Using Current Clinical Markers to Define High Risk Smoldering Multiple Myeloma: Agree to Disagree
Authors: Hill Elizabeth , Korde Neha , Mailankody Sham , Morrison Candis , Dew Alexander , Hsu Albert Jennifer , Graap Katherine , Maura Francesco , Landgren Ola , Kazandjian Dickran 
Published: November 2019

Introduction
Defining high risk (HR) smoldering multiple myeloma (SMM) is becoming increasingly important as multiple clinical trials are actively investigating the role of early treatment. On average, patients with SMM progress to multiple myeloma (MM) at a rate of 10% per year for the first 5 years (Kyle 2007). Several classification systems have been developed to identify patients with a higher rate of progression, including two commonly used models: the 2008 Mayo Clinic model and the PETHEMA (Programa de Estudio y Tratamiento de las Hemopatias Malignas) model. The 2008 Mayo Clinic model incorporates M-protein (>3 g/dL), bone marrow plasma cell percentage (BMPC%) >10%, and a ratio of involved to uninvolved serum free light chains (sFLCr) >8. Patients with all three characteristics had a 76% risk of progression to MM in 5 years (Dispenzieri 2008). The PETHEMA model uses the proportion of BMPCs with aberrant plasma cell phenotype on flow cytometry (>95%) and reduction in uninvolved immunoglobulins (immunoparesis) to identify HR patients. Patients with both risk factors had a 5-year rate of progression to MM of 72% (Perez-Persona 2007). The 2008 Mayo Clinic model was validated prior to the International Myeloma Working Group reclassification of MM in 2014. Therefore, in 2018, Mayo Clinic proposed a new model to define HR SMM referred to as "2/20/20": M-protein >2 g/dL, BMPC% >20%, and sFLCr >20 (Lakshman 2018). The median time to progression for the HR group (2-3 risk factors) was 29 months, compared to 110 months in the low risk (LR) group (0 risk factors). Previously, a high discordance rate among the 2008 Mayo model and the PETHEMA model was reported (Cherry 2013). In this study, we aim to define the concordance among patients defined as HR SMM by the aforementioned models in an independent sequential patient cohort.
Methods
The medical records of patients sequentially assigned a diagnosis of SMM by the myeloma program at the NIH Clinical Center between April 2010 to July 2019 were reviewed. Patients with myeloma defining events were excluded (i.e. MM). Each patient was assigned a risk score based on the 2008 Mayo Clinic model, the 2018 Mayo Clinic model, and the PETHEMA model. The distribution of patients in the LR, intermediate (IR), and HR groups were compared between the models. Concordance ratios were calculated between the three models.
Results
A total of 236 patient records were reviewed and per the 2014 IMWG criteria, 138 patients were identified as having SMM. Two patients did not have bone marrow flow cytometry samples and thus could not be classified by the PETHEMA model. Therefore, 136 patients were stratified by risk based on all three models (Table 1,2). The rate of concordance between the 2008 Mayo Model and the PETHEMA model was 31.6% (95% CI: 24.4-39.8%), similar to previously published results. The concordance between the 2018 Mayo Model and the PETHEMA model was slightly higher at 44.8% (95% CI: 36.7-53.2%; P=0.0337). There was significant discordance between the models in classifying patients as HR versus non-HR (Table 3). However, the 2018 Mayo Clinic model had a higher concordance with the PETHEMA model (27.2%; 95% CI: 20.4-35.3%) than the 2008 Mayo Clinic model (4.4%; 95% CI:1.8-9.5%).
Conclusions
The accurate identification of SMM patients at highest risk of developing MM remains elusive and no one model has been found to be superior than the other. As this study indicates, a significant number of patients may be classified as "HR" according to the PETHEMA model while simultaneously be defined as "LR" based on the Mayo Clinic models. While the 2018 Mayo Clinic model has a higher concordance rate to the PETHEMA model, it remains significantly discordant. These results indicate that the current clinical variables used to determine risk are not reliable. This is likely due to the fact that they are markers of disease burden rather than biology and risk is subject to increase over time (Landgren 2019). It is time for genomic signatures which signify varying biology to be incorporated into risk models. The treatment of HR SMM is currently being investigated in multiple clinical trials. As the results from these trials are published, the data will need to be scrutinized as to how patients were defined as "HR" in order to compare results. At this time, it remains unclear which patients warrant early intervention and it is imperative that patients with SMM be exclusively treated on clinical trials.

Disclosures
Mailankody: Juno: Research Funding; Celgene: Research Funding; Janssen: Research Funding; Takeda Oncology: Research Funding; CME activity by Physician Education Resource: Honoraria. Landgren:Merck: Other: IDMC; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding; Theradex: Other: IDMC; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding.