceptionV3, DenseNet201, SqueezeNet and MobileNetV2) were investigated in this study. InceptionV3 outperformed the other CNNs in detecting thalassaemia using Hb electrophoresis images. The accuracy, precision, recall, f1-score, and specificity in the detection of thalassaemia obtained with the InceptionV3 model were 95.8%, 95.84%, 95.8%, 95.8% and 95.8%, respectively. MobileNetV2 demonstrated an accuracy, precision, recall, f1-score, and specificity of 95.72%, 95.73%, 95.72%, 95.7% and 95.72% respectively. Its performance was comparable with the best performing model, InceptionV3. Since it is a very shallow network, MobileNetV2 also provides the least latency in processing a single-patient image and it can be suitably used for mobile applications. The proposed approach, which has shown very high classification accuracy, will assist in the rapid and robust detection of thalassaemia using Hb electrophoresis images.

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“…In India, approximately 10,000 children are born with -TM every year, and there are nearly 42 million carriers of BTT, with some communities like Sindhis, Gujaratis, Mahars, Kolis, Saraswats, Lohanas, and Gaurs exhibiting high prevalence [ 16 , 17 ]. Although the Government of India had included the care and management of patients with thalassemia syndrome, the existing resources and infrastructure remain insufficient [ 2 , 15 , 16 , 18 ]. Methods for differential diagnosis between BTT and Iron Deficiency Anemia (IDA) include quantitative detection of Hemoglobin A2 (HbA2) by High-Performance Liquid Chromatography (HPLC) and DNA studies [ 18 , 19 ].…”

Section: Introductionmentioning

confidence: 99%

“…Although the Government of India had included the care and management of patients with thalassemia syndrome, the existing resources and infrastructure remain insufficient [ 2 , 15 , 16 , 18 ]. Methods for differential diagnosis between BTT and Iron Deficiency Anemia (IDA) include quantitative detection of Hemoglobin A2 (HbA2) by High-Performance Liquid Chromatography (HPLC) and DNA studies [ 18 , 19 ]. However, HPLC and DNA tests are expensive, and tests for a large population at risk can make a substantial healthcare burden.…”

Section: Introductionmentioning

confidence: 99%

Multi-criteria decision making to validate performance of RBC-based formulae to screen $$\beta$$-thalassemia trait in heterogeneous haemoglobinopathies

Jain,

Sharma,

Saleh

et al. 2024

BMC Med Inform Decis Mak

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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$$_{BTT}$$ BTT 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$$_{BTT}$$ BTT were the best-performing formulae. Further, a modification of the SCS$$_{BTT}$$ BTT 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$$_{BTT}$$ BTT along with the condition MCV$$\le$$ ≤ 80 fl was recommended for a higher heterogeneous population set. It was found that SCS$$_{BTT}$$ BTT can classify all BTT samples with 100% sensitivity when MCV$$\le$$ ≤ 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$$_{BTT}$$ BTT and its web application SUSOKA can provide 100% sensitivity when MCV$$\le$$ ≤ 80 fl.

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A decision support scheme for beta thalassemia and HbE carrier screening

Cited by 12 publications

References 56 publications

Prevalence of β-haemoglobinopathies in Eastern India and development of a novel formula for carrier detection

Prevalence of β-haemoglobinopathies in Eastern India and development of a novel formula for carrier detection

Deep Learning Assisted Automated Assessment of Thalassaemia from Haemoglobin Electrophoresis Images

Multi-criteria decision making to validate performance of RBC-based formulae to screen $$\beta$$-thalassemia trait in heterogeneous haemoglobinopathies

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