Updated risk stratification model for smoldering multiple myeloma (SMM) incorporating the revised IMWG diagnostic criteria.

8000 Background: The diagnostic criteria for MM were revised in 2014, recategorizing ultra-high risk (i.e., 80% at two years) as active myeloma requiring therapy. The removal of patients at the highest risk of progression from the smoldering group requires reassessment of current risk stratification models. Methods: We designed a multicenter, retrospective study of SMM patients to develop a risk stratification model. Patients diagnosed with SMM on/after January 1, 2004 were included if they had no disease progression within 6 months, had baseline data from diagnosis (+/- 3 months), had a follow up of ≥1 year, and did not participate in a therapeutic trial of SMM. Various clinical and laboratory factors were explored to identify factors that predicted progression at 2 years. Univariate Cox regressions were run for each factor. For factors with p-values ≤ 0.25, optimal cut points were identified using Youden’s index. Binary factors were used in stepwise regression to fit multivariable Cox model and significant risk factors were determined (F-test). Results: Overall, 2004 patients were included (ages 26-93, 51% female). Factors independently associated with progression (optimal cutoffs) included: Serum M protein (2 g/dL), involved to uninvolved serum-free light chain ratio (20), and marrow plasma cell % (20%). Patients were stratified using the risk factors: Low- (0 factors), Intermediate- (1), and High-Risk (≥2). Previously used high risk markers such as Bence Jones proteinuria (≥500 mg/24 hours) and severe immunoparesis (50% decrease in uninvolved immunoglobulin levels) were both significant in univariate analysis, but were eliminated on step wise selection. Compared to the low risk group, intermediate- and high-risk groups had significantly higher rate of progression (Table). Within the high-risk group, having all 3 risk factors (n=61) versus 2 did not add to the model, with insufficient separation between 2 and 3 factors. Conclusions: We have developed a risk stratification model for SMM that incorporates revised cutoffs for previously used parameters (20/2/20) that can be universally applied. Additonal analysis are being conducted to develop models that utilize common cytogenetic abnormalities, as well as those without FLC given lack of availability of all tests across the world. [Table: see text]