Trial reportInternational journal of radiation oncology, biology, physics2018
Machine Learning on a Genome-wide Association Study to Predict Late Genitourinary Toxicity After Prostate Radiation Therapy.
Trial report in International journal of radiation oncology, biology, physics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 50 papers, 3 of them syntheses that pooled it.
What it found
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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
50 citing papers in PubMed, 3 syntheses or guidelines pooled it, 89 citations in OpenAlex.
- The Role of Artificial Intelligence in the Characterization and Outcome Prediction of Prostate Cancer: A Systematic Review.Tomography (Ann Arbor, Mich.) · 2026Pooled it
- Assessment of Prostate and Bladder Cancer Genomic Biomarkers Using Artificial Intelligence: a Systematic Review.Current urology reports · 2024Pooled it
- The Application and Development of Deep Learning in Radiotherapy: A Systematic Review.Technology in cancer research & treatmentPooled it
- A Pharmacogenetic Prediction Model of Progression-Free Survival in Breast Cancer using Genome-Wide Genotyping Data from CALGB 40502 (Alliance).Clinical pharmacology and therapeutics · 2019Trial
- A genome-wide association study on radiation induced fibrosis in breast cancer patients.Clinical and translational radiation oncology · 2026Article
- Novel method for risk stratification of radiation-induced breast fibrosis: subgroup hypothesis verified by machine learning.NPJ breast cancer · 2026Article
- Phenotypic risk factors linked to acute radiation-induced toxicities: a phenome-wide Mendelian randomization study of 12,042 cancer patients.Journal of Cancer · 2026Article
- Article
- A Polygenic Risk Score for Late Bladder Toxicity Following Radiotherapy for Non-Metastatic Prostate Cancer.Cancer epidemiology, biomarkers & prevention : a publication of the American Association for Cancer Research, cosponsored by the American Society of Preventive Oncology · 2025Article
- Transparency and Representation in Clinical Research Utilizing Artificial Intelligence in Oncology: A Scoping Review.Cancer medicine · 2025Article
- Towards Personalized Radiotherapy in Pelvic Cancer: Patient-Related Risk Factors for Late Radiation Toxicity.Current oncology (Toronto, Ont.) · 2025Review
- Data Science Opportunities To Improve Radiotherapy Planning and Clinical Decision Making.Seminars in radiation oncology · 2024Review
- Remote assessment of cognition and quality of life following radiotherapy for nasopharyngeal carcinoma: deep-learning-based predictive models and MRI correlates.Journal of cancer survivorship : research and practice · 2024Article
- A practical introduction to holo-omics.Cell reports methods · 2024Review
- Acute and long-term toxicity in primary hypofractionated external photon radiation therapy in patients with localized prostate cancer.World journal of urology · 2024Review
- Systematic Review of Genetic Polymorphisms Associated with Acute Pain Induced by Radiotherapy for Head and Neck Cancers.Clinical and translational radiation oncology · 2023Review
- Review
- Predicting the germline dependence of hematuria risk in prostate cancer radiotherapy patients.Radiotherapy and oncology : journal of the European Society for Therapeutic Radiology and Oncology · 2023Article
- Benchmarking machine learning approaches to predict radiation-induced toxicities in lung cancer patients.Clinical and translational radiation oncology · 2023Article
- Application of a genetic signature of late GU toxicity in SCIMITAR, a Post-op SBRT trial.Clinical and translational radiation oncology · 2023Article
Corrections and comments
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Authors and funding
6 authors at 4 institutions in 1 country.
Funding
Abstract
purposeLate genitourinary (GU) toxicity after radiation therapy limits the quality of life of prostate cancer survivors; however, efforts to explain GU toxicity using patient and dose information have remained unsuccessful. We identified patients with a greater congenital GU toxicity risk by identifying and integrating patterns in genome-wide single nucleotide polymorphisms (SNPs). METHODS AND MATERIALS: We applied a preconditioned random forest regression method for predicting risk from the genome-wide data to combine the effects of multiple SNPs and overcome the statistical power limitations of single-SNP analysis. We studied a cohort of 324 prostate cancer patients who were self-assessed for 4 urinary symptoms at 2 years after radiation therapy using the International Prostate Symptom Score.
resultsThe predictive accuracy of the method varied across the symptoms. Only for the weak stream endpoint did it achieve a significant area under the curve of 0.70 (95% confidence interval 0.54-0.86; P = .01) on hold-out validation data that outperformed competing methods. Gene ontology analysis highlighted key biological processes, such as neurogenesis and ion transport, from the genes known to be important for urinary tract functions.
conclusionsWe applied machine learning methods and bioinformatics tools to genome-wide data to predict and explain GU toxicity. Our approach enabled the design of a more powerful predictive model and the determination of plausible biomarkers and biological processes associated with GU toxicity.
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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.