Ting-Shi Su1, Ren Luo2, Ping Liang3, Tao Cheng4, Ying Zhou5, Yong Huang5. 1. Department of Radiation Oncology, Affiliated Tumor Hospital of Guangxi Medical University, Nanning, China; Department of Radiation Oncology, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China. Electronic address: sutingshi@163.com. 2. Department of Radiation Oncology, University Hospital Freiburg, Germany. 3. Department of Radiation Oncology, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China; Cyberknife Center, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China. 4. Cyberknife Center, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China. 5. Department of Radiation Oncology, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China.
Abstract
PURPOSE: To build and validate multivariate normal tissue complication probability (NTCP) models for radiation-induced hepatic toxicity (RIHT) after stereotactic body radiation therapy (SBRT). METHODS: Eighty-five patients with hepatocellular carcinoma (HCC) in a phase II clinical trial were enroled. A progression of at least 1 or 2 points in the Child-Pugh (CP) score post-SBRT was classified as RIHT (≥1 or ≥2). NTCP models for RIHT (≥1 or ≥2) were developed using logistic regression. Nomograms for each model were formulated. The cut-off point of each independent dosimetric risk factor was obtained using receiver-operating characteristic (ROC) analysis. We used an independent cohort (101 patients) for model validation. RESULTS: Twenty (23.5%) and 12 (14.2%) patients experienced RIHT (≥1) and RIHT (≥2), respectively. V15, VS10, and pretreatment CP (pre-CP) were the optimal predictors for RIHT (≥1 and ≥2) modelling. V15 ≤33.1% and VS10 ≥416.2 mL for RIHT (≥1), and V15 ≤21.5% and VS10 ≥621.8 mL for RIHT (≥2), were the cut-off points. Four NTCP models and their nomograms were generated. These models and nomograms showed good prediction performance (area under the curve (AUC), 0.83-0.89). Our NTCP model (RIHT ≥2) based on V15 plus pre-CP performed well (AUC = 0.78) in a validation cohort. CONCLUSION: V15, VS10, and pre-CP are crucial predictors for RIHT (≥1 and ≥2). Our NTCP models and nomograms were conducive to obtain individual constraints for patients with HCC. REGISTRATION NUMBER: ChiCTR-IIC-16008233.
PURPOSE: To build and validate multivariate normal tissue complication probability (NTCP) models for radiation-induced hepatic toxicity (RIHT) after stereotactic body radiation therapy (SBRT). METHODS: Eighty-five patients with hepatocellular carcinoma (HCC) in a phase II clinical trial were enroled. A progression of at least 1 or 2 points in the Child-Pugh (CP) score post-SBRT was classified as RIHT (≥1 or ≥2). NTCP models for RIHT (≥1 or ≥2) were developed using logistic regression. Nomograms for each model were formulated. The cut-off point of each independent dosimetric risk factor was obtained using receiver-operating characteristic (ROC) analysis. We used an independent cohort (101 patients) for model validation. RESULTS: Twenty (23.5%) and 12 (14.2%) patients experienced RIHT (≥1) and RIHT (≥2), respectively. V15, VS10, and pretreatment CP (pre-CP) were the optimal predictors for RIHT (≥1 and ≥2) modelling. V15 ≤33.1% and VS10 ≥416.2 mL for RIHT (≥1), and V15 ≤21.5% and VS10 ≥621.8 mL for RIHT (≥2), were the cut-off points. Four NTCP models and their nomograms were generated. These models and nomograms showed good prediction performance (area under the curve (AUC), 0.83-0.89). Our NTCP model (RIHT ≥2) based on V15 plus pre-CP performed well (AUC = 0.78) in a validation cohort. CONCLUSION: V15, VS10, and pre-CP are crucial predictors for RIHT (≥1 and ≥2). Our NTCP models and nomograms were conducive to obtain individual constraints for patients with HCC. REGISTRATION NUMBER: ChiCTR-IIC-16008233.
Authors: Jennifer Pursley; Issam El Naqa; Nina N Sanford; Bridget Noe; Jennifer Y Wo; Christine E Eyler; Matthew Hwang; Kristy K Brock; Beow Y Yeap; John A Wolfgang; Theodore S Hong; Clemens Grassberger Journal: Int J Radiat Oncol Biol Phys Date: 2020-04-27 Impact factor: 7.038
Authors: Stephanie K Schaub; Pehr E Hartvigson; Michael I Lock; Morten Høyer; Thomas B Brunner; Higinia R Cardenes; Laura A Dawson; Edward Y Kim; Nina A Mayr; Simon S Lo; Smith Apisarnthanarax Journal: Technol Cancer Res Treat Date: 2018-01-01