ArticleFrontiers in oncology2021
A Risk Prediction Model by LASSO for Radiation-Induced Xerostomia in Patients With Nasopharyngeal Carcinoma Treated With Comprehensive Salivary Gland-Sparing Helical Tomotherapy Technique.
Article in Frontiers in oncology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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Who cites it
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 15 citations in OpenAlex.
- Prognostic models for radiation-induced complications after radiotherapy in head and neck cancer patients.The Cochrane database of systematic reviews · 2025Pooled it
- Trial
- High-Recall Biomedical Language Models for Radiation Oncology Evidence Synthesis: An Integrated Systematic Review of Prediction Models for Radiotherapy-Induced Complications in Nasopharyngeal Carcinoma.Life (Basel, Switzerland) · 2026Review
- Radiation-Induced Xerostomia in Patients With Head and Neck Cancer Treated With Comprehensive Salivary Gland-Sparing Helical Tomotherapy Technique Based on a Back Propagation Artificial Neural Network.Journal of clinical medicine research · 2026Article
- Cohort-based nomogram for forensic prediction of SCD: a single-center pilot study.Forensic science, medicine, and pathology · 2025Article
- The use of machine and deep learning to model the relationship between discomfort temperature and labor productivity loss among petrochemical workers.BMC public health · 2024Article
- Determining risk and predictors of head and neck cancer treatment-related lymphedema: A clinicopathologic and dosimetric data mining approach using interpretable machine learning and ensemble feature selection.Clinical and translational radiation oncology · 2024Article
- Fine Motor Skill Decline After Brain Radiation Therapy-A Multivariate Normal Tissue Complication Probability Study of a Prospective Trial.International journal of radiation oncology, biology, physics · 2023Article
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Authors and funding
9 authors at 4 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveThis study aimed to develop a least absolute shrinkage and selection operator (LASSO)-based multivariable normal tissue complication probability (NTCP) model to predict radiation-induced xerostomia in patients with nasopharyngeal carcinoma (NPC) treated with comprehensive salivary gland-sparing helical tomotherapy technique. METHODS AND MATERIALS: LASSO with the extended bootstrapping technique was used to build multivariable NTCP models to predict factors of patient-reported xerostomia relieved by 50% and 80% compared with the level at the end of radiation therapy within 1 year and 2 years, R50-1year and R80-2years, in 203 patients with NPC. The model assessment was based on 10-fold cross-validation and the area under the receiver operating characteristic curve (AUC).
resultsThe prediction model by LASSO with 10-fold cross-validation showed that radiation-induced xerostomia recovery could be predicted by prognostic factors of R50-1year (age, gender, T stage, UICC/AJCC stage, parotid Dmean, oral cavity Dmean, and treatment options) and R80-2years (age, gender, T stage, UICC/AJCC stage, oral cavity Dmean, N stage, and treatment options). These prediction models also demonstrated a good performance by the AUC.
conclusionThe prediction models of R50-1year and R80-2years by LASSO with 10-fold cross-validation were recommended to validate the NTCP model before comprehensive salivary gland-sparing radiation therapy in patients with NPC.
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