Trial reportFrontiers in immunology2023
Development and validation of a radiomics-based nomogram for predicting a major pathological response to neoadjuvant immunochemotherapy for patients with potentially resectable non-small cell lung cancer.
Trial report in Frontiers in immunology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 55 papers, 3 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
55 citing papers in PubMed, 3 syntheses or guidelines pooled it, 62 citations in OpenAlex.
- Radiomics-Based AI for Predicting Neoadjuvant Immunochemotherapy Pathological Response in Non-Small Cell Lung Cancer: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2026Pooled it
- CT-based radiomics in predicting the efficacy of preoperative neoadjuvant chemoimmunotherapy for non-small cell lung cancer: a systematic review and meta-analysis.Frontiers in immunology · 2026Pooled it
- CT-based radiomics for predicting Ki-67 expression in lung cancer: a systematic review and meta-analysis.Frontiers in oncology · 2024Pooled it
- Study on the expression, prognostic value, and molecular mechanisms of TIMP1 in glioma.Cancer gene therapy · 2026Article
- Radiomics in Lung Cancer Imaging: A Narrative Review of Current Evidence.Journal of imaging · 2026Review
- Value of a radiomics model based on high-resolution large matrix target reconstruction images in predicting the invasiveness of lung adenocarcinoma with pure ground-glass nodules.Biomedical engineering online · 2026Article
- Individualized prediction of brain metastasis risk in patients with breast cancer.Journal of neuro-oncology · 2026Article
- Risk factor identification and nomogram-based predictive model development for recurrence of pituitary adenomas following transsphenoidal surgery: a dual-center retrospective study.Frontiers in surgery · 2026Article
- A Clinical-Radiomics Nomogram Based on Pretreatment Magnetic Resonance Imaging Predicting Tumor Residual at the End of Radiotherapy in Patients With Nasopharyngeal Carcinoma.International journal of biomedical imaging · 2026Article
- CT-derived topological intratumoral heterogeneity predicts major pathological response to neoadjuvant immunochemotherapy in resectable non-small-cell lung cancer: a two-center study.Frontiers in immunology · 2026Article
- Development of a nomogram for predicting incident heart failure and all-cause mortality in patients with chronic kidney disease: a 3-year follow-up study.Frontiers in medicine · 2026Article
- Article
- Abrine targets ERK to suppress EMT and lung metastasis model via MAPKs and Nrf2/Keap-1/HO-1 signaling.Frontiers in immunology · 2026Article
- Article
- AI-based neoadjuvant immunotherapy response prediction across pan-cancer: a comprehensive review.Cancer cell international · 2025Review
- Artificial Intelligence Applications in Interventional Radiology.Journal of personalized medicine · 2025Review
- Article
- Identification and external validation of a prognostic signature based on MAPK-related genes to evaluate survival prognosis and treatment efficacy in lung adenocarcinoma.Clinical and experimental medicine · 2025Article
- Predictive value of the systemic immune-inflammation index in 28-day survival after surgery for intracerebral hemorrhage.European journal of medical research · 2025Article
- Pilot Exploratory Study of a CT Radiomics Model for the Classification of Small Cell Lung Cancer and Non-Small-Cell Lung Cancer in the Moscow Population: A Step Toward Virtual Biopsy.Journal of imaging · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
18 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The treatment response to neoadjuvant immunochemotherapy varies among patients with potentially resectable non-small cell lung cancers (NSCLC) and may have severe immune-related adverse effects. We are currently unable to accurately predict therapeutic response. We aimed to develop a radiomics-based nomogram to predict a major pathological response (MPR) of potentially resectable NSCLC to neoadjuvant immunochemotherapy using pretreatment computed tomography (CT) images and clinical characteristics. Methods: A total of 89 eligible participants were included and randomly divided into training (N=64) and validation (N=25) sets. Radiomic features were extracted from tumor volumes of interest in pretreatment CT images. Following data dimension reduction, feature selection, and radiomic signature building, a radiomics-clinical combined nomogram was developed using logistic regression analysis. Results: The radiomics-clinical combined model achieved excellent discriminative performance, with AUCs of 0.84 (95% CI, 0.74-0.93) and 0.81(95% CI, 0.63-0.98) and accuracies of 80% and 80% in the training and validation sets, respectively. Decision curves analysis (DCA) indicated that the radiomics-clinical combined nomogram was clinically valuable. Discussion: The constructed nomogram was able to predict MPR to neoadjuvant immunochemotherapy with a high degree of accuracy and robustness, suggesting that it is a convenient tool for assisting with the individualized management of patients with potentially resectable NSCLC.
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.