Type: Oral
Session: 653. Multiple Myeloma: Clinical and Epidemiological: Addressing Hematologic and Immune Toxicities and the Status of Quad Therapies
Hematology Disease Topics & Pathways:
Plasma Cell Disorders, Diseases, Treatment Considerations, Lymphoid Malignancies, Measurable Residual Disease
QUADs with an anti-CD38 mAb, an IMiD, a proteasome inhibitor and dexamethasone followed by autologous stem cell transplantation (ASCT) in the treatment of newly diagnosed multiple myeloma (NDMM) led to substantial improvements in depth of response, including minimal residual disease (MRD) negativity, and progression-free survival. The therapeutic success of QUAD + ASCT has reinvigorated an interest in fixed-duration therapy, yet optimal short term efficacy endpoint for treatment cessation is unknown. We used a large dataset of patients (pts) treated with QUAD + ASCT, monitored with serial MRD assessment and managed with MRD-adapted treatment duration to determine the best short term efficacy endpoint to identify pts at low risk of treatment failure.
Methods
We analyzed 221 pts with NDMM treated with QUAD + ASCT and monitored with serial marrow-based MRD by next-generation sequencing. Based on trial design (N=116) and institutional practice (N=105) most pts received post ASCT QUAD consolidation followed by treatment cessation if MRD<10-5 in two consecutive datapoints. Pts were monitored with MRD post induction, ASCT and consolidation, and at least yearly thereafter. We utilized Cox regression to build parallel models of predictors of disease progression or MRD resurgence utilizing the same patient and disease features and one distinct short term efficacy endpoint per model, inputted as time-varying covariate. Efficacy endpoints tested were IMWG-defined stringent complete response (sCR), MRD<10-5 (single datapoint), MRD<10-6, sustained MRD (S-MRD, two consecutive assessments at least 1 year apart) <10-5and S-MRD<10-6. Best fitting models were determined using Akaike’s information criterion (AIC, lower value indicates better fitting model), an information theory approach, and Heagerty & Zheng C index.
Results
Median age of the 221 pts. was 61 years (IQR 55-68), 21% age 70 or older, 37% had MM with 1 high risk chromosome abnormality [HRCA, gain/amp 1q, t(4;14), t(14:16), del(17p)], 16% had 2+HRCA, 30% were non-White and 58% male. We followed pts for a median of 40.6 mo. and performed 979 MRD assessments. One hundred and eighty-three pts (83%) achieved sCR, 170(77%) MRD<10-5, 146 (66%) MRD<10-6 , 110 (50%) S-MRD<10-5 and 90 (41%) S-MRD<10-6. Average time to achieve the endpoint was 7.8 mo for sCR, 7.1 mo. for MRD <10-5, 9.4 mo. for MRD<10-6, 19.3 mo. for S-MRD<10-5 and 20.5 mo. for S-MRD<10-6. We first tested models to predict PFS among all 221 pts. Predictive models included same covariates (ISS, high LDH and number of HRCA) other than the efficacy endpoint. The best fitting model (AIC 417.2, C-stat 0.757) was based on S-MRD<10-5 (HR=0.23, 95% C.I. 0.11-0.47) and included presence of 1 HRCA (HR=2.93, 95% C.I. 1.31-6.52), 2+ HRCA (HR=7.60, 95% C.I. 3.31-17.43), high LDH (HR=1.64, 95% C.I. 0.81-3.33), ISS2 (HR 1.31, 95% C.I. 0.62-2.77) and ISS3 (HR 1.96, 95% C.I. 0.90-4.28). The model with S-MRD<10-6 had similar, but not better performance (AIC 419.4, C-stats 0.752). We subsequently analyzed the 121 (55%) pts who reached MRD-guided treatment cessation for the best fitting model to predict progression or MRD resurgence in absence of continuous therapy. Among these pts, 117(97%) achieved sCR, all (by definition) MRD<10-5, 116 (96%) MRD<10-6 , 95 (79%) S-MRD<10-5 and 81 (67%) S-MRD<10-6. The best fitting model (AIC 197.2, C-stat 0.766) was based on S-MRD<10-5 (HR 0.01, 95% C.I. 0.002-0.05) and included presence of 1 HRCA (HR=1.41, 95% C.I. 0.49-4.07), 2+ HRCA (HR=5.43, 95% C.I. 1.75-16.84), high LDH (HR=3.19, 95% C.I. 0.98-10.40), ISS2 (HR 1.25, 95% C.I. 0.53-2.96) and ISS3 (HR 0.73, 95% C.I. 0.23-2.37). The model with S-MRD<10-6 did not perform better (AIC 232.4, C-stat 0.727). Among the 94 pts who achieved S-MRD<10-5 and were monitored off therapy, the risk of MRD resurgence or progression 2.5 years after cessation of therapy was 6.1%, 15.0% and 22.2% and risk of progression was 3.0 %, 12.0% and 11.1% for patients with 0, 1 and 2+ HRCA, respectively
Conclusion
In the setting of QUAD therapy + ASCT, no short term conventional or MRD-based efficacy parameter negates the cumulative impact of HRCA on prognosis. S-MRD<10-5 is the best predictor of PFS and yields the best predictive models for risk of MRD resurgence or progression in the setting of fixed duration therapy. This analysis validates S-MRD<10-5 as efficacy parameter for treatment cessation in trials exploring fixed duration therapy in NDMM.
Disclosures: Giri: CareVive: Honoraria, Research Funding; PackHealth: Research Funding; Sanofi: Honoraria, Research Funding; Janssen: Honoraria, Research Funding. Dhakal: C4 therapeutics: Research Funding; Carsgen: Research Funding; Sanofi: Research Funding; Genentech: Consultancy, Honoraria; Medical College of Wisconsin: Current Employment; Karyopharm: Honoraria, Speakers Bureau; Janssen: Honoraria, Research Funding, Speakers Bureau; Acrellx: Research Funding; Pfizer: Consultancy, Honoraria, Speakers Bureau; Bristol Myers Squibb: Honoraria, Research Funding. Bal: Adaptive Biotechnologies: Consultancy; Bristol Myers Squibb: Consultancy, Research Funding; Janssen: Consultancy; AstraZeneca: Consultancy; MJH LifeSciences: Consultancy; Amyloid Foundation: Research Funding; BeiGene: Consultancy; Fate Therapeutics: Consultancy; AbbVie: Consultancy, Research Funding. Ravi: Guidepoint: Consultancy. Chhabra: Bristol Myers Squibb, Amgen, Janssen, Novartis, Syndax, Ionis, Sanofi, and GlaxoSmithKline: Research Funding; GlaxoSmithKline, Sanofi: Honoraria; Omeros: Speakers Bureau. Silbermann: Sanofi: Consultancy, Research Funding; Janssen Oncology: Research Funding; Pfizer: Consultancy; Oncopeptides: Consultancy. Costa: Sanofi: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding; Abbvie: Consultancy, Honoraria, Research Funding; Adaptive biotechnoligies: Honoraria; BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Pfizer: Consultancy, Honoraria; Caribou: Research Funding; Genentech, Inc.: Consultancy, Honoraria, Research Funding.