Daratumumab, Lenalidomide, and Dexamethasone Versus Bortezomib, Lenalidomide, and Dexamethasone in Transplant‐Ineligible Newly Diagnosed Multiple Myeloma: A Systematic Literature Review and Meta‐Analysis
Bibliographic record
Abstract
Daratumumab in combination with lenalidomide and dexamethasone (DRd) and bortezomib in combination with lenalidomide and dexamethasone (VRd) are guideline-recommended preferred regimens for initial treatment of transplant-ineligible (TIE) patients with newly diagnosed multiple myeloma (NDMM). This study aimed to systematically identify evidence on the clinical effectiveness of DRd and VRd as first-line treatments for patients with TIE NDMM and to conduct a meta-analysis. Ovid MEDLINE, Embase, and Cochrane Library were searched from January 2019 to June 2023, along with key congresses from January 2018 to June 2023. Bibliographies of relevant systematic literature reviews (SLR) were hand-searched. Randomized controlled trials and appropriately adjusted non-randomized studies comparing DRd versus VRd as first-line treatment for TIE NDMM were included. Overall, five records from three unique studies were identified. The fixed-effects meta-analysis showed a lower risk of disease progression or death with DRd versus VRd using the naïve approach (hazard ratio [HR]: 0.60; 95% confidence interval [CI]: 0.46, 0.77) as well as with the adjusted approach, which accounted for both double counting (i.e., two studies shared one comparison) and variance inflation due to studies with moderate and high risk of bias (HR: 0.56; 95% CI: 0.39, 0.82). In the absence of clinical trials with head-to-head comparison of these treatment regimens, these results could help inform the selection of optimal first-line treatment for TIE NDMM patients.
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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 | 0.014 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.020 | 0.042 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".