Ibrutinib in Elderly Patients with Chronic Lymphocytic Leukemia: Adverse Event Incidence, Management, and Outcomes in a Canadian Real-World Setting
Bibliographic record
Abstract
BACKGROUND: Long-term clinical trials and real-world data have established a comprehensive risk-benefit profile for ibrutinib, informing adverse event (AE) management strategies to optimize safety and efficacy. METHODS: We retrospectively assessed the incidence of AEs of special interest and management strategies in all patients treated with ibrutinib for chronic lymphocytic leukemia (CLL) in Saskatchewan, Canada, since 2014. RESULTS: Among 187 patients (median age 75.7 years, 63% male), the median time from ibrutinib treatment initiation to data cutoff was 3.1 years. Approximately two-thirds of patients received ibrutinib for relapsed CLL (33.7% second-line and 32.6% third-line and beyond), with 33.7% receiving it first-line. All patients initiated ibrutinib as monotherapy at 420 mg. AEs of interest were observed in 81.3% of patients, with 42.8% experiencing ≥2 AEs. No grade 5 AEs were reported. Among the 284 first-onset AEs observed in 152 patients, 90.8% were successfully managed, allowing treatment continuation. The median time to successful management ranged from 27.0 days (range: 12.5-73.0) for infections to 84.0 days (range: 55.0-141.0) for hypertension. Both AE and discontinuation rates were comparable or favourable to previous reports. CONCLUSION: This real-world analysis suggests that ibrutinib may be safely used in the majority of CLL patients encountered in routine practice.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".