Post‐transplant consolidation plus lenalidomide maintenance vs lenalidomide maintenance alone in multiple myeloma: A systematic review
Bibliographic record
Abstract
BACKGROUND: In newly diagnosed multiple myeloma (NDMM), autologous stem cell transplantation (ASCT) remains the standard approach for transplant-eligible patients. To control the inevitable relapse, post-transplant consolidation/maintenance strategies are commonly used. However, the benefit of post-transplant consolidation is still uncertain METHOD: We conducted a systematic review of phase II/III studies to compare the efficacy of post-ASCT consolidation plus lenalidomide maintenance (CON+LEN) vs lenalidomide maintenance alone (LEN alone) in NDMM. A meta-analysis using fixed and random effects models was performed. RESULTS: Fourteen studies were included with 2275 participants with NDMM treated with ASCT and lenalidomide maintenance. Two groups were identified: CON+LEN group (n = 1102) and LEN alone group (n = 1173). There was no statistically significant difference in the complete response rate between the two groups [RR = 1.1; 95% CI: 0.83-1.44; P = .490]. Interestingly, we found that very good partial response or better rate is around 1.5-fold significantly higher in the CON+LEN group compared to LEN alone group [RR: 1.46; 95% CI: 1.25-1.70; P < .0001]. However, there was no significant difference between the two groups regarding PFS [RR: 1.0; 95% CI: 0.92-1.08, P = .929] and OS [RR: 0.9; 95% CI: 0.92-1.01; P = .148] at 3-4 years follow-up. The risk of secondary primary malignancy (SPM) was also similar between the two groups (RR: 1.2; 95% CI: 0.84-1.92; P = .2). Data on adverse events were limited. CONCLUSION: Our data suggest that, in NDMM patients treated with upfront ASCT, post-transplant consolidation may improve depth of response, but does not add to OS or PFS, compared to lenalidomide maintenance alone. However, data in this context are still immature.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.005 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.011 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".