Time to Next Treatment in Patients with Chronic Lymphocytic Leukemia Initiating First-Line Ibrutinib or Acalabrutinib
Bibliographic record
Abstract
Aim: To investigate real-world time to next treatment in patients with chronic lymphocytic leukemia initiating first-line (1L) ibrutinib or acalabrutinib. Materials & methods: US specialty pharmacy electronic medical records (11/21/2018–4/30/2022) were used; patients initiated 1L on/after 11/21/2019 (acalabrutinib approval). Results: Among 710 patients receiving ibrutinib, 5.9% initiated next treatment (mean time to initiation = 9.2 months); among 373 patients receiving acalabrutinib, 7.5% initiated next treatment (mean time to initiation = 5.9 months). Adjusting for baseline characteristics, acalabrutinib-treated patients were 89% more likely to initiate next treatment (hazard ratio = 1.89; p = 0.016). Conclusion: This study addresses a need for real-world comparative effectiveness between 1L ibrutinib and acalabrutinib and shows that next treatment (a clinically meaningful measure for real-world progression) occurred less frequently with 1L ibrutinib.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| 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) | 0.002 | 0.006 |
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; both teacher heads agree on what is shown here.
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".