ArticleTherapeutic advances in medical oncology2022
Predicting treatment outcomes using
Article in Therapeutic advances in medical oncology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 2 of them syntheses that pooled it.
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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.
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Who cites it
12 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Prognostic superiority of volumetric PET parameters (MTV and TLG) over SUV in advanced non-small-cell lung cancer: a systematic review and meta-analysis of univariate and multivariate evidence.Frontiers in immunology · 2026Pooled it
- Prognostic value ofFrontiers in immunology · 2022Pooled it
- Predictive modeling of immunotherapy efficacy in driver gene-negative non-small cell lung cancer.Translational lung cancer research · 2026Article
- Chemoimmunotherapy synergism: mechanisms and clinical applications.Naunyn-Schmiedeberg's archives of pharmacology · 2025Review
- The value ofFrontiers in oncology · 2025Article
- Radiomicsmetabolic signature profiles for advanced non-small cell lung cancer with chemoimmunotherapy by reflecting biological function and survival.Translational lung cancer research · 2024Article
- Current trends in the characterization and monitoring of vascular response to cancer therapy.Cancer imaging : the official publication of the International Cancer Imaging Society · 2024Review
- The role of baselineTherapeutic advances in medical oncology · 2024Review
- Relationship of FDG Uptake of the Reticuloendothelial System with Tumor Immune Microenvironment and Prognosis in Patients with Gastric Cancer.Life (Basel, Switzerland) · 2023Article
- A novel analytical approach for outcome prediction in newly diagnosed NSCLC based on [European radiology · 2023Article
- Combined SUVmax and localized colonic wall thickening parameters to identify high-risk lesions from incidental focal colorectalFrontiers in oncology · 2022Article
- Pretreatment CT-Based Machine Learning Radiomics Model Predicts Response in Inoperable Stage III NSCLC Treated with Concurrent Radiochemotherapy Plus PD-1 Inhibitors.Technology in cancer research & treatmentArticle
Corrections and comments
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Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPredictive markers for treatment response and survival outcome have not been identified in patients with advanced non-small-cell lung cancer (NSCLC) receiving chemoimmunotherapy. We aimed to evaluate whether imaging biomarkers of
methodsWe retrospectively enrolled 52 patients with advanced NSCLC who underwent baseline
resultsDuring the median follow-up period of 16.7 months (95% confidence interval: 15.7-17.7 months), 43 (82.7%) and 31 (59.6%) patients experienced disease progression and death, respectively. Objective response was observed in 23 (44.2%) patients. In the multivariate analysis, maximum standardized uptake value, metabolic tumour volume
conclusionPET/CT variables and NLR were useful biomarkers for predicting outcomes of patients with NSCLC receiving pembrolizumab and chemotherapy as a first-line treatment, suggesting their potential as effective markers for combined PD-1 blockade and chemotherapy.
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