Critical insights on real-life PD-L1 histopathological workflow and assessment in esophageal, esophagogastric junction, and gastric carcinoma in Italy
Bibliographic record
Abstract
BACKGROUND: Immune checkpoint inhibitors (ICIs) targeting programmed cell death protein 1/programmed death-ligand 1 (PD-1/PD-L1) have improved survival in locally advanced and metastatic esophageal, esophagogastric junction, and gastric carcinoma (GEC). Patient selection for ICI-treatment relies on PD-L1 protein expression assessment via immunohistochemistry (IHC). This study aimed to evaluate the real-world assessment of PD-L1 IHC results compared with clinical trial data. PATIENTS AND METHODS: This multicentric, real-world retrospective study analyzed PD-L1 IHC data from 28 Italian pathology centers of GEC cases diagnosed between October 2023 and September 2024. The study documented PD-L1 expression distribution via combined positive (CPS), tumor proportion (TPS), and tumor area positivity (TAP) scores, and investigated the impact of several factors on IHC results. RESULTS: We collected 1936 cases: 1802 adenocarcinomas (ADCA), 131 squamous carcinomas (SCC), and 3 carcinomas of non-specific histotype. Most institutions reported CPS and TPS data, whereas a minority used TAP. Overall, CPS, TPS, and TAP scores were in line with the data in literature and clinical trials for both ADCA and SCC, but inter-institutional heterogeneity was observed as represented by CPS ≥1 ADCA cases (range among institutions: 43.6%-100%). Inter-institutional heterogeneity was significantly associated with several variables, including (i) PD-L1 IHC case workload, with lower workload centers reporting more CPS ≥1 cases on average, and (ii) PD-L1 clone, with the 22C3 clone showing higher CPS scores than the SP263 clone. Tissue block aging was also significantly associated with a lower PD-L1 score, with a critical time window at 24-60 months. CONCLUSIONS: This study confirms the alignment of GEC PD-L1 expression in Italian real-world practice with clinical trials. Inter-institutional variability and the significant influence of preanalytical factors, particularly tissue aging and PD-L1 clone, highlight important challenges in routine PD-L1 testing. Addressing these issues is crucial to enhance the reliability of PD-L1 IHC assessment and ensure optimal patient selection for ICIs in GEC.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".