Cyclophosphamide, Bortezomib and Dexamethasone (CyBorD) Compared to Lenalidomide and Dexamethasone (LD) for the Treatment of Non-Transplant Eligible Multiple Myeloma
Bibliographic record
Abstract
Abstract Introduction: Cyclophosphamide, bortezomib and Dexamethasone (CyBorD) has become the standard frontline approach for the treatment of multiple myeloma (MM) in many centers across Canada. In the non-transplant eligible setting, recently a randomized controlled trial reported on the impact of Lenalidomide and Dexamethasone (LD), showing that this doublet-therapy is a feasible and efficacious combination. Based on the above-mentioned success of the LD combination, we aimed to compare the effect of CyBorD and LD for the treatment of non-transplant eligible MM (NTE) patients in the Alberta Myeloma and Dysproteinemia Program (AMDP). Patients and Methods: The primary objective was to assess ORR and PFS for NTE MM patients treated with CyBorD and LD. The recommended CyBorD regimen was as follows: bortezomib 1.3-1.5 mg/m2 SC or IV days 1, 8, 15 of a 28 day cycle (as of August, 2013 we adopted the a strategy whereby bortezomib can also be given on day 22), cyclophosphamide 300 mg/m2 PO days 1, 8, 15 and 22 and dexamethasone 20-40 mg PO days 1, 8, 15 and 22 with an aim to deliver a minimum of 9 cycles of treatment. LD was given at 25 mg days 1-21 of a 28-day cycle with Dexamethasone 20-40 mg PO days 1, 8, 15 and 22. Dose adjustments were at the discretion of the treating physician. Two-sided Fisher exact test was used to test for differences between categorical variables. A p value of <0.05 was considered significant and survival curves were constructed according to the Kaplan-Meier method and compared using the log rank test. Results: Ninety-one patients have received CyBorD and 56 have received LD. Clinical characteristics are shown in Table 1. At the time of analysis, 64 and 32 patients in the CyBorD and LD are alive of which 10 and 11, respectively, have progressed, ORR and VGPR rates were 85.7% and 56% for patients treated with CyBorD, and 83.9% and 64% for LD respectively (p=0.3). Estimated median OS was 40 months for CyBorD compared to 66 months for LD (p=0.156). In addition, median PFS was longer for LD patients compared to CyBorD (26 months vs 16.4 months, p=0.018). The rate of treatment discontinuation was similar between both groups (8.7% vs 10%, p=0.3). In Conclusion: CyBorD and LD appeared to be effective treatment options for NTE myeloma patients with similar response rates. Recognizing the limitations of a retrospective series, it is interesting to note a longer PFS and a trend towards better PFS in the LD group, however, longer follow-up and prospective validation is still required. Table 1. Clinical Characteristics Characteristic CyBorD, n=91 LD, n=56 P value Age (median) 73.9 73.6 0.2 GenderMaleFemale 57 (62.6%)34 (37.4%) 34 (60.7%)22 (39.3%) 0.8 B2microglobulin (µmol/L) 4.9 4.89 0.4 Albumin (g/L) 35 36 0.7 Stage IStage IIStage III 17.7%35.4%46.9% 23.5%37.2%39.3% 0.6 BMPC (%) 32 37.5 0.6 Heavy chain:IgGIgAFLC onlyIgDIgMBiclonal 501018113 26179010 0.068 Response rateORRCR/nCRVGPRPR 85.7%23%31.8%30.7 83.9%28%37.5%17.8% 0.3 Ab: BMPC: Bone marrow plasma cell Figure 1. Overall Survival according to treatment regimen Figure 1. Overall Survival according to treatment regimen Figure 2. Progression-Free survival according to treatment regimen Figure 2. Progression-Free survival according to treatment regimen Disclosures Jimenez-Zepeda: Celgene: Honoraria; Amgen: Honoraria; J&J: Honoraria. Venner:J&J: Honoraria, Research Funding; Celgene: Honoraria, Research Funding; Amgen: Honoraria. Sandhu:Janssen: Consultancy, Honoraria; Celgene: Consultancy, Honoraria; Novartis: Consultancy, Honoraria; Amgen: Consultancy, Honoraria. Duggan:Celgene: Honoraria; Jansen: Honoraria. Neri:Celgene: Research Funding. Bahlis:Johnson & Johnson: Speakers Bureau; Johnson & Johnson: Research Funding; Amgen: Consultancy; Johnson & Johnson: Consultancy; Celgene: Consultancy, Honoraria, Research Funding, Speakers Bureau.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.003 | 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".