Major Thalassemia, Screening or Treatment: An Economic Evaluation Study in Iran

Redesigning New Policy Options for Thalassemia Prevention in Sri Lanka

Sri Lanka, a country with 22 million people, has nearly 2000 thalassemia patients with severe thalassemia, two-thirds of whom have beta thalassemia major (TM). The current prevention program based on promoting “safe marriages”, which has been in existence for over 15 years, has failed to reduce thalassemia major births. We set about to examine the cost-effectiveness of novel policy options for thalassemia prevention in Sri Lanka. Methods: The current cost for treatment of a thalassemia major patient (USD 2602/yr) was compared against the cost per reduction of single birth with three novel strategies, namely intensifying the screening in the current five districts combined with an education program (policy option 1), a nationwide screening program (policy option 2), and antenatal screening combined with the termination of pregnancy (policy option 3). The incremental cost-effectiveness ratio (ICER) of the different strategies was calculated. Results: The status quo was considered to reduce one TM birth whilst the new policy options were able to reduce births by 14, 35, and 48, respectively. The costs incurred for the program for a year for status quo and the three novel programs were USD 104,788, 173,884, 781,372, and 904,186 respectively. Cost per prevention of a thalassemia major birth was USD 87,324, 12,420, 22,324, and 20,084, respectively. The lifetime cost per treatment of a thalassemia major patient was USD 34,653. Conclusions: Given the current legal restriction on termination of pregnancy for fetal indications, policy option 2, an island-wide screening with mass education, is the most cost-effective and will be expected to deliver a substantial reduction in new births.

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.