PD-L1 as a response biomarker to chemotherapy plus immune checkpoint inhibitors in operable gastroesophageal adenocarcinoma: a meta-analysis of neoadjuvant clinical trials
Bibliographic record
Abstract
Background Perioperative chemoimmunotherapy [i.e. chemotherapy plus immune checkpoint inhibitor (ICI) (ChT–ICI)] is an investigational treatment for operable gastroesophageal adenocarcinoma (GEA) with unclear outcomes in an unselected population. We aimed to assess the cumulative treatment effect of ChT–ICI on pathological response rates, the surrogacy of pathological response rates on overall survival (OS), and the value of programmed death-ligand 1 (PD-L1) as a biomarker of response to ICIs in operable GEA. Methods We conducted a systematic review and meta-analysis of randomised clinical trials (RCTs) of ChT with or without ICIs with the primary outcome being pathological response rates [pathological complete response (pCR) and similar metrics]. A weighted linear regression model quantified the relationship between pathological response rates and OS using a determination coefficient ( R 2 ). A second meta-regression analysed the predictive effect of PD-L1 on pCR in trials of ICIs with ChT or chemoradiotherapy (CRT). Results A total of 18 records from 15 RCTs were included. Of 6624 patients, 5291 received ChT and 1333 ChT–ICI. ChT–ICI significantly improved pathological response rates [pooled odds ratio 3.18, 95% confidence interval (CI) 2.42-4.18, P < 0.0001] compared with ChT (pooled odds ratio 1.66, 95% CI 1.33-2.07, P < 0.0001). The correlation between pathological response and OS was low ( R 2 = 0.12) but improved in recent trials ( R 2 = 0.51) and those with ChT–biological agents, including ICIs ( R 2 = 0.79). In the second analysis (11 studies, 633 patients), PD-L1 ≥5 was a significant predictor of response both individually (estimate: 0.73, 95% CI 0.28-1.18, P = 0.001) and after accounting for the backbone treatment (estimate: 0.80, 95% CI 0.28-1.33, P = 0.003). Conclusions Perioperative ChT–ICI improves pathological response rates in operable GEA and PD-L1 ≥5 is a significant biomarker of pCR, supporting stratification by PD-L1 and the design of biomarker-selected trials.
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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 | 0.020 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.046 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".