Genetic variants of <i>SP‐D</i> confer susceptibility to radiation pneumonitis in lung cancer patients undergoing thoracic radiation therapy

Cui

et al. 2020

Front. Oncol.

PurposeWe quantitatively analyzed the characteristics of cone-beam computed tomography (CBCT) radiomics in different periods during radiotherapy (RT) and then built a novel nomogram model integrating clinical features and dosimetric parameters for predicting radiation pneumonitis (RP) in patients with esophageal squamous cell carcinoma (ESCC).MethodsAt our institute, a retrospective study was conducted on 96 ESCC patients for whom we had complete clinical feature and dosimetric parameter data. CBCT images of each patient in three different periods of RT were obtained, the images were segmented using both lungs as the region of interest (ROI), and 851 image features were extracted. The least absolute shrinkage selection operator (LASSO) was applied to identify candidate radiomics features, and logistic regression analyses were applied to construct the rad-score. The optimal period for the rad-score, clinical features, and dosimetric parameters were selected to construct the nomogram model and then the receiver operating characteristic (ROC) curve was used to evaluate the prediction capacity of the model. Calibration curves and decision curves were used to demonstrate the discriminatory and clinical benefit ratios, respectively.ResultsThe relative volume of total lung treated with ≥5 Gy (V5), mean lung dose (MLD), and tumor stage were independent predictors of RP and were finally incorporated into the nomogram. When the three time periods were modeled, the first period was better than the others. In the primary cohort, the area under the ROC curve (AUC) was 0.700 (95% confidence interval (CI) 0.568–0.832), and in the independent validation cohort, the AUC was 0.765 (95% CI 0.588–0.941). In the nomogram model that integrates clinical features and dosimetric parameters, the AUC in the primary cohort was 0.836 (95% CI 0.700–0.918), and the AUC in the validation cohort was 0.905 (95% CI 0.799–1.000). The nomogram model exhibits excellent performance. Calibration curves indicate a favorable consistency between the nomogram prediction and the actual outcomes. The decision curve exhibits satisfactory clinical utility.ConclusionThe radiomics model based on early lung CBCT is a potentially valuable tool for predicting RP. V5, MLD, and tumor stage have certain predictive effects for RP. The developed nomogram model has a better prediction ability than any of the other predictors and can be used as a quantitative model to predict RP.

Section: Discussionmentioning

confidence: 99%

A Novel Nomogram Model Based on Cone-Beam CT Radiomics Analysis Technology for Predicting Radiation Pneumonitis in Esophageal Cancer Patients Undergoing Radiotherapy

Cui

et al. 2020

Front. Oncol.

“…Numerous dosimetric indicators of the lung have been widely veri ed in previous studies for RP, such as total or ipsilateral lung V5, V10, V13, V20 [6][7][8][9][10][11][12][13][14] . Furthermore, the dosimetric indicators about esophagus, which may have not been previously well established as predictors, were also considered in this study.…”

Section: Discussionmentioning

confidence: 99%

“…Previous studies have shown the importance of clinical characteristics, dosimetric parameters factors as well as laboratory indicators, such as pack-years, baseline pulmonary function, a history of lung resection, mean lung dose (MLD), total or ipsilateral lung volume receiving more than 2000 cGy (V20), total lung V10, total lung V13, ipsilateral lung V5, interleukin-8, recombinant human eotaxin-2, recombinant human eotaxin-22, recombinant human eotaxin-17 and so on [6][7][8][9][10][11][12][13] . In addition, genetic variants of pulmonary surfactant-associated glycoprotein D, homeodomain interacting protein kinase 2 and interleukin-4 were also reported to be associated with risk of RP development [14][15][16] . And the combination of chemotherapy has also been implicated in increasing chances of developing RP [10,17,18] .…”

Section: Introductionmentioning

confidence: 99%

A Novel Nomogram Containing Acute Radiation Esophagitis Predicting Radiation Pneumonitis in Thoracic Cancer Receiving Radiotherapy

