ReviewNature reviews. Clinical oncology2013
Predicting outcomes in radiation oncology--multifactorial decision support systems.
Review in Nature reviews. Clinical oncology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT02851329 (Association of Computed Tomography Phenotypic Signature With Progression-free Survival in Stage IV EGFR-mutant Non-small Cell Lung Cancer Undergoing Tyrosine Kinase Inhibitors), which is not on this map. Cited by 168 papers, 5 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.
Association of Computed Tomography Phenotypic Signature With Progression-free Survival in Stage IV EGFR-mutant Non-small Cell Lung Cancer Undergoing Tyrosine Kinase Inhibitors
Who cites it
168 citing papers in PubMed, 5 syntheses or guidelines pooled it.
- Application of radiomics-based prediction model to predict preoperative lymph node metastasis in prostate cancer: a systematic review and meta-analysis.Frontiers in oncology · 2025Pooled it
- Clinical application of MR-Linac in tumor radiotherapy: a systematic review.Radiation oncology (London, England) · 2023Pooled it
- The barriers and facilitators of radical innovation implementation in secondary healthcare: a systematic review.Journal of health organization and management · 2021Pooled it
- Systematic Review of Privacy-Preserving Distributed Machine Learning From Federated Databases in Health Care.JCO clinical cancer informatics · 2020Pooled it
- Inclusion of dosimetric data as covariates in toxicity-related radiogenomic studies : A systematic review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2018Pooled it
- Trial
- Trial
- Implementation of a rapid learning platform: Predicting 2-year survival in laryngeal carcinoma patients in a clinical setting.Oncotarget · 2016Trial
- Radiation-induced CD8 T-lymphocyte Apoptosis as a Predictor of Breast Fibrosis After Radiotherapy: Results of the Prospective Multicenter French Trial.EBioMedicine · 2015Trial
- Repeatability of hypoxia PET imaging using [¹⁸F]HX4 in lung and head and neck cancer patients: a prospective multicenter trial.European journal of nuclear medicine and molecular imaging · 2015Trial
- Systematic analysis of 18F-FDG PET and metabolism, proliferation and hypoxia markers for classification of head and neck tumors.BMC cancer · 2014Trial
- Definitive radiation therapy for treatment of laryngeal carcinoma: impact of local relapse on outcome and implications for treatment strategies.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2013Trial
- Benchmarking of radiobiological NTCP models in head and neck radiotherapy using independent computational pipelines: an institutional validation study with machine learning augmentation.Ecancermedicalscience · 2026Article
- Review
- Criteria for establishing a centre of excellence in oncology: a scoping review.BMC health services research · 2025Article
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- Linear Federated Learning for Outcome Prediction With Application to Hepatocellular Carcinoma Radiotherapy.JCO clinical cancer informatics · 2025Article
- Decision tree-based machine learning algorithm for prediction of acute radiation esophagitis.Biochemistry and biophysics reports · 2025Article
- Evaluation of MRI anatomy in machine learning predictive models to assess hydrogel spacer benefit for prostate cancer patients.Technical innovations & patient support in radiation oncology · 2025Article
- Knowledge-Informed Machine Learning for Cancer Diagnosis and Prognosis: A Review.IEEE transactions on automation science and engineering : a publication of the IEEE Robotics and Automation Society · 2025Article
108 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
14 authors.
Funding
Abstract
With the emergence of individualized medicine and the increasing amount and complexity of available medical data, a growing need exists for the development of clinical decision-support systems based on prediction models of treatment outcome. In radiation oncology, these models combine both predictive and prognostic data factors from clinical, imaging, molecular and other sources to achieve the highest accuracy to predict tumour response and follow-up event rates. In this Review, we provide an overview of the factors that are correlated with outcome-including survival, recurrence patterns and toxicity-in radiation oncology and discuss the methodology behind the development of prediction models, which is a multistage process. Even after initial development and clinical introduction, a truly useful predictive model will be continuously re-evaluated on different patient datasets from different regions to ensure its population-specific strength. In the future, validated decision-support systems will be fully integrated in the clinic, with data and knowledge being shared in a standardized, instant and global manner.
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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.