Impact of autologous transplantation on survival in patients with newly diagnosed multiple myeloma who have high‐risk cytogenetics: A meta‐analysis of randomized controlled trials
Bibliographic record
Abstract
Background Despite routine evaluation of cytogenetics in myeloma, little is known regarding the impact of high‐dose therapy (HDT) consolidation on overall survival (OS) or progression‐free survival (PFS) in patients who have high‐risk cytogenetics. The authors performed a meta‐analysis of randomized controlled trials (RCTs) to assess the heterogeneity of HDT efficacy according to cytogenetic risk. Methods All RCTs in patients who had newly diagnosed myeloma from 2000 to 2021 that compared upfront HDT versus standard‐dose therapy (SDT) consolidation were included. The primary objective was to assess the difference in HDT efficacy between standard‐risk and high‐risk cytogenetics in terms of the OS or PFS log(hazard ratio) (HR). The pooled OS and PFS HR was calculated according to cytogenetic‐risk subgroup using a random‐effects model, and heterogeneity (I2) (the percentage of total observed variability explained by between‐study differences) was assessed using an interaction test. Results After screening 3307 citations, 6 RCTs were included for PFS analysis, and 4 were included for OS analysis. The median follow‐up ranged from 3.1 to 7.8 years. The pooled OS HR for HDT versus SDT consolidation in patients with standard‐risk and high‐risk cytogenetics was 0.90 (95% confidence interval [CI], 0.70‐1.17; I2 = 0%) and 0.66 (95% CI, 0.45‐0.97; I2 = 0%), respectively. The difference in HDT efficacy in terms of OS between standard‐risk and high‐risk patients was statistically significant in favor of the high‐risk group (P for interaction = .03). The pooled PFS HR for HDT versus SDT was 0.65 (95% CI 0.56‐0.76; I2 = 0%) versus 0.52 (95% CI, 0.33‐0.83; I2 = 55%), respectively. The difference in HDT efficacy in terms of PFS between standard‐risk and high‐risk patients was not significant (P for interaction = .25). Conclusions The magnitude of OS benefit with upfront HDT is cytogenetics‐dependent. Patients with high‐risk cytogenetics should preferably receive upfront rather than delayed HDT consolidation. Lay Summary Upfront autologous stem cell transplantation improves overall survival in patients with newly diagnosed myeloma harboring high‐risk cytogenetics.
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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 | 0.018 | 0.035 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.047 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".