Real-World Effectiveness of Bortezomib Plus Dexamethasone in Patients with t(11;14) Positive Multiple Myeloma
Bibliographic record
Abstract
Abstract Background: Initial studies with venetoclax, a BCL-2 inhibitor, alone or in combination with either dexamethasone or bortezomib and dexamethasone has shown considerable anti-tumor activity in t(11;14) MM with relapsed disease. Based on preclinical studies suggesting synergy when combined with bortezomib and phase 1 data showing efficacy for venetoclax, this combination was compared with bortezomib and dexamethasone (BortDex) in relapsed MM. While the BELLINI (NCT02755597) trial did demonstrate improved PFS with the combination, there were limited number of patients with t(11;14) treated with BortDex. The objective of this study was to assess real-world effectiveness of BortDex in patients with t(11;14) positive relapsed/refractory MM. Patients and methods: This non-interventional, retrospective observational cohort study included patients with t(11;14) MM from the International Myeloma Working Group (IMWG) retrospective study of t(11;14) MM. From the overall cohort, patients with t(11;14) MM receiving BortDex in ≥2 nd and ≤4 th line were initially selected. The cohort was further limited to patients with no evidence of allogeneic SCT within 16 weeks or autologous SCT within 12 weeks prior to BortDex initiation. Finally, patients non-refractory to prior PI regimen and not receiving BortDex regimen as part of a clinical trial were included in the study. Patient demographic and clinical characteristics along with real-world effectiveness outcomes including best response, overall survival (OS), and time to next therapy (TTNT) as a surrogate measure for progression-free survival (PFS) were assessed. All analyses were descriptive in nature and were conducted using the SAS 9.4 (SAS Institute Inc., Cary, NC, USA). Results: Overall, 144 patients who met the inclusion criteria were analyzed. Median age was 62.5 years, 62% were male. Patients had a median of 1 prior line (range 1-3) at start of BortDex, at a median of 18.4 months (range, 1-100) from diagnosis; 29% had a prior transplant. A PR or better was observed in 53% of patients with BortDex. The median TTNT for this cohort was 8.4 months and median OS was 46.1 months. Conclusions: This retrospective study of non-trial patients with t(11;14) MM provides a benchmark for newer therapies in this patient population for comparison with both venetoclax dexamethasone as well as combinations using the -BortDex backbone. Disclosures Emechebe: AbbVie: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company; Pharmaceutical/Biotech Companies: Current holder of stock options in a privately-held company. Kumar: Tenebio: Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Oncopeptides: Consultancy; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Carsgen: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Roche-Genentech: Consultancy, Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Beigene: Consultancy; Antengene: Consultancy, Honoraria; Bluebird Bio: Consultancy; Merck: Research Funding; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; BMS: Consultancy, Research Funding; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Research Funding. Goldschmidt: Takeda: Consultancy, Research Funding; Novartis: Honoraria, Research Funding; Mundipharma: Research Funding; MSD: Research Funding; Molecular Partners: Research Funding; Dietmar-Hopp-Foundation: Other: Grant; Sanofi: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Janssen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Incyte: Research Funding; GSK: Honoraria; Chugai: Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; BMS: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Celgene: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Adaptive Biotechnology: Consultancy; Amgen: Consultancy, Honoraria, Other: Grants and/or Provision of Investigational Medicinal Product, Research Funding; Johns Hopkins University: Other: Grant. Mateos: Takeda: Honoraria, Membership on an entity's Board of Directors or advisory committees; Regeneron: 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; AbbVie: Honoraria; Sea-Gen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Adaptive Biotechnologies: Honoraria, Membership on an entity's Board of Directors or advisory committees; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees; Roche: Honoraria, Membership on an entity's Board of Directors or advisory committees; Celgene - Bristol Myers Squibb: Honoraria, Membership on an entity's Board of Directors or advisory committees; Bluebird bio: Honoraria; Amgen: Honoraria, Membership on an entity's Board of Directors or advisory committees; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria, Membership on an entity's Board of Directors or advisory committees; GSK: Honoraria; Oncopeptides: Honoraria. Kim: Janssen, BMS: Research Funding. Dimopoulos: Janssen: Honoraria; Takeda: Honoraria; Beigene: Honoraria; BMS: Honoraria; Amgen: Honoraria. Ludwig: Janssen, Celgene-BMS, Sanofi, Seattle Genetics: Consultancy, Speakers Bureau; Amgen, Takeda: Consultancy, Research Funding, Speakers Bureau. Handa: Kyowa Kirin: Research Funding; Chugai: Research Funding; Celgene: Honoraria, Research Funding; Daiichi Sankyo: Research Funding; Janssen: Honoraria; BMS: Honoraria; Ono: Honoraria; Sanofi: Honoraria, Research Funding; Abbvie: Honoraria; MSD: Research Funding; Shionogi: Research Funding; Takeda: Honoraria, Research Funding. Fernandez de Larrea: Janssen: Consultancy, Honoraria, Research Funding; BMS: Consultancy, Honoraria, Research Funding; Amgen: Consultancy, Honoraria, Research Funding; Takeda: Honoraria, Research Funding; GSK: Honoraria; Sanofi: Consultancy. Reece: Amgen: Consultancy, Honoraria; GSK: Honoraria; Celgene: Consultancy, Honoraria, Research Funding; Janssen: Consultancy, Honoraria, Research Funding; Sanofi: Honoraria; Millennium: Research Funding; Karyopharm: Consultancy, Research Funding; BMS: Honoraria, Research Funding; Takeda: Consultancy, Honoraria, Research Funding. Raje: Celgene, Amgen, Bluebird Bio, Janssen, Caribou, and BMS: Other. Karve: AbbVie: Current Employment, Current equity holder in publicly-traded company. Arriola: AbbVie: Current Employment, Current holder of individual stocks in a privately-held company, Current holder of stock options in a privately-held company. Ross: AbbVie: Current Employment, Current equity holder in publicly-traded company, Current holder of individual stocks in a privately-held company. Durie: Amgen: Other: fees from non-CME/CE services ; Amgen, Celgene/Bristol-Myers Squibb, Janssen, and Takeda: Consultancy.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
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".