ArticleCancer control : journal of the Moffitt Cancer Center
Construction and Verification of a Radiation Pneumonia Prediction Model Based on Multiple Parameters.
Article in Cancer control : journal of the Moffitt Cancer Center. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.
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10 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Predictive value of machine learning for radiation pneumonitis and checkpoint inhibitor pneumonitis in lung cancer patients: a systematic review and meta-analysis.Scientific reports · 2025Pooled it
- Adapting federated radiomics models for radiation pneumonitis prediction in patients receiving thoracic radiotherapy with immunotherapy.Frontiers in immunology · 2026Article
- VPrecision radiation oncology · 2025Article
- A dynamic nomogram predicting symptomatic pneumonia in patients with lung cancer receiving thoracic radiation.BMC pulmonary medicine · 2024Article
- Radiation pneumonia predictive model for radiotherapy in esophageal carcinoma patients.BMC cancer · 2023Article
- Exploring Natural Products as Radioprotective Agents for Cancer Therapy: Mechanisms, Challenges, and Opportunities.Cancers · 2023Review
- Effect of intensity modulated radiotherapy on lymphocytes in patients with esophageal squamous cell carcinoma and its clinical significance.Frontiers in oncology · 2023Article
- Key changes in the future clinical application of ultra-high dose rate radiotherapy.Frontiers in oncology · 2023Article
- Risk analysis of grade ≥ 2 radiation pneumonitis based on radiotherapy timeline in stage III/IV non-small cell lung cancer treated with volumetric modulated arc therapy: a retrospective study.BMC pulmonary medicine · 2022Article
- Diagnostic and Prognostic Value of Dysregulated miR-10a-3p in Patients with Severe Pneumonia.Journal of inflammation research · 2022Article
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11 authors.
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Abstract
objectivePatients with lung cancer are at risk of radiation pneumonia (RP) after receiving radiotherapy. We established a prediction model according to the critical indicators extracted from radiation pneumonia patients. MATERIALS AND
methods74 radiation pneumonia patients were involved in the training set. Firstly, the clinical data, hematological and radiation dose parameters of the 74 patients were screened by Logistics regression univariate analysis according to the level of radiation pneumonia. Next, Stepwise regression analysis was utilized to construct the regression model. Then, the influence of continuous variables on RP was tested by smoothing function. Finally, the model was externally verified by 30 patients in validation set and visualized by R code.
resultsIn the training set, there was 40 patients suffered≥ level 2 acute radiation pneumonia. Clinical data (diabetes), blood indexes (lymphocyte percentage, basophil percentage, platelet count) and radiation dose (V15 > 40%, V20 > 30%, V35 >18%, V40 > 15%) were related to radiation pneumonia (
conclusionThe combination of the basophils percentage, platelet count and V20 is available to build a predictive model of radiation pneumonia for patients with advanced lung cancer.
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