ArticleJournal of medical biochemistry2025
Predictive value of serum tumor markers (carcinoembryonic antigen, neuron-specific enolase, and squamous cell carcinoma antigen in non-small cell lung cancer patients treated with programmed cell death protein 1 inhibitors.
Article in Journal of medical biochemistry, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.
What it found
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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
2 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Association between prognostic nutritional index and prognosis in non-small cell lung cancer patients receiving PD-1/PD-L1 inhibitors: a meta-analysis.Frontiers in nutrition · 2026Pooled it
- Laboratory biomarkers and immunological modulation of sintilimab in gastric cancer: A meta-analysis focused on tumor markers and T-cell subsets.Journal of medical biochemistry · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Adverse reactions (ARs) may occur in patients with advanced non-small cell lung cancer (ANSCLC) undergoing treatment with programmed cell death protein 1 (PD-1) inhibitors (PD-1Is). Establishing a risk assessment model can facilitate personalized treatment. Methods: Clinical data were collected from 215 ANSCLC patients treated with PD-1Is. Patients who experienced ARs were classified as the observation group (OG, 92 cases), while those who did not experience ARs were classified as the control group (CG, 123 cases). A multivariable logistic regression (LR) model was employed to analyze independent risk factors (RFs) associated with ARs, and R Studio software was utilized to create a nomogram predictive model. Results: The concordance index for the nomogram predictive model for ARs in ANSCLC patients treated with PD-1Is was 0.911. The threshold for predicting ARs using the nomogram was more significant than 0.25, providing a clinical net benefit superior to individual indicators such as smoking, tumour-node-metastasis (TNM) staging, neutrophil-to-lymphocyte ratio (NLR), systemic immune-inflammation index (SII), and prognostic nutritional index (PNI). The proportion of smokers in the OG was markedly superior to that in the CG (P<0.05). Conclusions: Smoking, TNM staging, and peripheral blood indicators such as NLR, SII, and PNI are independent RFs for the occurrence of ARs. The constructed nomogram predictive model demonstrates greater clinical utility than individual indicators, enhancing the accuracy of AR predictions.
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Registered trials
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