Treatment Discontinuation Patterns for Patients With Chronic Lymphocytic Leukemia in Real-World Settings: Results From a Multi-Center International Study
Bibliographic record
Abstract
INTRODUCTION: This study assessed treatment discontinuation patterns and reasons among chronic lymphocytic leukemia (CLL) patients initiating first-line (1L) and second-line (2L) treatments in real-world settings. MATERIALS AND METHODS: Using deidentified electronic medical records from the CLL Collaborative Study of Real-World Evidence, premature treatment discontinuation was assessed among FCR, BR, BTKi-based, and BCL-2-based regimen cohorts. RESULTS: Of 1364 1L patients (initiated in 1997-2021), 190/13.9% received FCR (23.7% discontinued prematurely); 255/18.7% received BR (34.5% discontinued prematurely); 473/34.7% received BTKi-based regimens, of whom 28.1% discontinued prematurely; and 43/3.2% received venetoclax-based regimens, of whom 16.3% discontinued prematurely (venetoclax monotherapy: 7/0.5%, of whom 42.9% discontinued; VG/VR: 36/2.6%, of whom 11.1% discontinued). The most common reasons for treatment discontinuation were adverse events (FCR: 25/13.2%; BR: 36/14.1%; BTKi-based regimens: 75/15.9%) and disease progression (venetoclax-based: 3/7.0%). Of 626 2L patients, 20/3.2% received FCR (50.0% discontinued); 62/9.9% received BR (35.5% discontinued); 303/48.4% received BTKi-based regimens, of whom 38.0% discontinued; and 73/11.7% received venetoclax-based regimens, of whom 30.1% discontinued (venetoclax monotherapy: 27/4.3%, of whom 29.6% discontinued; VG/VR: 43/6.9%, of whom 27.9% discontinued). The most common reasons for treatment discontinuation were adverse events (FCR: 6/30.0%; BR: 11/17.7%; BTKi-based regimens: 60/19.8%; venetoclax-based: 6/8.2%). CONCLUSION: The findings of this study highlight the continued need for tolerable therapies in CLL, with finite therapy offering a better tolerated option for patients who are newly diagnosed or relapsed/refractory to prior treatments.
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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) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".