ArticleFrontiers in oncology2025
A predictive model and mechanistic study of treatment effectiveness in patients newly diagnosed with small cell lung cancer.
Article in Frontiers in oncology, 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.
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Who cites it
1 citing paper in PubMed.
- A Multi-Faceted Approach to Explore the Role of Inflammatory CAFs, Providing Prognostic Value and Therapeutic Implications in Lung Adenocarcinoma.International journal of genomics · 2025Article
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Authors and funding
8 authors.
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Abstract
Introduction: Extensive-stage small cell lung cancer (ES-SCLC) is an aggressive malignancy with a poor prognosis. This study aimed to identify and validate clinical and laboratory biomarkers for predicting treatment response and overall survival (OS) in ES-SCLC patients. Methods: We retrospectively analyzed 101 ES-SCLC patients receiving first-line treatment. Logistic and Cox regression analyses identified independent factors influencing treatment efficacy and OS. Subgroup analysis was performed to compare white blood cell (WBC) changes between chemotherapy-alone and chemo-immunotherapy groups. Predictive models were constructed and evaluated via cross-validation, ROC, and calibration curves. Differential expression of key proteins (neuron-specific enolase (NSE), fibrinogen (FIB), and gastrin-releasing peptide precursor (ProGRP)) was validated using GEO database data. Results: Pre-chemotherapy tumor size and post-cycle 2 FIB levels were independent predictors of treatment efficacy. Pre-chemotherapy WBC count, pre-chemotherapy D-dimer, and post-cycle 2 ProGRP were independent risk factors for OS. The predictive models demonstrated strong performance. Subgroup analysis showed no significant difference in WBC changes between treatment regimens (mean change: -2.30 ± 2.47 vs. -2.08 ± 2.45, p=0.659). GEO data confirmed the differential expression of FIB and ProGRP. Discussion: Our findings establish robust and validated models based on readily available clinical metrics (tumor size, WBC, D-dimer, FIB, ProGRP) to predict outcomes in ES-SCLC, which could aid in personalizing treatment strategies. The stability of WBC trends across therapies strengthens the prognostic value of baseline WBC.
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