Retrospective cohort study of real-world treatment patterns and overall survival in patients with chronic lymphocytic leukemia (CLL) diagnosed between 2010 to 2017 in Ontario, Canada.
Bibliographic record
Abstract
e20003 Background: With recent advances in treatment of CLL, it is important to understand emerging treatment patterns and associated outcomes. A population-based study was undertaken to describe the management and survival of CLL patients in Ontario, Canada. Methods: Patients diagnosed with CLL between January 1, 2010 and December 31, 2017 were identified in the Ontario Cancer Registry and linked to provincial administrative databases. Treatment patterns by line of therapy were characterized, including analyses of time to initiation and between therapies. Overall survival was calculated. Results: 2,887 CLL patients were identified (median age 68yr; 67% male). The mean time from diagnosis to first line (1L) treatment was 651 days with 35% of patients receiving fludarabine-cyclophosphamide-rituximab (FCR) based treatment. During the study period, 71% of patients did not yet receive second line (2L) therapy and did not have subsequent follow up, while 19% received 2L ibrutinib. Median time to 2L initiation from 1L treatment discontinuation was 636 days. The table summarizes 1L and 2L therapies. Of the 827 patients on 2L therapy, 65% received ibrutinib. After the introduction of publicly funded novel agents in 2015, a shift in treatment patterns away from FCR and chlorambucil based regimens was observed. Overall mean survival for the cohort from diagnosis was 6.8yrs, and mean 5 year probability of survival was 72.4%. Conclusions: A shift in treatment patterns for CLL can be seen with the introduction of newer therapies, such as ibrutinib. The results can support healthcare decision-makers by characterizing the size of this patient population, real world treatment patterns and survival outcomes for patients with CLL. [Table: see text]
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".