PMID- 38167309 OWN - NLM STAT- MEDLINE DCOM- 20240105 LR - 20240116 IS - 1472-6947 (Electronic) IS - 1472-6947 (Linking) VI - 24 IP - 1 DP - 2024 Jan 2 TI - Multi-criteria decision making to validate performance of RBC-based formulae to screen [Formula: see text]-thalassemia trait in heterogeneous haemoglobinopathies. PG - 5 LID - 10.1186/s12911-023-02388-w [doi] LID - 5 AB - 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. CI - (c) 2023. The Author(s). FAU - Jain, Atul Kumar AU - Jain AK AD - Department of Hematology, Postgraduate Institute of Medical Education and Research, Chandigarh, 160012, India. FAU - Sharma, Prashant AU - Sharma P AD - Department of Hematology, Postgraduate Institute of Medical Education and Research, Chandigarh, 160012, India. FAU - Saleh, Sarkaft AU - Saleh S AD - Department of Materials and Production, Aalborg University, 9220, Aalborg, Denmark. FAU - Dolai, Tuphan Kanti AU - Dolai TK AD - Department of Hematology, Nil Ratan Sircar Medical College and Hospital, Kolkata, 700014, West Bengal, India. FAU - Saha, Subhas Chandra AU - Saha SC AD - Department of Obstetrics and Gynecology, PGIMER, Chandigarh, India. FAU - Bagga, Rashmi AU - Bagga R AD - Department of Obstetrics and Gynecology, PGIMER, Chandigarh, India. FAU - Khadwal, Alka Rani AU - Khadwal AR AD - Department of Clinical Hematology and Medical Oncology, PGIMER, Chandigarh, India. FAU - Trehan, Amita AU - Trehan A AD - Pediatric Hematology/Oncology Unit, Department of Pediatric Medicine, Advanced Pediatric Centre, PGIMER, Chandigarh, India. FAU - Nielsen, Izabela AU - Nielsen I AD - Department of Materials and Production, Aalborg University, 9220, Aalborg, Denmark. FAU - Kaviraj, Anilava AU - Kaviraj A AD - Department of Zoology, University of Kalyani, Kalyani, 741235, India. FAU - Das, Reena AU - Das R AD - Department of Hematology, Postgraduate Institute of Medical Education and Research, Chandigarh, 160012, India. FAU - Saha, Subrata AU - Saha S AD - Department of Materials and Production, Aalborg University, 9220, Aalborg, Denmark. saha@m-tech.aau.dk. AD - Department of Mathematics, University of Engineering & Management, Action Area III, B/5, Newtown, Kolkata , 700160, India. saha@m-tech.aau.dk. LA - eng PT - Journal Article DEP - 20240102 PL - England TA - BMC Med Inform Decis Mak JT - BMC medical informatics and decision making JID - 101088682 SB - IM MH - Child MH - Humans MH - *beta-Thalassemia/diagnosis MH - Mass Screening MH - Predictive Value of Tests MH - Diagnosis, Differential MH - Decision Making PMC - PMC10759673 OTO - NOTNLM OT - -Thalassemia carrier screening OT - Multi-criteria decision making OT - RBC indices COIS- The authors declare no competing interests. EDAT- 2024/01/04 01:18 MHDA- 2024/01/05 06:42 PMCR- 2024/01/02 CRDT- 2024/01/03 09:43 PHST- 2023/05/06 00:00 [received] PHST- 2023/12/04 00:00 [accepted] PHST- 2024/01/05 06:42 [medline] PHST- 2024/01/04 01:18 [pubmed] PHST- 2024/01/03 09:43 [entrez] PHST- 2024/01/02 00:00 [pmc-release] AID - 10.1186/s12911-023-02388-w [pii] AID - 2388 [pii] AID - 10.1186/s12911-023-02388-w [doi] PST - epublish SO - BMC Med Inform Decis Mak. 2024 Jan 2;24(1):5. doi: 10.1186/s12911-023-02388-w.