Optimal early endpoint for second-line or subsequent immune checkpoint inhibitors in previously treated advanced solid cancers: a systematic review
Bibliographic record
Abstract
BACKGROUND: The administration of second-line or subsequent immune checkpoint inhibitors (ICIs) in previously treated patients with advanced solid cancers has been clinically investigated. However, previous clinical trials lacked an appropriate primary endpoint for efficacy assessment. This systematic review aimed to explore the most optimal early efficacy endpoint for such trials. METHODS: Phase 2 or 3 clinical trials involving patients with advanced solid cancers with disease progression following standard first-line therapy receiving second-line or subsequent ICI administration, with adequate survival outcome data, were included from PubMed, Embase, Web of Science, and Cochrane Library databases before February 2023. Quality assessment was conducted using the Cochrane tool and Newcastle-Ottawa Quality Assessment Scale for Cohort Studies for randomized controlled trials (RCTs) and non-randomized trials, respectively. Objective response rate (ORR) and progression-free survival (PFS) at 3, 6, and 9 months were investigated as potential early efficacy endpoint candidates for 12-month overall survival (OS), with a strong correlation defined as Pearson's correlation coefficient r ≥ 0.8. RESULTS: A total of 64 RCTs comprising 22,725 patients and 106 non-randomized prospective trials involving 10,608 participants were eligible for modeling and external validation, respectively. RCTs examined 15 different cancer types, predominantly non-small-cell lung cancer (NSCLC) (17, 28%), melanoma (9, 14%), and esophageal squamous cell carcinoma (5, 8%). The median sample size of RCTs was 124 patients, and the median follow-up time was 3.2-57.7 months. The ORR (r = 0.38; 95% confidence interval [CI], 0.18-0.54) and PFS (r = 0.42; 95% CI, 0.14-0.64) exhibited weak trial-level correlations with OS. Within ICI treatment arms, the r values of ORR and 3-, 6-, and 9-month PFS with 12-month OS were 0.61 (95% CI, 0.37-0.79), 0.78 (95% CI, 0.62-0.88), 0.84 (95% CI, 0.77-0.90), and 0.86 (95% CI, 0.79-0.90), respectively. External validation of 6-month PFS indicated an acceptable discrepancy between actual and predicted 12-month OS. CONCLUSIONS: In non-randomized phase 2 trials on second-line or subsequent ICI therapy in patients with advanced solid cancers, 6-month PFS could serve as an early efficacy endpoint. However, early efficacy endpoints are not recommended in RCTs to replace OS.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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 teacher head, 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".