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Evaluating CR as a surrogate endpoint for PFS in R/R chronic lymphocytic leukemia/small lymphocytic lymphoma (CLL/SLL): A meta-analysis of randomized controlled trials (RCT).

2024· article· en· W4399481218 on OpenAlexaff
Lin Wang, Tim Disher, Fei Fei Liu, Murat Kurt, Serena Perna, Elise Aronitz, Toby A. Eyre, Matthew S. Davids

Bibliographic record

VenueJournal of Clinical Oncology · 2024
Typearticle
Languageen
FieldMedicine
TopicChronic Lymphocytic Leukemia Research
Canadian institutionsEVERSANA (Canada)
Fundersnot available
KeywordsMedicineChronic lymphocytic leukemiaRandomized controlled trialOncologyInternal medicineClinical endpointLymphomaSurrogate endpointLeukemia

Abstract

fetched live from OpenAlex

7046 Background: CLL/SLL is the most common leukemia in adults. Achieving a CR by International Workshop on CLL 2018 criteria indicates complete eradication of CLL/SLL in all disease compartments. Patients with R/R CLL/SLL who achieved CR tend to have delayed disease progression/death compared with patients who did not achieve CR. This is the first report to evaluate CR as a surrogate endpoint for PFS in R/R CLL/SLL using aggregate RCT data. Methods: A systematic literature review (SLR) identified published RCTs in R/R CLL/SLL from inception to 10/2023, reporting nonzero CR rates (CRR) and PFS. Association between treatment effects on CR and PFS across RCTs was estimated using a weighted linear model (WLM) in the primary analysis, and Daniels and Hughes (D&H) and Riley bivariate random-effects meta-analysis (BRMA) in sensitivity analyses. Strength of association was assessed based on surrogacy criteria described by D&H. Predictive performance of models was evaluated using leave-one-out cross-validation. Results: The SLR identified 13 RCTs with a total of 4388 patients with R/R CLL/SLL treated with a variety of therapies, including but not limited to BTKi, BCL2i, PI3Ki, CAR T cell therapy, anti-CD20 mAb, and chemotherapy. Across the evidence base, CRR ranged from 0.48% to 38.10% and median PFS was between 1 and 35.9 months (excluding unreached medians). Across RCTs, contrasting treatment and control arms, higher odds of CR resulted in lower hazards of disease progression/death (CRR improvement translated to PFS benefit). D&H surrogacy criteria were met for WLM: 1) a near-zero, statistically nonsignificant intercept, indicating that no treatment effect on CRR implies no effect on PFS; 2) a negative, statistically significant slope, suggesting that improved CRR correlates with longer PFS; and 3) a near-zero conditional variance, meaning that PFS HR variation was primarily explained by CR odds ratio. During cross-validation, treatment effects on CR were predictive of PFS benefits, as the 95% predictive interval of PFS HR contained the observed HR in all RCTs for WLM. Results were largely consistent across all 3 models(Table). Conclusions: Improved CRR corresponds to prolonged PFS across RCTs and treatment comparisons. The results support CRR as an important treatment goal for R/R CLL/SLL and a valid surrogate endpoint. Consistent results and predictive performance across different models indicate the robustness of the results. [Table: see text]

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.033
metaresearch head score (Gemma)0.063
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (broad)
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.986
Threshold uncertainty score0.176

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0330.063
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0140.045
Bibliometrics0.0040.005
Science and technology studies0.0000.001
Scholarly communication0.0030.002
Open science0.0020.001
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.479
GPT teacher head0.588
Teacher spread0.108 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

Study designMeta-analysis
DomainMethods
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

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