An algorithm to predict intrathecal IgM synthesis in multiple sclerosis patients: optimizing the use of oligoclonal band testing

Abstract Objectives We aimed to develop a simple, cost-effective algorithm to predict the presence of oligoclonal IgM bands (OCMB) in patients with multiple sclerosis (MS), using surrogate markers such as the IgM Index (IgMi) and the Free Kappa Light Chains Index (FKLCi), with the aim of reducing the need for OCMB testing while maintaining high diagnostic accuracy. Methods A retrospective study was conducted using paired serum and cerebrospinal fluid samples from patients diagnosed with MS at disease onset at Hospital Universitari i Politècnic La Fe. Receiver operating characteristic (ROC) curve analyses were performed for IgMi and FKLCi to evaluate their ability to predict OCMB positivity. Several combinations of cutoff values prioritizing high specificity and positive predictive value (PPV) were tested, and the best-performing threshold combination was selected. Results A total of 97 patients were included. The optimal model defined OCMB positivity as having either IgMi≥0.2 or FKLCi≥250. Applying this algorithm reduced the need for OCMB testing by 33 %, while achieving a specificity of 90 % and a PPV of 85 %. Conclusions IgMi and FKLCi may serve as reliable predictors of OCMB positivity in MS, potentially reducing unnecessary testing and laboratory workload.