Plasma Cell precursor and Other Disorders
Category: Plasma Cell precursor and Other Disorders
COMPARING SMOULDERING MYELOMA HIGH-RISK AND EVOLVING PHENOTYPE DEFINITIONS IN THE PROSPECTIVE, NATIONWIDE UK COSMOS STUDY
Daniel P. Hughes, MBBS
Clinical research training fellow
UCL Cancer Institute
SMM carries variable risk of progression to MM. Several models aim to identify high-risk (HR) patients. An evolving phenotype (EP) by various criteria also increases risk. As early intervention may benefit HR-SMM, accurate identification is critical. In the prospective UK COSMOS cohort, we compared reported HR/EP criteria, and evaluated whether EP adds risk within HR.
Methods:
SMM patients were risk-stratified at entry using Mayo-2007, -2008, -2018, Rajkumar, Czech Myeloma Group (CMG), IMWG [20-2-20+CGN], IMWGp [points-based]. Other models were not included in our analysis due to unavailable data or personalised prediction rather than group-stratification. Patients were assessed for EP using Rosiñol, Fernàndez De Larrea (FDL), Ravi, Werly, and Visram criteria. To assess identification of higher risk patients, for all models HR was compared to combined lower risk groups. For 4-tier models, with intermediate-risk (IR) progression ~50% in 2y, HR and IR were combined (“+IR”) in additional analysis and compared with lower risk groups. Cox regression and Harrell’s C-statistic were used to assess the different models. %Evaluable %HR or EP Hazard ratio p C-statistic HR or EP median PFS (m) HR model (CS n=106, mFU 28.1m) Mayo-2007 62 16.0 2.43 0.056 0.545 37.0 Mayo-2008 60 10.4 3.47 0.016 0.567 26.5 Mayo-2018 59 28.3 4.65 < 0.001 0.697* NR CMG 71 8.5 3.80 0.018 0.579* 16.4 CMG+IR 71 39.6 7.17 (2.41-21.33) < 0.001 0.691* 36.4 IMWG 36 17.0 4.52 < 0.001 0.652* 20.0 IMWG+IR 36 43.4 2.88 0.023 0.651* NR IMWGp+IR 34 14.2 1.51 0.459 0.543 NR EP criteria (CS n=113, mFU = 32.7m) Rosiñol 80 12.4 1.19 0.823 0.545 NR Ravi 52 48.7 2.27 0.181 0.614 NR Werly 58 28.3 2.34 0.014 0.731* NR Visram 57 18.6 2.26 0.182 0.570 NR *p< 0.05
Results: A total of 320 SMM patients were included. In the HR common evaluable set (CS, n=106), 58 were HR by ≥1 model, only 4 by all, and 14 by one. Best discrimination was seen with Mayo-2018. In the EP CS (n=113), 74 had EP by ≥1 criterion, only 2 by all, and 42 by one (26 of these by Ravi criteria). Best discrimination was seen with Werly. Concordance was modest overall. The Rajkumar (93.2% HR), IMWGp (0.9% HR) and FDL (2.7% EP) models were excluded due to skewed classifications. Combined analysis using Mayo-2018 and Werly showed EP across all risk groups. Among HR patients the 33% with EP had higher progression risk (HR 13.96, p=0.017, C-index 0.806) and shorter median PFS vs HR alone (8m vs NR from EP assignment, p=0.005).
(n=320)
(95%CI)
(0.98-6.05)
(1.26-9.51)
(1.94-11.14)
(1.26-11.42)
(1.85-11.05)
(1.16-7.15)
(0.51-4.50)
(0.26-5.48)
(0.68-7.55)
(1.34-13.35)
(0.68-7.52)
Conclusions:
We validated and compared risk models and EP criteria in SMM in our prospective, nationwide cohort and found that HR and EP classification and model performance varied. Discrimination was best for Mayo-2018 HR and Werly EP. Moreover, EP adds significant risk in HR patients warranting close monitoring. Our results indicate that standardized HR definitions are needed for clinical trial design.