ArticleFrontiers in oncology2021
Evaluation of PD-L1 Expression Level in Patients With Non-Small Cell Lung Cancer by
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 38 papers, 4 of them syntheses that pooled it.
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Who cites it
38 citing papers in PubMed, 4 syntheses or guidelines pooled it, 63 citations in OpenAlex.
- Prediction of PD-L1 expression in nonsmall cell lung cancer using artificial intelligence models based on radiomics: a systematic review and meta-analysis.European respiratory review : an official journal of the European Respiratory Society · 2026Pooled it
- Diagnostic accuracy of ¹⁸F-FDG PET/CT radiomics for non-invasive prediction of PD-L1 expression in non-small cell lung cancer: A systematic review and meta-analysis.Annals of nuclear medicine · 2026Pooled it
- Predictive value of machine learning for PD-L1 expression in NSCLC: a systematic review and meta-analysis.World journal of surgical oncology · 2025Pooled it
- PD-1/PD-L1 inhibitor treatment and its impact on clinical imaging in non-small cell lung cancer: a systematic review and meta-analysis of immune-related adverse events.Frontiers in oncology · 2023Pooled it
- CT-based radiomics as a non-invasive virtual biopsy for high PD-L1 expression prediction in non-small cell lung cancer.Cancer imaging : the official publication of the International Cancer Imaging Society · 2026Article
- A lncRNA and radiomics-based model for predicting the response of non-small cell lung cancer to chemo- and radio-therapy.Scientific reports · 2026Article
- Artificial Intelligence for Predicting Immunotherapy Efficacy in Non-Small Cell Lung Cancer.Journal of inflammation research · 2026Review
- Predicting PD-L1 expression status in NSCLC using radiomic analysis of 18 F-FDG-PET/CT images.European journal of nuclear medicine and molecular imaging · 2026Article
- Review
- Noninvasive Prediction of Programmed Cell Death Protein-Ligand 1 Expression in Locally Advanced Non-small Cell Lung Cancer byAnnals of surgical oncology · 2025Article
- Article
- Predicting PD-L1 status in NSCLC patients using deep learning radiomics based on CT images.Scientific reports · 2025Article
- Evaluation of programmed cell death ligand-1 expression in primary central nervous system lymphoma using whole-tumor histogram analysis of multiparametric MRI: implications for immunotherapy selection.Frontiers in immunology · 2025Article
- Non-invasive assessment of programmed cell death ligand-1 expression usingScientific reports · 2024Article
- Prognostic nomogram combiningScientific reports · 2024Article
- Prediction of PD-L1 and Ki-67 status in primary central nervous system diffuse large B-cell lymphoma by diffusion and perfusion MRI: a preliminary study.BMC medical imaging · 2024Article
- Deep learning radiomics model based on PET/CT predicts PD-L1 expression in non-small cell lung cancer.European journal of radiology open · 2024Article
- Texture Features ofJournal of clinical medicine · 2024Article
- Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Radiomics based onFrontiers in oncology · 2024Article
Corrections and comments
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Authors and funding
5 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeIn the present study, we aimed to evaluate the expression of programmed death-ligand 1 (PD-L1) in patients with non-small cell lung cancer (NSCLC) by radiomic features of
methodsA total 255 NSCLC patients (training cohort: n = 170; validation cohort: n = 85) were retrospectively enrolled in the present study. A total of 80 radiomic features were extracted from pretreatment
resultsA total of 80 radiomic features were extracted in the training dataset. In the univariate analysis, the expression of PD-L1 in lung tumors was significantly correlated with the radiomic signature, histologic type, Ki-67, SUV
conclusionsA prediction model based on PET/CT images and clinicopathological characteristics provided a novel strategy for clinicians to screen the NSCLC patients who could benefit from the anti-PD-L1 immunotherapy.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.