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A prospective cohort study of hepatic toxicity after stereotactic body radiation therapy for hepatocellular carcinoma.
Su, Ting-Shi; Luo, Ren; Liang, Ping; Cheng, Tao; Zhou, Ying; Huang, Yong.
Afiliação
  • Su TS; 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.
  • Luo R; Department of Radiation Oncology, University Hospital Freiburg, Germany.
  • Liang P; 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.
  • Cheng T; Cyberknife Center, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China.
  • Zhou Y; Department of Radiation Oncology, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China.
  • Huang Y; Department of Radiation Oncology, Rui Kang Hospital, Guangxi Traditional Chinese Medical University, Nanning, China.
Radiother Oncol ; 129(1): 136-142, 2018 10.
Article em En | MEDLINE | ID: mdl-29548558
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.
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Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiocirurgia / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: Radiother Oncol Ano de publicação: 2018 Tipo de documento: Article

Texto completo: 1 Coleções: 01-internacional Base de dados: MEDLINE Assunto principal: Radiocirurgia / Carcinoma Hepatocelular / Neoplasias Hepáticas Tipo de estudo: Etiology_studies / Observational_studies / Prognostic_studies / Risk_factors_studies Limite: Adult / Aged / Aged80 / Female / Humans / Male / Middle aged Idioma: En Revista: Radiother Oncol Ano de publicação: 2018 Tipo de documento: Article