Multinational cohort study of dynamic risk stratification of smoldering multiple myeloma

Accurate prediction of risk of progression from smoldering multiple myeloma (SMM) to active multiple myeloma (MM) is needed for individualizing early therapeutic strategies with mimimum risk of overtreatment. Current risk stratification models do not account for evolving biomarker trajectories. Researchers at seven multinational centers assembled a cohort of 2,344 SMM patients with longitudinal clinical and biological data to train and validate the Precursor Asymptomatic Neoplasms by Group Effort Analysis (PANGEA)-SMM risk models. Four evolving biomarkers were significantly associated with shorter time to progression: M-protein increase ≥ 0.2 g/dl, involved/uninvolved serum free light chain ratio increase ≥ 20, creatinine increase ≥ 25%, and hemoglobin decrease ≥ 1,5 g/dl. PANGEA-SMM outperforms established models, including the 20/2/20 and IMWG models, by more accurately predicting progression (C-statistic 0.79), even without biomarker history (C-statistic 0.78) or recent bone marrow biopsy (C-statistic 0.78). The authors conclude that PANGEA-SMM is an easy-to-use, open-access tool for risk stratification in SMM.