Effect of Lenalidomide Maintenance in Chronic Lymphocytic Leukemia: A Meta-Analysis and Trial-Sequential Analysis
Bibliographic record
Abstract
Chronic lymphocytic leukemia (CLL) is the most common lymphoproliferative disease in adults. Despite durable responses and sustained remission rates to frontline therapy, CLL is still incurable within standard therapy and eventually relapses. Maintenance therapies aim to achieve deep remission. However, the efficacy and safety of lenalidomide maintenance are still debated. Randomized controlled trials published before March 2022 were retrieved from databases. Primary outcomes were progression-free survival (PFS) and overall survival (OS). Trial sequential analysis examined analytical power in primary outcomes. Secondary outcomes were Grade 3–4 neutropenia, treatment discontinuation (TD), serious adverse events (SAE), and fatal adverse events (FAE). Hazard (HR) and odds ratios (ORs) with 95% confidence intervals (CIs) were calculated. Four articles (733 patients) met the selection criteria. Lenalidomide maintenance was associated with a statistically significant effect in prolonging PFS (HR, 0.43; 95% CI, 0.28–0.68; I2 = 57%) and higher proportion of SAE (OR 4.64; 95% CI 2.96–7.26; I2 = 0%) and exhibited no difference in OS (HR, 0.62; 95% CI, 0.29–1.30; I2 = 52%) observation/placebo. It showed no significant difference compared with observation/placebo regarding Grade 3–4 neutropenia (OR 2.30; 95% CI 0.84–6.28; I2 = 81%), TD (OR 0.76; 95% CI 0.29–1.99; I2 = 84%), and FAE (OR 0.86; 95% CI 0.28–2.63; I2 = 0%). Lenalidomide maintenance can prolong PFS in CLL. Further studies should verify its effect on OS.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.015 | 0.019 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.046 |
| 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 | 0.002 |
| 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".