The REMA Score Revisited: An Optimized Algorithm for Early Prediction of Clonal Mast Cell Disease

BACKGROUND: The Spanish Network on Mastocytosis (REMA) score was developed to predict clonal mast cell (MC) activation disorders (MCAD) in patients presenting with anaphylaxis without mastocytosis in the skin (MIS) and guide selection of patients for bone marrow (BM) examination. This study reassessed the diagnostic accuracy of the REMA score after 15 years of use and proposes refinements to optimize its predictive value. METHODS: Overall, 1204 patients with severe MC mediator-related symptoms without MIS referred to the REMA were retrospectively analyzed. All underwent clinical and allergologic evaluation, serum tryptase, BM histology, immunophenotyping, and KIT mutational analysis. REMA scores were calculated and diagnostic accuracy assessed across the score ranges. Multivariable analysis was applied to identify independent predictors and refine prediction. RESULTS: Clonal MCAD was diagnosed in 64% of patients who underwent a BM study. Overall, the REMA score showed excellent sensitivity (87%-90%) but limited specificity (34%-35%), with the poorest accuracy in the score 0-2 range. In this subgroup, independent predictors were elevated tryptase without hereditary alpha tryptasemia (OR 5.42, 95% CI 2.86-10.28) and insect venom as trigger (OR 2.18, 95% CI 1.28-3.72). KIT p.D816V in blood, although detected in only 29% of all clonal MCAD cases, allowed identification of additional low-score patients requiring BM evaluation. A refined algorithm combining these predictors improved specificity to 57% while maintaining sensitivity at 86%. CONCLUSIONS: The REMA score remains highly sensitive for early detection of clonal MCAD presenting without MIS. Incorporation of additional clinical and molecular predictors into an updated diagnostic algorithm enhances specificity and ensures more accurate selection of patients with a REMA score of 0-2 for subsequent BM evaluation.