Meta-Analysis of the Efficacy and Adverse Reactions of Ibrutinib in the Treatment of Refractory/Relapsed Mantle Cell Lymphoma
Bibliographic record
Abstract
Objective: Therapeutic results of relapsed/refractory mantle cell lymphoma (R/R MCL) are very disappointing at present, and there is no standard effective treatment regimen. Ibrutinib has been proved to be effective for R/R MCL, however, the sample size of these individual clinical studies was relatively small. Hence, current clinical experience in its usage is still limited. It is necessary to systematically analyze the efficacy and adverse reactions of ibrutinib in the treatment of R/R MCL. Methods: The PubMed, Cochrane Library, and Embase databases were searched using English search terms, mantle cell lymphoma, MCL, and ibrutinib; the VIP, Wanfang, and China National Knowledge Infrastructure (CNKI) databases were searched using the Chinese search terms, ibrutinib and mantle cell lymphoma. The extracted data were subjected to meta-analysis using R software to deduce the effective rate and occurrence rate of serious adverse reactions. Results: A total of 12 cohort studies were included in this analysis. The results demonstrated that ibrutinib could be an efficient therapy regimen for R/R MCL patients and the effect of combination therapy was better than that of single-drug therapy. During the treatment with ibrutinib, the adverse reactions mainly included hematological toxicity, infection, atrial fibrillation, and bleeding. Discussion: Our analysis showed ibrutinib is an optimal second-line treatment for R/R MCL, and the combination therapy is more effective than monotherapy as it was well-tolerated by the patients. Therefore, the combination of other drugs for R/R MCL should be considered for patients with poor efficacy of ibrutinib alone or relapse after treatment.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".