Safety Analysis of Four Randomized Controlled Studies of Ibrutinib in Patients With Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma or Mantle Cell Lymphoma
Bibliographic record
Abstract
BACKGROUND: Multiple studies have demonstrated the efficacy and safety of ibrutinib for chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) and mantle cell lymphoma (MCL). This first-in-class inhibitor of Bruton's tyrosine kinase has become a standard treatment for patients with CLL and MCL. PATIENTS AND METHODS: We conducted an integrated safety analysis to characterize the frequency, severity, natural history, and outcomes of adverse events (AEs) with ibrutinib versus comparators. Data were pooled from 4 completed randomized controlled studies that had included 756 ibrutinib-treated and 749 comparator-treated patients with CLL/SLL or relapsed/refractory MCL. Safety analyses included reporting of AEs using crude and exposure-adjusted incidence rates. RESULTS: The median treatment duration was 13.3 months (maximum, 28.2 months) for ibrutinib and 5.8 months (maximum, 27.3 months) for comparators. When adjusted for exposure, diarrhea, atrial fibrillation, and hypertension were the only common grade ≥ 3 AEs more often reported with ibrutinib than with the comparators. Dose reductions (7% vs. 14%) and discontinuation (12% vs. 16%) because of AEs occurred less often with ibrutinib, and deaths due to AEs occurred at similar rates (6% vs. 7%). When adjusted for exposure, the corresponding data were all lower with ibrutinib than with the comparators (0.06 vs. 0.22, 0.11 vs. 0.22, and 0.06 vs. 0.09 patient-exposure-years, respectively). The prevalence of common grade 3/4 AEs with ibrutinib generally decreased over time, with the exception of hypertension. CONCLUSION: These results from an integrated analysis support a favorable benefit/risk profile of ibrutinib in patients with CLL/SLL and MCL.
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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 | 0.010 | 0.016 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 0.008 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| 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".