ArticleLung cancer (Amsterdam, Netherlands)2020
Stable and discriminating radiomic predictor of recurrence in early stage non-small cell lung cancer: Multi-site study.
Article in Lung cancer (Amsterdam, Netherlands), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 41 papers, 1 of them a synthesis 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
41 citing papers in PubMed, 1 synthesis or guideline pooled it, 48 citations in OpenAlex.
- Can quantitative peritumoral CT radiomics features predict the prognosis of patients with non-small cell lung cancer? A systematic review.European radiology · 2023Pooled it
- Development and internal validation of a clinicopathological and CT radiomics based prediction model for extracranial distant metastasis after radical resection in early-stage non-small cell lung cancer.Journal of thoracic disease · 2026Article
- The Diagnostic Value of Deep Learning for Multi-Classification of Rectal Cancer T Staging Based on Regional Attention.Diagnostics (Basel, Switzerland) · 2026Article
- Variability Regularized Feature Selection (VaRFS) for optimal identification of robust and discriminable features from medical imaging.Npj imaging · 2026Article
- [Advances in radiomics for early diagnosis and precision treatment of lung cancer].Sheng wu yi xue gong cheng xue za zhi = Journal of biomedical engineering = Shengwu yixue gongchengxue zazhi · 2025Review
- Review
- Article
- Repeatability and prognostic value of radiomic features: a study in esophageal cancer and nasopharyngeal carcinoma.Insights into imaging · 2025Article
- Computationally integrating radiology and pathology image features for predicting treatment benefit and outcome in lung cancer.NPJ precision oncology · 2025Article
- Developing a Reproducible Radiomics Model for Diagnosis of Active Crohn's Disease on CT Enterography Across Annotation Variations and Acquisition Differences.Journal of imaging informatics in medicine · 2025Article
- Integrative radiomics analysis of peri-tumoral and habitat zones for predicting major pathological response to neoadjuvant immunotherapy and chemotherapy in non-small cell lung cancer.Translational lung cancer research · 2025Article
- MRI-based artificial intelligence models for post-neoadjuvant surgery personalization in breast cancer: a narrative review of evidence from Western Pacific.The Lancet regional health. Western Pacific · 2025Review
- Diagnostic utility of bronchoscopy for newly emerging peripheral pulmonary lesions after pulmonary resection.Translational lung cancer research · 2025Article
- Article
- Rank acquisition impact on radiomics estimation (AсquIRE) in chest CT imaging: A retrospective multi-site, multi-use-case study.Computer methods and programs in biomedicine · 2024Article
- Application of Chest CT Imaging Feature Model in Distinguishing Squamous Cell Carcinoma and Adenocarcinoma of the Lung.Cancer management and research · 2024Article
- 2.5D peritumoural radiomics predicts postoperative recurrence in stage I lung adenocarcinoma.Frontiers in oncology · 2024Article
- Are radiomic signatures ready for incorporation in the clinical pipeline?Translational lung cancer research · 2023Article
- Radiomic predicts early response to CDK4/6 inhibitors in hormone receptor positive metastatic breast cancer.NPJ breast cancer · 2023Article
- Review of the use of radiomics to assess the risk of recurrence in early-stage non-small cell lung cancer.Translational lung cancer research · 2023Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
17 authors at 7 institutions in 1 country.
Funding
Abstract
objectivesTo evaluate whether combining stability and discriminability criteria in building radiomic classifiers will improve the prognosis of cancer recurrence in early stage non-small cell lung cancer on non-contrast computer tomography (CT). MATERIALS AND
methodsCT scans of 610 patients with early stage (IA, IB, IIA) NSCLC from four independent cohorts were evaluated. A total of 350 patients from Cleveland Clinic Foundation and University of Pennsylvania were divided into two equal sets for training (D
resultsA feature selection strategy focusing on both feature discriminability and stability resulted in the classifier having a higher discriminability on validation datasets compared to the discriminability alone criteria in discriminating cancer recurrence (D
conclusionAccounting for both stability and discriminability yielded a more generalizable classifier for predicting cancer recurrence and TTP in early stage 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.