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Record W2905506084 · doi:10.1182/blood-2018-99-113177

Evaluation of Sustained Minimal Residual Disease (MRD) Negativity in Relapsed/Refractory Multiple Myeloma (RRMM) Patients (Pts) Treated with Daratumumab in Combination with Lenalidomide Plus Dexamethasone (D-Rd) or Bortezomib Plus Dexamethasone (D-Vd): Analysis of Pollux and Castor

2018· article· en· W2905506084 on OpenAlexaff
Hervé Avet‐Loiseau, Jesús F. San Miguel, Tineke Casneuf, Shinsuke Iida, Sagar Lonial, Saad Z. Usmani, Andrew Spencer, Philippe Moreau, Torben Plesner, Katja Weisel, Jon Ukropec, Linda Okonkwo, Sonali Trivedi, Christopher Joseph Velas, Xiang Qin, Ming Qi, Christopher Chiu, Nizar J. Bahlis

Bibliographic record

VenueBlood · 2018
Typearticle
Languageen
FieldMedicine
TopicMultiple Myeloma Research and Treatments
Canadian institutionsInstitute of Cancer ResearchUniversity of Calgary
Fundersnot available
KeywordsDaratumumabLenalidomideMedicineInternal medicineOncologyMinimal residual diseaseMultiple myelomaDexamethasoneBone marrow

