ArticleFrontiers in immunology2025
Predictive value of peripheral blood CD4
Article in Frontiers in immunology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A machine learning-driven prognostic model based on peripheral blood lymphocyte subsets in osteosarcoma.Frontiers in immunology · 2026Article
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Early assessment of the efficacy of immune checkpoint inhibitor (ICI) therapy in advanced hepatocellular carcinoma (HCC) patients plays a crucial role. In this study, we systematically analyzed the predictive values of various lymphocyte subpopulations (CD4 Materials and methods: We systematically reviewed the clinical data of these patients in our hospital. Logistic regression analyses were conducted to identify variables predicting OR. Cut-off values were determined by maximizing Youden index. Then, patients were stratified based on these cut-off values, and Kaplan-Meier analysis with log-rank test was used to compare progression-free survival (PFS) and overall survival (OS) between groups. Results: A total of 41 patients were included. Multivariate logistic regression analysis revealed that W3 CD4 Conclusions: W3 CD4
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Registered trials
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