Evaluation of real-world outcomes among CLL patients based on sequencing of BTKi and BCL2i therapies
Bibliographic record
Abstract
Abstract Background: Current first-line (1L) therapies for chronic lymphocytic leukemia (CLL) consist of Bruton tyrosine kinase inhibitors (BTKi) or B-cell lymphoma 2 inhibitors (BCL2i). However, many patients (pts) will require multiple therapies over the course of their treatment and often switch from one of the aforementioned drug classes into the other in second-line (2L). There is limited real-world evidence assessing the impact on clinical outcomes after switching drug classes in pts with relapsed or refractory CLL. This study evaluates real-world time to second subsequent treatment (TSST) among pts with prior BTKi or BCL2i that switched drug classes from the 1L to 2L setting. Methods: The IntegraConnect PrecisionQ de-identified electronic health record database was used to identify pts with CLL that either received BLC2i in the 2L setting after receiving BTKi or received BTKi in the 2L setting after receiving BLC2i. Analyses were restricted to pts that initiated 1L from 4/11/2016 to 1/7/2025. Regimens may consist of multiple drugs, such as the addition of anti-CD20 therapy, but pts that received any combination of BTKi and BLC2i in the 1L or 2L setting were excluded from the analysis. The index date was the initiation of 1L therapy. Descriptive statistics were used to summarize demographic and clinical characteristics by treatment group, including age at index date, race, and ECOG performance status. TSST was defined as the time to third-line (3L) regimen or death from index. Pts that were alive at the end of the observation period that did not initiate a 3L regimen were censored. TSST was analyzed using Kaplan-Meier (KM) survival curves, with median estimates reported. Multivariable Cox proportional hazards regression was used to evaluate the impact of treatment switching on TSST, adjusting for the aforementioned demographic and clinical covariates. Hazard ratios (HRs) and corresponding 95% confidence intervals (CIs) are presented. Results: A total of 852pts met study eligibility, of whom 703 (83%) received BCL2i as 2L therapy after BTKi and 149 (17%) that received BTKi as 2L therapy after BCL2i. There were no significant differences in the distribution of demographic and clinical factors between groups. At the univariable level, there was no difference observed in TSST between treatment groups (Median TSST, BCL2i to BTKi: 66 months, BTKi to BCL2i: 71months, logrank P=0.69). Additionally, there was no significant difference observed in TSST between groups after adjustment for demographic and clinical covariates (HR: 0.97; 95% CI: 0.71–1.33; p=0.86). Conclusions: This study evaluated treatment outcomes in TSST between pts with CLL that had switched drug classes from the 1L to 2L setting (BTKi to BCL2i and BCL2i to BTKi). Overall, no significant differences in TSST were observed. Treatment sequencing considerations are complex, and considerations should be made based on individual pt risk profiles.
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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 | 0.004 | 0.018 |
| 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 | 0.001 | 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".