|Table of Contents|

The value of nomogram model based on CT radiomics in predicting the efficacy of stereotactic body radiotherapy for lung tumors

Journal Of Modern Oncology[ISSN:1672-4992/CN:61-1415/R]

Issue:
2023 05
Page:
898-904
Research Field:
Publishing date:

Info

Title:
The value of nomogram model based on CT radiomics in predicting the efficacy of stereotactic body radiotherapy for lung tumors
Author(s):
WANG Huan1; WANG Helong2; WANG Xiao3; HU Songliu1; LI Jian1; WANG Siyu1; LI Gen1; BAI Yang1; XU Jianyu1
1.Department of Radiation Oncology;2.Department of Radiation Physics，Harbin Medical University Cancer Hospital，Heilongjiang Harbin 150081，China;3.Department of Radiation Oncology，Yantai Yuhuangding Hospital,Shandong Yantai 264099，China.
Keywords:
stereotactic body radiotherapy; non-small cell lung cancer; nomogram; radiomics
PACS:
R734.2
DOI:
10.3969/j.issn.1672-4992.2023.05.022
Abstract:
Objective:To construct a nomogram model based on pretreatment CT images to screen radiomics characteristics to predict the radiotherapy efficacy of early stage-non-small cell lung cancer（ES-NSCLC) and oligometastatic lung cancer.Methods:122 patients with ES-NSCLC and lung oligometastatic carcinoma who received stereotactic body radiotherapy（SBRT) were randomly divided into training set and validation set.Radiomics characteristics associated with radiotherapy efficacy in the training set were screened using least absolute shrinkage and selection operator（LASSO) and logistic regression to build nomogram models.Model performance was evaluated with area under the receiver operating characteristic curves，calibration curves，and decision curve analysis（DCA).Results:Six radiomics features were screened to form radiomics score（Rad-score) to establish nomogram model.AUC values were 0.808（95%CI:0.712~0.884，P<0.001) for the model training set and 0.741（95%CI:0.556~0.879，P=0.003) for the validation set.Delong test showed that the model performed equally（P=0.496)，and both the calibration curve and DCA showed a better predictive performance of the model and a higher clinical value.Conclusion:We developed and validated a nomogram model for predicting SBRT treatment efficacy in lung tumors based on pretreatment CT，which has high predictive performance and clinical utility.

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Last Update: 2023-01-31