OA-37: Optimization of the 20/2/20 risk stratification model for patients with smoldering multiple myeloma through integration of the evolving patterns of monoclonal protein and serum free light chains

Introduction: The 20/2/20 model represents the prevailing standard of risk stratification for patients with smoldering multiple myeloma (SMM). This study aims at optimization of the 20/2/20 model by integrating evolving patterns of serum M-protein and involved serum free light chains (sFLC) as risk factors to more accurately identify patients at high risk who benefit from intensified monitoring or early therapeutic interventions.

Methods: In this study we retrospectively included 339 patients diagnosed with SMM between 2010 and 2022, who met the 2014 IMWG diagnostic criteria (Rajkumar SV et al., Lancet Oncol., 2014). Through cutoff analyses, we defined evolving patterns of serum M-protein and involved sFLC. We then compared the performance of the Mayo2018 (BMPC >20%, M-protein > 2g/dl, FLCr >20; 0 points = low risk, 1 point = intermediate risk, ≥2 points = high risk; Lakshman A et al., BCJ, 2018), IMWG2020 (as Mayo2018 plus cytogenetic abnormalities (t(4;14), t(14;16), +1q21 and/or del13q); 0 points = low risk, 1 point = low intermediate risk, 2 points = intermediate risk, ≥3 points = high risk; Mateos MV et al., BCJ, 2020) and gradual IMWG2020 (gradual scoring system for M-protein, BMPC, FLCr and cytogenetic abnormalities; Mateos MV et al., BCJ, 2020) models enhanced by the dynamic risk factor “evolving M-protein and/or evolving sFLC” at one year from diagnosis to the respective standard models, using the c-index.

Results: Based on optimal cut-point search and clinical applicability we defined the independent risk factors evolving M-protein as a >10% and >0,2g/dl increase in M-protein (49/222 patients (22%), HR=5.02, 95% CI [2.86;8.81], p< 0.001) and evolving sFLC as a >25% and >50mg/l increase in involved sFLC (14/178 patients (8%), HR=3.66, 95% CI [1.60;8.38], p< 0.002) within one year from diagnosis. 58/179 patients (32%) had an evolving M-protein and/or evolving sFLC phenotype resulting in an increased risk of progression (HR=6.41, 95% CI [3.19;12.86], p< 0,001). At one year, 10 of 78 patients migrated from low to intermediate risk and 19 of 56 patients from intermediate to high risk in the Mayo2018 model when adding the evolving phenotype. At one year the combined risk factor „evolving M-protein and/or evolving sFLC” improved discrimination of the risk groups when added to the Mayo2018 model (c-statistics for static model: 0.750 vs. dynamic model: 0.783, p=0.165). Similarly, the IMWG2020 (static: 0.745 vs. dynamic: 0.805, p=0.014) and gradual IMWG2020 (static: 0.753 vs. dynamic: 0.828, p=0.005) models improved prognostication when expanded by dynamic M-protein/sFLC.

Conclusions: Through integration of the dynamic risk factor “evolving M-protein and/or evolving sFLC” in the current risk stratification models of SMM, a crucial aspect of individual disease dynamics is taken into account. Our results show that the dynamic M-protein/sFLC models are superior to standard models. Independent validation of the analyses is in preparation.