Evaluating complete response/remission rate as a surrogate endpoint in relapsed/refractory chronic lymphocytic leukemia
Bibliographic record
Abstract
Achieving complete response/remission (CR) by International Workshop on Chronic Lymphocytic Leukemia 2018 criteria indicates complete remission of leukemia in all disease compartments. We evaluated CR rate as a surrogate endpoint for progression-free survival (PFS) in patients with relapsed/refractory (R/R) chronic lymphocytic leukemia (CLL)/small lymphocytic lymphoma (SLL) using data from randomized controlled trials (RCT). A systematic literature review was conducted to identify RCTs with ≥ 2 treatment arms, parallel group design, and reporting CR rate and PFS in patients with R/R CLL/SLL. Association between treatment effects on CR rate and corresponding PFS changes contrasting treatment and control arms was estimated using a weighted linear model, Daniels and Hughes model, and Riley bivariate random-effects meta-analysis. Association between absolute CR rate and PFS within individual treatment arms was estimated using nonparametric (Cox) and parametric (exponential, Weibull, Gompertz) proportional hazards models. Twenty RCTs were identified including 5765 patients with R/R CLL/SLL investigating various treatments (Bruton tyrosine kinase inhibitors, a B-cell lymphoma 2 inhibitor, phosphatidylinositol 3-kinase inhibitors, chimeric antigen receptor T-cell therapy, anti-CD20 monoclonal antibody, chemotherapy). Across RCTs, higher odds of CR resulted in statistically significant lower hazards of disease progression/death, where each 10 % increase in CR rate was associated with a 26 % (95 % confidence interval, 22 %30 %) reduction in risk of progression/death. Cross-validation analyses demonstrated that treatment effects on CR rate reasonably predicted PFS benefits. Results were broadly consistent across different models. This study supports CR rate as an essential treatment goal and a valid surrogate endpoint in R/R CLL/SLL.
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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 | 0.043 | 0.072 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.013 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".