PD-1 or PD-L1 inhibitors in addition to first-line chemotherapy for endometrial cancer: an extracted individual patient data meta-analysis
Bibliographic record
Abstract
Objective: To assess the impact of PD-1/PD-L1 inhibitors in first-line treatment of advanced or recurrent endometrial cancer (EC) through individual patient data (IPD) Meta-analysis, providing insights by integrated survival curves. Methods: We searched PubMed, Embase, Cochrane and meetings up to April 2024 for randomised phase II or III trials (randomised controlled trials) investigating immunotherapy plus chemotherapy for EC. IPD was reconstructed from Kaplan-Meier plots using WebPlotDigitizer and the R package IPDfromKM, and then combined. Results: NRG-GY018, RUBY, MITO END-3, AtTEnd/ENGOT-en7 and DUO-E were included. 2,436 patients were analysed for progression-free survival (PFS) and 2,317 for overall survival (OS). Among these, 621 patients had deficient DNA mismatch repair (dMMR) and 1,815 had the proficient disease (pMMR).The IPD analysis highlighted the significant benefit of adding immunotherapy to chemotherapy in dMMR patients, with 3-year absolute gains of 36% in PFS (HR 0.36, 95% CI 0.28-0.45) and 28% in OS (HR 0.41, 95% CI 0.30-0.48).For pMMR, a smaller benefit was observed in PFS, with a 3-year absolute gain of 6% (HR 0.78, 95% CI 0.69-0.88). Notably, a significant benefit occurred only with PD-1 inhibitors (PFS HR 0.66, 95% CI 0.55-0.79; OS: HR 0.78, 95% CI 0.62-0.96). No significant benefit was seen with PD-L1 inhibitors (PFS: 0.87, 95% CI 0.75-1.03; OS: HR: 0.93, 95% CI 0.75-1.16). Conclusion: This meta-analysis validated the benefit of adding immunotherapy to platinum-based chemotherapy with respect to PFS. dMMR patients gain advantages from the inclusion of either anti-PD-1 or anti-PD-L1 agents, whereas pMMR patients only experience this benefit when treated with anti-PD-1 agents.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.010 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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".