ArticleRadiology and oncology2020
[18F]FDG PET immunotherapy radiomics signature (iRADIOMICS) predicts response of non-small-cell lung cancer patients treated with pembrolizumab.
Article in Radiology and oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 44 papers, 4 of them syntheses that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
44 citing papers in PubMed, 4 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
- Current status and quality of radiomic studies for predicting immunotherapy response and outcome in patients with non-small cell lung cancer: a systematic review and meta-analysis.European journal of nuclear medicine and molecular imaging · 2021Pooled it
- The Future of Cancer Diagnosis, Treatment and Surveillance: A Systemic Review on Immunotherapy and Immuno-PET Radiotracers.Molecules (Basel, Switzerland) · 2021Pooled it
- Artificial Intelligence for Predicting Immunotherapy Efficacy in Non-Small Cell Lung Cancer.Journal of inflammation research · 2026Review
- The Role of Artificial Intelligence in Theranostics.Journal of nuclear medicine technology · 2025Review
- Survival impact of a KEAP1-NFE2L2 radiomics model in PDL1 ≥ 50% non-small cell lung cancer treated with pembrolizumab: the PEMBROMIC study.Cancer imaging : the official publication of the International Cancer Imaging Society · 2025Article
- Development of a prognostic multiomic biomarker of progression-free survival in advanced non-small cell lung cancer patients treated with first line immunotherapy.Scientific reports · 2025Article
- Prediction of immunotherapy response in nasopharyngeal carcinoma: a comparative study using MRI-based radiomics signature and programmed cell death ligand 1 expression score.European radiology · 2025Article
- BaselineFrontiers in medicine · 2025Article
- Advances in Multimodal Imaging Techniques for Evaluating and Predicting the Efficacy of Immunotherapy for NSCLC.Cancer management and research · 2025Review
- Artificial intelligence in immunotherapy PET/SPECT imaging.European radiology · 2024Review
- [Advancements in Radiomics for Immunotherapy of Non-small Cell Lung Cancer].Zhongguo fei ai za zhi = Chinese journal of lung cancer · 2024Review
- Defining clinically useful biomarkers of immune checkpoint inhibitors in solid tumours.Nature reviews. Cancer · 2024Review
- Integrating Artificial Intelligence and PET Imaging for Drug Discovery: A Paradigm Shift in Immunotherapy.Pharmaceuticals (Basel, Switzerland) · 2024Review
- Applications of CT-based radiomics for the prediction of immune checkpoint markers and immunotherapeutic outcomes in non-small cell lung cancer.Frontiers in immunology · 2024Review
- PET Radiomics and Response to Immunotherapy in Lung Cancer: A Systematic Review of the Literature.Cancers · 2023Review
- Assessment of the Association between Entropy in PET/CT and Response to Anti-PD-1/PD-L1 Monotherapy in Stage III or IV NSCLC.Life (Basel, Switzerland) · 2023Article
- PET Imaging in Bladder Cancer: An Update and Future Direction.Pharmaceuticals (Basel, Switzerland) · 2023Review
- Radiomics of Tumor Heterogeneity inCancers · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background Immune checkpoint inhibitors have changed the paradigm of cancer treatment; however, non-invasive biomarkers of response are still needed to identify candidates for non-responders. We aimed to investigate whether immunotherapy [18F]FDG PET radiomics signature (iRADIOMICS) predicts response of metastatic non-small-cell lung cancer (NSCLC) patients to pembrolizumab better than the current clinical standards. Patients and methods Thirty patients receiving pembrolizumab were scanned with [18F]FDG PET/CT at baseline, month 1 and 4. Associations of six robust primary tumour radiomics features with overall survival were analysed with Mann-Whitney U-test (MWU), Cox proportional hazards regression analysis, and ROC curve analysis. iRADIOMICS was constructed using univariate and multivariate logistic models of the most promising feature(s). Its predictive power was compared to PD-L1 tumour proportion score (TPS) and iRECIST using ROC curve analysis. Prediction accuracies were assessed with 5-fold cross validation. Results The most predictive were baseline radiomics features, e.g. Small Run Emphasis (MWU, p = 0.001; hazard ratio = 0.46, p = 0.007; AUC = 0.85 (95% CI 0.69-1.00)). Multivariate iRADIOMICS was found superior to the current standards in terms of predictive power and timewise with the following AUC (95% CI) and accuracy (standard deviation): iRADIOMICS (baseline), 0.90 (0.78-1.00), 78% (18%); PD-L1 TPS (baseline), 0.60 (0.37-0.83), 53% (18%); iRECIST (month 1), 0.79 (0.62-0.95), 76% (16%); iRECIST (month 4), 0.86 (0.72-1.00), 76% (17%). Conclusions Multivariate iRADIOMICS was identified as a promising imaging biomarker, which could improve management of metastatic NSCLC patients treated with pembrolizumab. The predicted non-responders could be offered other treatment options to improve their overall survival.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.