ArticleJournal of thoracic disease2026
Risk stratification of PD-L1 expression in non-small cell lung cancer: a predictive model for prognosis.
Article in Journal of thoracic disease, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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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.
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Authors and funding
16 authors.
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Abstract
Background: Immune checkpoint inhibitors (ICIs) have become the standard of care for non-small cell lung cancer (NSCLC) patients with programmed cell death ligand-1 (PD-L1) expression ≥1%. However, not all patients benefit equally from this treatment. This study develops a predictive model for risk stratification in NSCLC patients, integrating clinical, radiological, genomic, and PD-L1 expression data to enhance immunotherapy outcomes. Methods: We conducted a multicenter, retrospective cohort study of NSCLC patients treated with immunotherapy from January 2018 to June 2024. The primary endpoint was overall survival (OS), and secondary endpoints included progression-free survival (PFS). We constructed a prognostic nomogram using Kaplan-Meier survival analysis and multivariable Cox regression to identify key prognostic factors. Model performance was rigorously validated internally via C-index, time-dependent receiver operating characteristic (time-ROC) curves, calibration plots, 1,000-replicate bootstrap resampling, and decision curve analysis (DCA)-and patients were stratified into distinct risk groups. Results: PD-L1 expression ≥1% was associated with significantly improved OS (563 Conclusions: The prognostic model constructed in this study has excellent short-term predictive efficacy and clinical practicability. It can effectively stratify the prognosis risks of NSCLC patients after ICIs treatment, providing a convenient quantitative reference for clinical decision-making.
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