Efficacy of Carfilzomib in the Treatment of Relapsed and (or) Refractory Multiple myeloma: a Meta Analysis of Individual Patient Data from Clinical Trials
Bibliographic record
Abstract
Abstract Multiple myeloma (MM) is a plasma cell malignancy that accounts for approximately 10% of all hematological cancer. Although over the last few decades significant improvement in outcomes has been observed in MM patients, the prognosis of MM remains unfavorable. Existing agents, including the proteasome inhibitor bortezomib and the immunomodulatory agents thalidomide and lenalidomide, have improved outcomes in patients with RRMM greatly. However MM still remains incurable and continuing treatment escalates in complexity while presenting a special therapeutic challenge for patients who these agents have failed. Carfilzomib, a proteasome inhibitor, was approval in 2012 in the United States for RRMM based on efficacy results. Recently, carfilzomib has become a promising therapeutic approach for relapsed and (or) refractory multiple myeloma (RRMM), but no study has summarized the overall effect of carfilzomib in RRMM. To explore the role of carfilzomib, we performed a meta analysis of all known prospective clinical trials to assess the efficacy of carfilzomib in patients with RRMM. Methods and Materials: A systematic review of publications in the PubMed, Embase, the Cochrane Library and ISI Web of knowledge was performed on September 15, 2015 according to the Preferred Reporting Items for Systematic Reviews and Meta Analysis (PRISMA) guidelines. Accounting for some of the inter-study variation, the random-effects model was chosen for the entire study to increase power and precision regardless of heterogeneity. All statistical analyses were conducted by using the STATA software. Meta analyses were carried out to calculate the overall response rate (ORR), complete response rate (CRR) and clinical benefit rate (CBR) of carfilzomib for RRMM. Results: Seven single-arm pilot studies and one randomized controlled trial (RCT) were included. Eight prospective studies enrolled a total of 1,446 patients with 1,000 evaluable patients. The overall quality of the seven single-arm pilot studies was moderate according to Newcastle-Ottawa scale. In the only randomized controlled trial including 792 patients, 396 patients were treated by carfilzomib with lethalidomide and dexamethasome. The quality of this study was adequate according to Cochrane tool for assessment of bias. In patients with RRMM, ORR was 0.44, CRR was 0.13 and CBR was 0.54. High heterogeneity between studies was observed, and funnel plots was symmetrical, negating publication bias. he safety of carfizomib was deemed good and no long-term complications were reported. In the eight prospective studies selected for this analysis, common adverse effect (AE) of the patients varied in different studies, including fatigue, nausea, anemia, thrombocytopenia, neutropenia, diarrhea, etc. Conclusion: In this comprehensive meta analysis, we evaluated the efficacy of carfizomib in the treatment of RRMM. Our meta analysis of the eight studies included, our results demonstrate that carfilzomib is a safe, effective and well tolerated treatment in a large, well-characterized group of patients with RRMM. The lack of severe toxicities observed in patients treated with carfilzomib indicates the potential for full doses of carfilzomib to be used for patients with advanced MM. Disclosures No relevant conflicts of interest to declare.
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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 | 0.034 | 0.043 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.072 |
| Bibliometrics | 0.007 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| 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".