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Record W4366226148 · doi:10.3389/fimmu.2023.1119168

Prognostic value of programmed cell death ligand 1 expression in patients with intrahepatic cholangiocarcinoma: a meta-analysis

2023· review· en· W4366226148 on OpenAlexaboutno aff
Feng Xian, Dacheng Ren, Jun Bie, Guohui Xu

Bibliographic record

VenueFrontiers in Immunology · 2023
Typereview
Languageen
FieldMedicine
TopicCholangiocarcinoma and Gallbladder Cancer Studies
Canadian institutionsnot available
FundersNatural Science Foundation of Sichuan Province
KeywordsMeta-analysisMedicineFunnel plotInternal medicineCochrane LibraryHazard ratioPublication biasConfidence intervalGastroenterologyOncology

Abstract

fetched live from OpenAlex

Background: Programmed cell death ligand 1 (PD-L1) is highly expressed in intrahepatic cholangiocarcinoma (ICC) tissues. But there is still a dispute over the prognostic value of PD-L1 in patients with ICC. This study aimed to evaluate the prognostic value of PD-L1 expression in patients with ICC. Methods: We performed a meta-analysis based on the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Guidelines. We searched the literature from PubMed, Embase, Web of Science, and the Cochrane Library up to December 5, 2022. Hazard ratios (HR) and their 95% confidence intervals (95% CI) were calculated to analyze the overall survival (OS), recurrence-free survival (RFS), and time to relapse. The quality of the studies was assessed using the Newcastle-Ottawa scale. Publication bias was assessed using a funnel plot and Egger's test. Results: Ten trials with 1944 cases were included in this meta-analysis. The results showed that the low-PD-L1 group had a statistically significant advantage in OS (HR, 1.57; 95% CI, 1.38-1.79, P <0.00001), RFS (HR, 1.62; 95% CI, 1.34-1.97, P <0.00001), and time to relapse (HR, 1.60; 95% CI, 1.25-2.05, P = 0.0002) compared with the high-PD-L1 group. High programmed cell death (PD1)levels, on the other hand, were correlated with poorer OS (HR, 1.96; 95% CI, 1.43-2.70; P <0.0001) and RFS (HR, 1.87; 95% CI, 1.21-2.91; P = 0.005). Multivariate analysis showed that PD-L1 could act as an independent predictor for OS (HR, 1.48; 95% CI, 1.14-1.91; P = 0.003) and RFS (HR, 1.74; 95% CI, 1.22-2.47; P = 0.002), and PD1 acted as an independent predictor for OS (HR, 1.66; 95% CI, 1.15-2.38; P = 0.006). Conclusion: This meta-analysis demonstrated that high PD-L1/PD1 expression is associated with poor survival in ICC. PD-L1/PD1 may be a valuable prognostic and predictive biomarker and potential therapeutic target in ICC. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022380093.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.014
metaresearch head score (Gemma)0.023
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: Meta-analysis
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.016
Threshold uncertainty score0.074

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.023
Meta-epidemiology (narrow)0.0030.002
Meta-epidemiology (broad)0.0160.055
Bibliometrics0.0050.006
Science and technology studies0.0010.001
Scholarly communication0.0030.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0020.000

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.

Opus teacher head0.047
GPT teacher head0.292
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designMeta-analysis
Domainnot available
GenreReview

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".

Quick stats

Citations7
Published2023
Admission routes1
Has abstractyes

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