Carson, Robin

Abstract Introduction : Current standard of care for smoldering multiple myeloma (SMM), an asymptomatic precursor of multiple myeloma (MM), is observation until progression to active MM. Increasing evidence suggests that patients (pts) with SMM at high risk for progression to active MM may benefit from early treatment (tx). In AQUILA, a phase 3 study in pts with high-risk SMM (NCT03301220), daratumumab (Dara) monotherapy significantly reduced risk of progression to active MM or death with a trend of extending overall survival (OS) vs active monitoring (ActMon), with no new safety concerns. Given the evolution in SMM risk stratification, a post hoc analysis was performed to assess outcomes using the IMWG 2020 and IMWG 2020 plus cytogenetic risk models to assess which AQUILA pts benefited most from Dara monotherapy. Safety and efficacy analysis by age and stem cell collection outcomes were also assessed. Methods: Eligible pts with a confirmed diagnosis (≤5 y) of high-risk SMM per IMWG 2014 criteria, defined as clonal bone marrow plasma cells (BMPC) ≥10% and ≥1 risk factor (IgA SMM, serum protein ≥30 g/dL, serum involved:uninvolved free light chain [I/U FLC] ratio ≥8 and <100, immunoparesis with reduction of 2 uninvolved Ig isotypes, and/or clonal BMPC >50% to <60%) at study entry, were randomized 1:1 to receive subcutaneous Dara or ActMon for 39 cycles, 36 months, or until confirmed disease progression (PD), whichever came first. Primary endpoint was progression-free survival (PFS) assessed by independent review committee, defined as progression to active MM (based on IMWG SLiM-CRAB diagnostic criteria) or death. Secondary endpoints included time to first-line (1L) MM tx and OS. For this post hoc analysis, we assessed outcomes by age, IMWG 2020 high-risk SMM criteria (BMPC >20%, monoclonal spike >2 g/dL, serum FLC ratio >20; ≥2 factors=high risk; also known as the Mayo 2018 or the 20-2-20 criteria), and the IMWG 2020 plus cytogenetic criteria (IMWG 2020 criteria + presence of ≥1 high-risk cytogenetic abnormalities [t(4;14), t(14;16), +1q and/or del13q]; ≥3 factors=high risk). Results : Dara tx showed a PFS benefit across all IMWG 2020 risk subgroups (low: hazard ratio [HR], 0.59; intermediate: HR, 0.70), with the largest benefit in the high-risk subgroup, where the PD/death rate in the ActMon arm was ~1.6-fold that in the Dara arm (62.8% vs 37.5%; HR, 0.36). This benefit of Dara vs ActMon was preserved over time, with 5-year PFS rates of 78.2% vs 71.6%, 56.2% vs 42.9%, and 60.4% vs 23.6% in IMWG 2020 low-, intermediate-, and high-risk groups, respectively. There was a positive trend favoring Dara for time to 1L MM treatment across all IMWG 2020 risk groups (low-risk HR, 0.63; 95% CI, 0.22–1.80; intermediate-risk HR, 0.57; 95% CI, 0.35–0.92; high-risk HR, 0.39; 95% CI, 0.25–0.62). IMWG 2020 plus cytogenetic risk classification results will be available at the time of presentation. When comparing the younger (<65y HR, 0.51; 95% CI, 0.32–0.79) vs the older (≥65y, HR, 0.50; 95% CI, 0.32–0.77) pt population, a PFS benefit was observed regardless of age. Similarity was also observed in TEAE incidence rate when looking into <65, 65 to <75, and ≥75 y subgroups (82.7%, 81.1%, and 87.5% with ActMon; 96.2%, 98.5%, and 95.2% with Dara); however, serious TEAEs were more frequently observed in older ActMon pts (12.2%, 18.9%, and 50.0% with ActMon; 24.8%, 35.8%, and 28.6% with Dara). Across all pts treated/monitored in AQUILA, 23 (11.9%) and 41 (20.9%) pts in the Dara and ActMon arms, respectively, received autologous stem cell transplant as part of their first tx after progressing to active MM, with very limited plerixafor use (Dara, 3 [1.6%] vs ActMon, 9 [4.6%]). Median (range) CD34+ cell yield was 5.0 (2–20)×106 cells/kg body weight among 22 pts in the Dara arm and 5.1 (2–21)×106 cells/kg body weight among 39 pts in the ActMon arm. Conclusions : In this analysis, pts with high-risk SMM from the phase 3 AQUILA study treated with Dara monotherapy experienced long-term PFS benefit across IMWG 2020 subgroups, with the most pronounced benefit in the high-risk subgroup. No notable differences in PFS or safety were observed across age subgroups. Early Dara tx for high-risk SMM did not have a detrimental impact on stem cell yield. Although mature OS analyses are forthcoming, overall, these results further support early intervention with Dara monotherapy vs ActMon among pts with high-risk SMM, regardless of risk stratification criteria used.

