ArticleFrontiers in oncology2020
NTCP Models for Severe Radiation Induced Dermatitis After IMRT or Proton Therapy for Thoracic Cancer Patients.
Article in Frontiers in oncology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 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
23 citing papers in PubMed, 2 syntheses or guidelines pooled it, 34 citations in OpenAlex.
- Evidence-based indications for proton therapy in adults determined using the GRADE approach.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Pooled it
- Improving Prediction of Complications Post-Proton Therapy in Lung Cancer Using Large Language Models and Meta-Analysis.Cancer control : journal of the Moffitt Cancer CenterPooled it
- Potential normal tissue sparing in vulvar cancer using intensity modulated proton therapy versus volumetric modulated arc therapy.Physics and imaging in radiation oncology · 2026Article
- Benchmarking of radiobiological NTCP models in head and neck radiotherapy using independent computational pipelines: an institutional validation study with machine learning augmentation.Ecancermedicalscience · 2026Article
- Evaluating the quality and reliability of radiation dermatitis related videos on Douyin and Bilibili: a cross-sectional analysis.Frontiers in public health · 2026Article
- Artificial intelligence-based automated grading and severity prediction of radiation dermatitis: a review.Radiation oncology (London, England) · 2025Review
- NTCP-Based Prediction of Lung Sparing With IMPT in BC Patients and Implication of Patient Selection.International journal of particle therapy · 2025Article
- Comparison of predicted and actual dermatitis generated from computed tomography images and dose distribution maps.Technical innovations & patient support in radiation oncology · 2024Article
- An Experimental Model of Proton-Beam-Induced Radiation Dermatitis In Vivo.International journal of molecular sciences · 2023Article
- Review
- Prophylactic Use of Mepitel® Film to Prevent Radiation-Induced Moist Desquamation in Cancer Patients.Cureus · 2023Review
- Machine learning for normal tissue complication probability prediction: Predictive power with versatility and easy implementation.Clinical and translational radiation oncology · 2023Article
- IMPT of head and neck cancer: unsupervised machine learning treatment planning strategy for reducing radiation dermatitis.Radiation oncology (London, England) · 2023Article
- A Bayesian optimization tunning integrated multi-stacking classifier framework for the prediction of radiodermatitis from 4D-CT of patients underwent breast cancer radiotherapy.Frontiers in oncology · 2023Article
- A Review of Proton Therapy - Current Status and Future Directions.Precision radiation oncology · 2022Article
- Radiation-Induced Esophagitis in Non-Small-Cell Lung Cancer Patients: Voxel-Based Analysis and NTCP Modeling.Cancers · 2022Article
- Remediation of Mild, Acute Radiation Dermatitis Using a Stem Cell-Based Topical: A Real-World Case Report.Integrative medicine (Encinitas, Calif.) · 2021Article
- Normal tissue complication probability models for prospectively scored late rectal and urinary morbidity after proton therapy of prostate cancer.Physics and imaging in radiation oncology · 2021Article
- Current Situation of Proton Therapy for Hodgkin Lymphoma: From Expectations to Evidence.Cancers · 2021Review
- Radiation-Induced Dyspnea in Lung Cancer Patients Treated with Stereotactic Body Radiation Therapy.Cancers · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 5 institutions in 3 countries.
Funding
Abstract
Radiation therapy (RT) of thoracic cancers may cause severe radiation dermatitis (RD), which impacts on the quality of a patient's life. Aim of this study was to analyze the incidence of acute RD and develop normal tissue complication probability (NTCP) models for severe RD in thoracic cancer patients treated with Intensity-Modulated RT (IMRT) or Passive Scattering Proton Therapy (PSPT). We analyzed 166 Non-Small-Cell Lung Cancer (NSCLC) patients prospectively treated at a single institution with IMRT (103 patients) or PSPT (63 patients). All patients were treated to a prescribed dose of 60 to 74 Gy in conventional daily fractionation with concurrent chemotherapy. RD was scored according to CTCAE v3 scoring system. For each patient, the epidermis structure (skin) was automatically defined by an in house developed segmentation algorithm. The absolute dose-surface histogram (DSH) of the skin were extracted and normalized using the Body Surface Area (BSA) index as scaling factor. Patient and treatment-related characteristics were analyzed. The Lyman-Kutcher-Burman (LKB) NTCP model recast for DSH and the multivariable logistic model were adopted. Models were internally validated by Leave-One-Out method. Model performance was evaluated by the area under the receiver operator characteristic curve, and calibration plot parameters. Fifteen of 166 (9%) patients developed severe dermatitis (grade 3). RT technique did not impact RD incidence. Total gross tumor volume (GTV) size was the only non dosimetric variable significantly correlated with severe RD (
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.