et al. 2020

Preprint

BackgroundRadiation-induced pneumonitis (RP) is a non-negligible and sometimes life-threatening complication in patients with thoracic radiation. We initially aimed to ascertain the predict value of acute radiation-induced esophagitis (SARE, grade≥2) to symptomatic RP (SRP, grade≥2) among thoracic cancer patients receiving radiotherapy. Based on that, we also established a novel nomogram model to provide individualized risk assessment for SRP.MethodsPatients with thoracic cancer who were treated with thoracic radiation from Jan 2018 to Jan 2019 in Shandong Cancer Hospital and Institute were enrolled prospectively. All patients were followed up during and after radiotherapy (RT) to observe the appearance of esophagitis and pneumonitis. Variables were analyzed by univariate and multivariate analysis using the logistic regression model, and a nomogram model was established to predict SRP by "R" version 3.6.0.ResultsA total of 123 patients were enrolled (64 esophageal cancer, 57 lung cancer and 2 mediastinal cancer) in this study prospectively. RP grades of 0, 1, 2, 3, 4 and 5 occurred in 29, 57, 31, 0, 3 and 3 patients, respectively. SRP appeared in 37 patients (30.1%). In univariate analysis, SARE was shown to be a significant predictive factor for SRP (P < 0.001), with the sensitivity 91.9% and the negative predictive value 93.5%. The incidence of SRP in different grades of ARE were as follows: Grade 0-1: 6.5%; Grade 2: 36.9%; Grade 3: 80.0%; Grade 4: 100%. Besides that, the dosimetric factors considering total lung mean dose, total lung V5, V20, ipsilateral lung mean dose, ipsilateral lung V5, and mean esophagus dose were correlated with SRP (all P < 0.005) by univariate analysis. The incidence of SRP was significantly higher in patients whose symptoms of RP appeared early. SARE (HR 34.408, P = 0.001), mean esophagus dose and ipsilateral mean lung dose were still significant in multivariate analysis, and they were included to build a predictive nomogram model for SRP.ConclusionsSARE was an easy index that can reflect patients’ radiosensitivity visually, which could be an applicable predictor for SRP in patients receiving thoracic radiation. And the nomogram could assist in accurate prediction to SRP in clinic.

“…Previous studies have shown the importance of clinical characteristics, dosimetric parameters factors as well as laboratory indicators, such as pack-years, baseline pulmonary function, a history of lung resection, mean lung dose (MLD), total or ipsilateral lung volume receiving more than 2000 cGy (V20), total lung V10, total lung V13, ipsilateral lung V5, interleukin-8, recombinant human eotaxin-2, recombinant human eotaxin-22, recombinant human eotaxin-17 and so on [ 6 – 13 ]. In addition, genetic variants of pulmonary surfactant-associated glycoprotein D, homeodomain interacting protein kinase 2 and interleukin-4 were also reported to be associated with RP development [ 14 – 16 ]. And the combination of chemotherapy has also been implicated in increasing chances of developing RP [ 10 , 17 , 18 ].…”

Section: Introductionmentioning

confidence: 99%

A novel nomogram containing acute radiation esophagitis predicting radiation pneumonitis in thoracic cancer receiving radiotherapy

et al. 2021

BMC Cancer

Background Radiation-induced pneumonitis (RP) is a non-negligible and sometimes life-threatening complication among patients with thoracic radiation. We initially aimed to ascertain the predictive value of acute radiation-induced esophagitis (SARE, grade ≥ 2) to symptomatic RP (SRP, grade ≥ 2) among thoracic cancer patients receiving radiotherapy. Based on that, we established a novel nomogram model to provide individualized risk assessment for SRP. Methods Thoracic cancer patients who were treated with thoracic radiation from Jan 2018 to Jan 2019 in Shandong Cancer Hospital and Institute were enrolled prospectively. All patients were followed up during and after radiotherapy (RT) to observe the development of esophagitis as well as pneumonitis. Variables were analyzed by univariate and multivariate analysis using the logistic regression model, and a nomogram model was established to predict SRP by “R” version 3.6.0. Results A total of 123 patients were enrolled (64 esophageal cancer, 57 lung cancer and 2 mediastinal cancer) in this study prospectively. RP grades of 0, 1, 2, 3, 4 and 5 occurred in 29, 57, 31, 0, 3 and 3 patients, respectively. SRP appeared in 37 patients (30.1%). In univariate analysis, SARE was shown to be a significant predictive factor for SRP (P < 0.001), with the sensitivity 91.9% and the negative predictive value 93.5%. The incidence of SRP in different grades of ARE were as follows: Grade 0–1: 6.5%; Grade 2: 36.9%; Grade 3: 80.0%; Grade 4: 100%. Besides that, the dosimetric factors considering total lung mean dose, total lung V5, V20, ipsilateral lung mean dose, ipsilateral lung V5, and mean esophagus dose were correlated with SRP (all P < 0.05) by univariate analysis. The incidence of SRP was significantly higher in patients whose symptoms of RP appeared early. SARE, mean esophagus dose and ipsilateral mean lung dose were still significant in multivariate analysis, and they were included to build a predictive nomogram model for SRP. Conclusions As an early index that can reflect the tissue’s radiosensitivity visually, SARE can be used as a predictor for SRP in patients receiving thoracic radiation. And the nomogram containing SARE may be fully applied in future’s clinical work.