Real-world outcomes following ibrutinib dose reduction in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma
Bibliographic record
Abstract
This study used real-world data from three separate United States (US) databases to evaluate dosing patterns and time to next treatment (TTNT) following the first-incident adverse event (AE) in patients with chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL) treated with first-line ibrutinib with and without dose reduction (DR). Median TTNT or death in patients with and without a DR following an AE in each database was as follows: Optum Clinformatics Data Mart (CDM): 59.5 and 30.6 months; ConcertAI: 27.1 and 18.0 months; and Medicare Fee-for-Service (FFS): 49.8 and 22.0 months, respectively. Median TTNT or death in patients with cardiac AEs, with and without a DR, was: Optum CDM: 44.4 and 22.9 months; ConcertAI: 29.9 and 18.3 months; and Medicare FFS: 49.6 and 14.0 months, respectively. Ibrutinib DR was associated with fewer outpatient visits and lower CLL/SLL-related medical costs. These findings suggest that utilizing ibrutinib DR may effectively manage tolerability without compromising clinical efficacy.
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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 | 0.002 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".