Pembrolizumab Added to First-Line Cyclophosphamide, Bortezomib and Dexamethasone in Newly Diagnosed Transplant Non-Eligible Myeloma Patients: A Phase 2A Open Label, Multi Centre Study
Bibliographic record
Abstract
Abstract Background: Despite recent improvements, myeloma is still incurable. There is need to add new therapeutic tools. The combination of the proteasome inhibitor (PI) Bortezomib, an alkylator (Cyclophosphamide or Melphalan) and Dexamethasone (Dex) /Prednisone is a widely used first-line therapy. Most patients achieve a rapid response within the first two cycles. The lack of a deep response to the bortezomib-based therapy predicts an inferior outcome, a poor response to newer PIs and limited therapeutic options. Different studies highlighted the role of the PD1/PDL1 pathway in myeloma immune escape and progression. The expression of PDL1 by myeloma cells is higher in relapsed or refractory disease and on minimal residual disease cells. At least one preclinical study showed that the binding of PD1 to PDL1 expressed by the myeloma cells leads to a reverse signal that induces resistance to bortezomib and melphalan. Also, Bortezomib is known to enhance anti-myeloma immune response by different mechanisms, including stimulating myeloma cell apoptosis, sensitizing myeloma cells to natural killer cell mediated killing and enhancing antigen presentation by dendritic cells. This suggests a mutual potentiation between Pembrolizumab and Cyclophosphamide, Bortezomib and Dex (CyBorD). An early immune-based intervention is likely more beneficial. With time and disease progression, the host is more immune-compromised and the disease is more refractory with redundant escape mechanisms. The benefits of early intervention are carefully weighed against the potential risks and other available therapeutic options. The adaptive design of this CMRG-006 trial is meant to select the population with the highest need for treatment improvement while still in the early phase of therapy. We expect the combination of Pembrolizumab and CyBorD to be more effective and well tolerated. Design and Methods: Phase 2A, pilot study. Non-transplant eligible newly diagnosed myeloma patients (NTE-NDMM) will start their standard nine cycles of CyBorD (Cyclophosphamide 300 mg/m 2 PO, Bortezomib 1.5 mg/m 2 SC, and Dex 40 mg PO, all given on days 1, 8, 15 and 22 of 28-day cycle). Patients not having primary disease progression and achieving less than Very Good Partial Response (VGPR) after 2 cycles will be screened for this study during cycle 3. Eligible patients will receive Pembrolizumab 200 mg IV every 3 weeks starting with day 1 of cycle 4 (P-CyBorD). After completion of cycle nine of CyBorD, Pembrolizumab will be administered as a single agent for up to total of 35 doses. The objectives are to evaluate the efficacy and tolerability of P-CyBorD. The key inclusion criteria are having a NTE-NDMM with a measurable disease; no primary progressive disease and not achieving VGPR after two cycles of CyBorD; adequate performance status; and adequate organ functions. The key exclusion criteria include previous exposure to anti-PD1 therapy, intolerance to CyBorD, adverse cardiac history, pulmonary disease, central nervous system disease, congenital or acquired immune suppression, and AL amyloidosis. S ample Size: A maximum of 20 patients will be enrolled to ensure 16 or more patients evaluable for response. Patients with less than VGPR after two cycles of CyBorD have ≤20% probability to achieve ≥VGPR after cycle 9. With the addition of Pembrolizumab, a minimal clinically important difference (MCID) of 10% would be meaningful, and a 50% response rate (≥VGPR) in 16 evaluable patients will be statistically significant. This study is currently recruiting. Clinicaltrials.gov #: NCT04258683. Disclosures Kotb: Amgen: Honoraria; BMS: Honoraria; Merck: Honoraria, Research Funding; Karyopharm: Current holder of individual stocks in a privately-held company; Takeda: Honoraria; Janssen: Honoraria; Celgene: Honoraria; Sanofi: Honoraria, Research Funding; Akcea: Honoraria; Pfizer: Honoraria. Othman: Takeda: Honoraria; Roche: Honoraria; Novartis: Honoraria; Janssen: Honoraria; Sanofi: Honoraria; Celgene: Honoraria. Reece: Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding; Sanofi: Honoraria; Millennium: Research Funding; BMS: Honoraria, Research Funding; Karyopharm: Consultancy, Research Funding; Amgen: Consultancy, Honoraria; GSK: Honoraria.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".