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4742 Expanded Meta-Analyses Confirms the Association between MRD and Long-Term Survival Outcomes in Multiple Myeloma (MM)

Program: Oral and Poster Abstracts
Session: 902. Health Services Research—Malignant Conditions (Lymphoid Disease): Poster III
Hematology Disease Topics & Pathways:
Adult, multiple myeloma, Diseases, antibodies, Biological, Therapies, Plasma Cell Disorders, Study Population, Lymphoid Malignancies
Monday, December 9, 2019, 6:00 PM-8:00 PM
Hall B, Level 2 (Orange County Convention Center)

Nikhil C Munshi, MD1,2, Herve Avet-Loiseau, MD, PhD3, Kenneth C. Anderson, MD1, Paola Neri, MD, PhD4, Bruno Paiva, PhD5*, Mehmet Samur, PhD1, Meletios A. Dimopoulos, MD6, Margarita Kulakova7*, Bart Heeg, PhD8*, Mahmoud Hashim7*, Jon Ukropec, PhD9, Kevin Liu10*, Maria Krevvata, PhD11*, Annette Lam12*, Sarah Cote12* and Nizar Bahlis, MD4

1Dana-Farber Cancer Institute, Harvard Medical School, Boston, MA
2Veterans Administration Boston Healthcare System, West Roxbury, MA
3Unite de Genomique du Myelome, IUC-T Oncopole, Toulouse, France
4Arnie Charbonneau Cancer Research Institute, University of Calgary, Calgary, AB, Canada
5Centro de Investigación Médica Aplicada, University of Navarra, Clínica Universidad de Navarra, Pamplona, Spain
6Department of Clinical Therapeutics, National and Kapodistrian University of Athens, Athens, Greece
7Ingress Health, Rotterdam, Netherlands
8Ingress-Health, Rotterdam, Netherlands
9Janssen Global Medical Affairs, Horsham, PA
10Janssen Research & Development, LLC, Raritan, NJ
11Janssen Research & Development, LLC, Spring House, PA
12Janssen Global Services, LLC, Raritan, NJ

Introduction: Achievement of MRD negativity in MM is associated with prolonged progression-free survival (PFS) and is being investigated as a potential surrogate for established clinical endpoints, such as PFS and overall survival (OS). Here, we evaluated the predictive utility of MRD in patients (pts) with MM for PFS and OS using a systematic literature review (SLR) and meta-analysis, and investigated how hazard ratios (HR) for PFS and OS, stratified by MRD status, changed for various pt subgroups.

Methods: A SLR was conducted to identify all studies in MM reporting survival outcomes by MRD status (through 8 June 2019). In these studies, MRD was assessed by various assays (multiparametric flow cytometry [MFC], next generation sequencing [NGS], and polymerase chain reaction [PCR]), sensitivity thresholds (10–4, 10–5, and 10–6), and disease settings (relapsed/refractory MM [RRMM], transplant-eligible [TE] and transplant-ineligible [TIE] newly diagnosed MM [NDMM]). Studies with allogeneic transplant, where MRD was measured in peripheral blood or using PET-CT, or from which PFS and OS data could not be extracted were excluded from the analysis. To obtain a pooled effect estimate of MRD status on PFS and OS HRs, a meta-analysis was performed. Subgroup analyses were performed to adjust for variables expected to impact the association of MRD and PFS/OS outcomes. Variables were selected based on available qualitative evidence from studies. Statistical analyses were performed using the ‘metafor’ R package for meta-analyses.

Results: 143 publications met the inclusion criteria; 86 publications were included in the meta-analysis based on data availability (65 PFS and 28 OS HRs). Outcomes for PFS (N = 8590) and OS (N = 3392) were significantly improved for MRD-negative pts: PFS HR 0.35 (95% confidence interval [CI], 0.31-0.39) and OS HR 0.48 (95% CI, 0.41-0.55; P <0.001 for both). This benefit was also observed in pts achieving ≥complete response, with HRs for MRD negativity being 0.44 (95% CI, 0.35-0.54) for PFS and 0.45 (95% CI, 0.28-0.71) for OS (both P <0.001), consistent with results of a previous analysis (Munshi NC, et al. 2017. JAMA Oncol).

