Utilizing Inhibitor Screening Assay Results to Predict Bethesda Titers in Patients With Hemophilia A: Cost‐Effective Strategy in Resource‐Constrained Setting
Abstract
ABSTRACT Background The classical or modified Nijmegen–Bethesda assay measures FVIII inhibitor titers and requires testing residual FVIII levels at multiple serial dilutions, making it prohibitively expensive in resource‐constrained settings. The study aimed to develop a cost‐effective strategy to predict inhibitor titers (Bethesda units [BU]) in patients with hemophilia A (HA) using the inhibitor screening assay. Methods Inhibitor screening and Bethesda assay were performed on samples of suspected HA with inhibitors. The laboratory data were analyzed to develop a model to predict inhibitor titers from inhibitor screening (normalized ratio of APTT values of the fresh mix [FM] or incubated mix [IM]). The model was then prospectively validated on new inhibitor‐positive samples. Results One hundred and four samples from 83 patients with HA and inhibitors were analyzed. A linear regression analysis was performed, and the normalized APTT ratio of FM ( R 2 = 0.815) proved to be highly predictive of inhibitor titers (BU) compared with IM ( R 2 = 0.536). A predictive model was developed based on the normalized APTT ratio of FM values. This predictive model was then validated on a new cohort of 27 inhibitor‐positive samples, where the predicted inhibitor titers strongly correlated with the observed titers ( R 2 = 0.843). Conclusion The FM of the screening assay serves as a potential indicator of the expected inhibitor titers (BU) and guides the selection of dilutions likely to yield near‐50% residual FVIII activity for estimating the Bethesda titers. This approach substantially reduces assay costs, particularly in cases with > 2 BU. Additional prospective studies are needed to validate these results.
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Authors: Dinesh Chandra, Manish Kumar Singh, Ruchi Gupta, Khaliqur Rahman, Prakhar Gupta, Anup Kumar, Jayanta Kumar Biswas, Sanjeev Yadav, Rajesh Kashyap
Institutions: Sanjay Gandhi Post Graduate Institute of Medical Sciences