The prognostic significance of PD-L1 and PD-1 expression in patients with nasopharyngeal carcinoma: a systematic review and meta-analysis
Bibliographic record
Abstract
BACKGROUND: Whether PD-L1/PD-1 expression plays a significant role in the prognosis of NPC is still controversial. The present study mainly aimed to investigate the prognostic significance of PD-L1/PD-1 expression in patients with NPC. METHODS: A systematical research was performed in the PubMed, Web of Science, EMBASE, and the Cochrane Library databases up to January 06, 2019. Eighteen studies met eligible criteria were included in the meta-analysis. Quality assessment of included articles was evaluated by Newcastle-Ottawa quality assessment scale (NOS). Pooled hazard ratios (HRs) and their corresponding 95% confidence intervals (95% CIs) were used to elucidated the primary endpoint, overall survival (OS), and the secondary endpoints. Furthermore, the relationship between clinicopathological features of NPC and PD-L1/PD-1 expression was estimated by relative ratios (RRs) and 95% CIs. RESULTS: A total of 1836 patients from 15 included studies concerning PD-L1 and 678 patients from six studies regarding PD-1 were included in the meta-analysis. Pooled results revealed that PD-L1 expression in NPC did not correlate with OS (HR 1.34 95% CI 0.93-1.93, p = 0.11), DFS (HR 1.82, 95% CI 0.86-3.85, p = 0.12), PFS (HR 1.19, 95% CI 0.46-3.08, p = 0.72), and DMFS (HR 2.26, 95% CI 0.60-8.56, p = 0.23). Meanwhile, no statistically significant differences existed between the expression level of PD-1 in tumor infiltrating lymphocytes (TILs) and the OS in NPC, with the pooled HR 1.29 (95% CI 0.68-2.42, p = 0.44). In subgroup analysis, higher expression of PD-L1 in immune cells correlated with better OS in patients with NPC, with a pooled HR 0.68 (95% CI 0.47-0.99, p = 0.04). Among the clinicopathological features included in our study, we found that the positive expression of PD-L1 in NPC associated with the higher expression of PD-1 (RR 1.25, 95% CI 1.02-1.52, p = 0.03). CONCLUSIONS: Our meta-analysis indicated that higher/positive expression of PD-L1/PD-1 may not serve as suitable biomarkers for the prognosis of NPC, which was not in consistent with some previous studies about the prognostic value of PD-L1/PD-1 in other types of tumors. Despite the positive results in subgroup analysis and study about clinicopathological features, it may still need corroboration of prospective and large-scale studies.
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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 | 0.013 | 0.028 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.019 | 0.039 |
| Bibliometrics | 0.008 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| 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".