When analyzed by MRD sensitivity threshold, HRs for PFS and OS were in favor of MRD-negativity in all subgroups. Outcomes for PFS and OS improved with increasingly stringent sensitivity thresholds. HRs for PFS were 0.36 (95% CI, 0.31-0.42) at 10–4; 0.35 (95% CI, 0.30-0.41) at 10–5, and 0.26 (95% CI, 0.17-0.39) at 10–6 (all P <0.001). For OS, HRs were 0.49 (95% CI, 0.42-0.57) at 10–4 and 0.47 (95% CI, 0.34-0.65) at 10–5 (both P <0.001); analysis of OS at a 10–6 sensitivity threshold was not possible due to limited data availability. MRD analyzed by MFC showed the least benefit, with PFS HRs of 0.39 (95% CI, 0.34-0.44), 0.27 (95% CI, 0.20-0.37), and 0.26 (95% CI, 0.19-0.36) by MFC, NGS, and PCR, respectively. This trend was less pronounced for OS, likely due to reduced data availability. It is possible that older studies reporting MFC used a lower MRD sensitivity threshold, resulting in less favorable HRs.

When analyzed by disease setting, MRD negativity provided superior PFS for both TE NDMM (HR, 0.39 [95% CI, 0.32-0.46]) and TIE NDMM (HR, 0.35 [95% CI, 0.29-0.42]). Consistent with PFS, the effect of MRD-negativity on OS was less pronounced in TE NDMM (HR, 0.53 [95% CI, 0.45-0.63]) than TIE NDMM (HR, 0.40 [95% CI, 0.30-0.54]). As RRMM is an aggressive disease state, achieving MRD-negativity is important for long-term outcomes; notably, our cohort of RRRM pts had a PFS HR of 0.30 (95% CI, 0.18-0.49). Benefit for achieving MRD-negativity was confirmed for PFS in pts with high-risk cytogenetics (HR, 0.44 [95% CI, 0.35-0.57]) and standard-risk cytogenetics (HR, 0.46 [95% CI, 0.32-0.66]). A similar improvement was observed in OS for high-risk (HR, 0.66 [95% CI, 0.46-0.94]) and standard-risk cytogenetic pts (HR, 0.64 [95% CI, 0.54-0.75]). Additional analyses with survival data will be presented.

Conclusions: This meta-analysis, involving a large pt cohort, confirms that MRD negativity has a positive effect on both PFS and OS in both TE and TIE NDMM. Outcomes for MRD-negative pts improve with an increase in MRD assay sensitivity. Pts with RRMM and with high cytogenetic risk also have favorable outcomes for PFS and OS with MRD negativity.

Disclosures: Munshi: Takeda: Consultancy; Abbvie: Consultancy; Celgene: Consultancy; Amgen: Consultancy; Janssen: Consultancy; Adaptive: Consultancy; Oncopep: Consultancy. Avet-Loiseau: celgene: Consultancy, Other: travel fees, lecture fees, Research Funding; takeda: Consultancy, Other: travel fees, lecture fees, Research Funding. Anderson: Janssen: Consultancy, Speakers Bureau; Takeda: Consultancy, Speakers Bureau; Celgene: Consultancy, Speakers Bureau; Bristol-Myers Squibb: Other: Scientific Founder; Oncopep: Other: Scientific Founder; Amgen: Consultancy, Speakers Bureau; Sanofi-Aventis: Other: Advisory Board. Neri: Celgene, Janssen: Consultancy, Honoraria, Research Funding. Paiva: Amgen, Bristol-Myers Squibb, Celgene, Janssen, Merck, Novartis, Roche, and Sanofi; unrestricted grants from Celgene, EngMab, Sanofi, and Takeda; and consultancy for Celgene, Janssen, and Sanofi: Consultancy, Honoraria, Research Funding, Speakers Bureau. Dimopoulos: Amgen: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria; BMS: Consultancy; Sanofi Oncology: Research Funding; Genesis Pharma: Research Funding. Kulakova: Ingress-health: Employment. Heeg: Ingress-Health: Employment. Hashim: Ingress-Health: Employment. Ukropec: Janssen: Employment, Equity Ownership. Liu: Janssen: Employment, Equity Ownership. Krevvata: Janssen: Employment. Lam: Janssen: Employment, Equity Ownership. Cote: Janssen: Employment, Equity Ownership. Bahlis: Takeda: Consultancy, Honoraria; Amgen: Consultancy, Honoraria; AbbVie: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Janssen: Consultancy, Honoraria.

*signifies non-member of ASH