Real-World Persistence and Time to Next Treatment With Ibrutinib in Patients With Chronic Lymphocytic Leukemia/Small Lymphocytic Lymphoma Including Patients at High Risk for Atrial Fibrillation or Stroke
Bibliographic record
Abstract
Background Atrial fibrillation (AF) is a recognized adverse consequence associated with all Bruton's tyrosine kinase inhibitors used to treat chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL); however, real-world time to discontinuation (TTD) and time to next treatment (TTNT) of CLL/SLL patients with a high baseline AF/stroke risk remain unknown. Materials and Methods Patients with CLL/SLL from a nationwide electronic health record-derived database (February 12, 2013-January 31, 2021) initiating first-line (1L) or second or later-line (2L+) treatment with ibrutinib or other regimens on or after February 12, 2014 (index date) were analyzed. Kaplan–Meier survival analysis was used to assess TTD and TTNT among all patients, patients with high AF risk (CHARGE-AF risk score ≥10.0%), and patients at high risk of stroke (CHA 2 DS 2 -VASc risk score ≥3 [females] or ≥2 [males]). Results In 1L/2L+, 2190/1851 patients received ibrutinib and 4388/4135, were treated with other regimens. Median TTD for ibrutinib was similar regardless of AF/stroke-related risk (1L: all patients, 15.7 months; high AF risk, 11.7 months; high stroke risk, 13.7 months; similar results in 2L+). Median TTNT was significantly longer for ibrutinib vs. other regimens (1L: not reached vs. 45.9 months; 2L+: not reached vs. 23.6 months; both P < .05), including among those with high AF/stroke risk. TTNT was similar between all patients and high-risk cohorts in 1L and 2L+ (all P > .05). Conclusion This study highlights that elevated baseline AF/stroke-related risk does not adversely impact TTD and TTNT outcomes associated with ibrutinib use. Additionally, TTNT was significantly longer for patients treated with ibrutinib vs. other regimens.
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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 | 0.001 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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 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".