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
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.
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