Analysis of PD-L1 Expression in Breast Cancer: A Systematic Review and Meta-Analysis in Asian Population
Bibliographic record
Abstract
OBJECTIVE: This study aimed to investigate the level of PD-L1 protein expression in patients with BCs who were of Asian descent. METHODS: Three databases were conducted on this article up to August 10th, 2022. The reference lists of the publications were examined for further studies, and in cases of duplicates, a study with a larger sample size was added. In survival analysis, the hazard ratio (HR) was applied to the circumstances characterized by the frequency of occurrences, and for the clinicopathological characteristic, the best-adjusted odds ratio (OR) with a 95% confidence interval (CI) was employed. The Newcastle-Ottawa Scale (NOS) was utilized to evaluate selection criteria, comparison, and exposure to establish the quality of the technique in the under-consideration studies. The Z test determined the association analysis of OS, DFS, and clinicopathological characteristics with PD-L1 expression. RESULT: All eight trials for OS and six for DFS were considered, with 4.111 and 3.071 participants, respectively. Overexpression of PD-L1 was linked to a reduced OS compared to individuals with undetectable expression (HR= 1.58, 95% CI 1.04-2.40; P=0.03). We analyzed clinicopathological features, and it elevated in individuals with histological grade III (OR=2.39, 95% CI 1.26-4.54; P=0.008) and positive node (OR=0.68, 95% CI 0.48-0.97; P<0.05). CONCLUSION: Overexpression of PD-L1 was associated with a shorter OS in BCs patients. High PDL1 was higher in persons with nodal positivity and histological grade III.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.010 | 0.005 |
| Bibliometrics | 0.004 | 0.007 |
| 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".