Introduction: Progression-free survival (PFS), a common endpoint used in multiple myeloma (MM) trials, is defined as the time to the earliest occurrence of disease progression or death. Disease progression in MM is determined by the International Myeloma Working Group (IMWG) Uniform Response Criteria based on imaging and biomarkers from blood, urine, and bone marrow biopsy testing. In clinical trials, IMWG-recommended assessments are protocol-based. However, in routine care, they are often performed and recorded differently based on a multitude of factors. Algorithms to ascertain progression events using routinely collected biomarker data are important to classify disease progression and align with trial-defined endpoints. The aim of this study was to construct and evaluate an optimized real-world Progression (rwP) algorithm using real-world data (RWD) and demonstrate how biomarker data are captured and used to derive endpoints in routine practice. Method: A cohort of 270 transplant ineligible newly diagnosed MM (NDMM) patients starting on lenalidomide and dexamethasone (Rd) and meeting select MAIA (NCT02252172) trial eligibility criteria were included from the nationwide Flatiron Health electronic health record-derived deidentified database from 2015 to 2023. A rwP algorithm was developed using key IMWG-recommended biomarkers, including serum protein electrophoresis (SPEP), urine protein electrophoresis (UPEP), and serum free light chains (FLCs). The initial baseline value for each biomarker was identified, if available, during either the pre-treatment period (45 days prior through 7 days after first line treatment (1L) start) or the on-treatment period (8 days after 1L start through 1L end). Available biomarkers were followed for disease assessment. If any subsequent lab value during 1L treatment was less than the initial baseline value, the subsequent “on-treatment baseline” value was adopted as the new lowest value; otherwise, the initial value was used as the “on-treatment baseline” value for assessing progression events. Three hierarchies, which describe the order of utilizing key IMWG-recommended biomarkers to define rwP events, were explored, including: i) strict hierarchy (SH) [SPEP > UPEP > FLCs], ii) partial hierarchy (PH) [SPEP = UPEP > FLCs], and iii) no hierarchy (NH) [SPEP = UPEP = FLCs]. The PH option closely resembles the IMWG criteria, with FLCs only used for rwP assessments when no measurable SPEP/UPEP are identified. The NH approach considers all available biomarkers equally and resembles how they are utilized in real-world clinical practice. The feasibility of requiring confirmatory events following the first suggestion of progression was also explored. Assays following the progression event up to the end of 1L were considered as confirmatory progression events if they met IMWG criteria. Results: We applied the rwP algorithm with each hierarchy to all eligible NDMM patients (N = 270). The SH, PH, and NH approaches respectively identified 106 (39.3%), 106 (39.3%), and 123 (45.6%) patients with progression events. Results from the SH and PH approach are consistent likely due to the rarity of UPEP usage in clinical practice. The NH approach captured more progression events because FLCs are used in the presence of measurable SPEP or UPEP, resulting in 73 progression events captured by FLCs in comparison to 32 from other approaches, potentially increasing false-positive capture due to the volatility of FLC results. Among the 106 PH-identified patients who progressed, 84 (79.2%) had IMWG-recommended tests following their progression event, and 74 (69.8%) had their progression confirmed before the end of 1L, with 35 (33.0%) receiving their confirmatory reading within 2 months after progression. These results suggest that requiring confirmatory testing as part of the rwP is feasible, though it may introduce false negatives for patients receiving clinical progression confirmation instead of getting confirmatory labs in routine clinical practice. Conclusion: We present a comprehensive assessment of important design choices for an rwP algorithm for NDMM, including a hierarchy of key assays and the inclusion of confirmatory testing. Further validation of the algorithm with health care provider assessments and the inclusion of bone marrow biopsy and imaging data is important for evaluating the performance of the algorithm in RWD.