Abstract

fetched live from OpenAlex

Abstract Introduction: Daratumumab (DARA) is a human IgGκ mAb targeting CD38 with both direct on-tumor and immunomodulatory mechanisms of action, and has been approved as monotherapy for RRMM and in combination with standard of care (SOC) regimens for RRMM and newly diagnosed MM (NDMM). Across three phase 3 DARA studies in RRMM and NDMM, DARA plus SOC reduced the risk of progression or death by ≥50%, enabled a doubling of CR rates, and elicited a ≥3-fold increase in MRD-negative rates. Among MRD-negative RRMM pts, pts treated with D-Rd or D-Vd rapidly achieved MRD negativity and demonstrated prolonged progression-free survival (PFS) vs MRD-positive pts (Avet-Loiseau H, et al. ASH 2016. Abstract 246). MRD assessment is being investigated as a potential surrogate for established endpoints such as overall survival (OS). When measured sequentially, sustained MRD-negativity provides an index of deep clinical responses that may provide a more robust assessment of disease control (Kumar S, et al. Lancet Oncol 2016. 17[8]:e328-e346). Here, we evaluate sustained MRD negativity with DARA plus SOC regimens and its association with PFS/OS outcomes in RRMM. Methods: Eligible pts in POLLUX and CASTOR received ≥1 prior line of therapy and were randomized (1:1) to receive SOC treatment regimens ± DARA. Pts in the POLLUX study were given lenalidomide (25 mg PO) on Days 1-21 and dexamethasone (40 mg) once per week in each 28-day cycle ± DARA (16 mg/kg IV) given weekly for Cycles 1-2, Q2W for Cycles 3-6, and Q4W thereafter. CASTOR pts received 8 cycles (21 d/cycle) of bortezomib (1.3 mg/m2 SC) on Days 1, 4, 8, and 11 and dexamethasone (20 mg) on Days 1, 2, 4, 5, 8, 9, 11, and 12 ± DARA (16 mg/kg IV) given weekly for Cycles 1-3, Q3W for Cycles 4-8, and Q4W thereafter. MRD was assessed at the time of suspected CR and at 3 and 6 months following confirmed CR in POLLUX, and at time of suspected CR and 6 and 12 months following the first treatment dose in CASTOR. Additional MRD evaluation was required in both studies every 12 months post-CR. MRD was assessed via next generation sequencing using the clonoSEQ® assay V2.0 (Adaptive Biotechnologies, Seattle, WA). Sustained MRD negativity was defined as the maintenance of MRD negativity in the bone marrow confirmed ≥6 or ≥12 months apart and was evaluated in the intent-to-treat (ITT) population. Sustained MRD negativity was also evaluated among ≥CR pts to account for different sustained MRD negativity rates between treatment arms. Results: A total of 569 (D-Rd, n = 286; Rd, n = 283) pts in POLLUX and 498 pts (D-Vd, n = 251; Vd, n = 247) in CASTOR were randomized; median (range) number of prior lines received was 1 (1-11) and 2 (1-10), respectively. Median duration of follow up was 39.5 months in POLLUX and 31.3 months in CASTOR for this analysis. Using the ≥6-month sustained MRD cutoff, a significantly higher proportion of pts achieved sustained MRD negativity for ≥6 months when treated with D-Rd vs Rd (16% vs 0.7%; P <0.0001) and D-Vd vs Vd (9% vs 1%; P = 0.0001) among the ITT population. Among ≥CR pts, the proportion of pts with sustained MRD negativity remained higher for pts treated with D-Rd vs Rd (30% vs 3%; P <0.0001) and D-Vd vs Vd (31% vs 13%; P = 0.11). While significantly fewer pts receiving SOC alone achieved sustained MRD negativity, sustained MRD negativity was associated with longer PFS and OS in all treatment arms vs pts without sustained MRD negativity in the ITT population (Figure 1). For the ≥12-month sustained MRD cutoff, more pts achieved sustained MRD negativity when receiving D-Rd vs Rd (13% vs 0.4%; P <0.0001) and D-Vd vs Vd (3% vs 0%; P = 0.0074) in the ITT population. Similar trends were observed for sustained MRD negativity rates among ≥CR pts treated with D-Rd vs Rd (24% vs 2%; P <0.0001) and D-Vd vs Vd (11% vs 0%; P = 0.19). Achievement of sustained MRD negativity for ≥12 months also consistently demonstrated longer PFS and OS for DARA-containing regimens vs those without sustained MRD negativity in the ITT population (Figure 2). Additional analyses, including an analysis of baseline pt characteristics for pts with sustained MRD negativity, will be presented at the meeting. Conclusions: DARA combinations with SOC regimens enable a significantly higher proportion of pts to achieve deep and durable responses of ≥CR and MRD negativity at 10-5. Importantly, the ability to reach durable MRD negativity is associated with prolonged survival, suggesting that achieving durable MRD negativity should be a treatment goal for RRMM pts. Disclosures San-Miguel: Sanofi: Honoraria; Novartis: Honoraria; BMS: Honoraria; Amgen: Honoraria; Celgene: Honoraria; Janssen: Honoraria; Roche: Honoraria. Casneuf:Janssen Research & Development: Employment. Iida:Chugai: Research Funding; Astellas: Research Funding; Bristol Myers Squibb: Honoraria, Research Funding; Kyowa-Hakko Kirin: Research Funding; MSD: Research Funding; Gilead: Research Funding; Toyama Chemical: Research Funding; Teijin Pharma: Research Funding; Sanofi: Consultancy; Novartis: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Ono: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Lonial:Amgen: Research Funding. Usmani:Amgen, BMS, Celgene, Janssen, Merck, Pharmacyclics,Sanofi, Seattle Genetics, Takeda: Research Funding; Abbvie, Amgen, Celgene, Genmab, Merck, MundiPharma, Janssen, Seattle Genetics: Consultancy. Spencer:Celgene: Honoraria, Research Funding, Speakers Bureau; Janssen-Cilag: Honoraria, Research Funding, Speakers Bureau; Amgen: Honoraria, Research Funding; BMS: Research Funding; Takeda: Honoraria, Research Funding, Speakers Bureau; STA: Honoraria. Moreau:Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity's Board of Directors or advisory committees; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees. Plesner:Celgene: Other: Independent Response Assessment Comittee; Janssen: Consultancy. Weisel:Amgen, BMS, Celgene, Janssen, Juno, Sanofi, and Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees; Amgen, BMS, Celgene, Janssen, and Takeda: Honoraria; Amgen, Celgene, Janssen, and Sanofi: Research Funding. Ukropec:Janssen Scientific Affairs, LLC: Employment. Okonkwo:Janssen Research & Development, LLC: Employment. Trivedi:Janssen Research & Development, LLC: Employment. Velas:Janssen Research & Development, LLC: Employment. Qin:Janssen Research & Development, LLC: Employment. Qi:Janssen Research & Development, LLC: Employment. Chiu:Janssen Research & Development, LLC: Employment. Bahlis:Amgen: Consultancy, Honoraria, Research Funding; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.002
Threshold uncertainty score0.008

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.033
GPT teacher head0.306
Teacher spread0.273 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations19
Published2018
Admission routes1
Has abstractyes

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