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Intermediate Dose-Volume Parameters, Not Low-Dose Bath, Is Superior to Predict Radiation Pneumonitis for Lung Cancer Treated With Intensity-Modulated Radiotherapy.
Meng, Yinnan; Luo, Wei; Wang, Wei; Zhou, Chao; Zhou, Suna; Tang, Xingni; Hou, Liqiao; Kong, Feng-Ming Spring; Yang, Haihua.
Afiliação
  • Meng Y; Laboratory of Cellular and Molecular Radiation Oncology, Radiation Oncology Institute of Enze Medical Health Academy, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Luo W; Department of Radiation Oncology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Wang W; Department of Radiation Medicine, University of Kentucky, Lexington, KY, United States.
  • Zhou C; Laboratory of Cellular and Molecular Radiation Oncology, Radiation Oncology Institute of Enze Medical Health Academy, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Zhou S; Department of Radiation Oncology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Tang X; Laboratory of Cellular and Molecular Radiation Oncology, Radiation Oncology Institute of Enze Medical Health Academy, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Hou L; Department of Radiation Oncology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Kong FS; Laboratory of Cellular and Molecular Radiation Oncology, Radiation Oncology Institute of Enze Medical Health Academy, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
  • Yang H; Department of Radiation Oncology, Affiliated Taizhou Hospital of Wenzhou Medical University, Taizhou, China.
Front Oncol ; 10: 584756, 2020.
Article em En | MEDLINE | ID: mdl-33178612
ABSTRACT

PURPOSE:

Although intensity-modulated radiotherapy (IMRT) is now a preferred option for conventionally fractionated RT in lung cancer, the commonly used cutoff values of the dosimetric constraints are still mainly derived from the data using three-dimensional conformal radiotherapy (3D-CRT). We aimed to compare the prediction performance among different dosimetric parameters for acute radiation pneumonitis (RP) in patients with lung cancer received IMRT.

METHODS:

A total of 236 patients treated with IMRT were retrospectively reviewed in two independent groups of lung cancer from January 2014 to August 2018. The primary endpoint was grade 2 or higher acute RP (RP2). Dose metrics were generated from the bilateral lung volume outside GTV (VdoseG) and PTV (VdoseP). The associations of RP2 with clinical variables, dose-volume parameters and mean lung dose (MLD) were analyzed by univariate and multivariate logistic regression. The power of discrimination among each predictor was assessed by employing the bootstrapped area under the receiver operating characteristic curve (AUC), net reclassification improvement (NRI), and the integrated discrimination improvement (IDI).

RESULTS:

Thirty-four (14.4%) out of 236 patients developed acute RP2 after the end of IMRT. The clinical parameters were identified as less important predictors for RP2 based on univariate and multivariate analysis. In both studied groups, the significance of association was more convincing in V20P, V30P, and MLDP (smaller Ps) than V5G and V5P. The largest bootstrapped AUC was identified for the V30P. We found a trend of better discriminating performance for the V20P and V30P, and MLDP than the V5G and V5P according to the higher values in AUC, IDI, and NRI analysis. To limit RP2 incidence less than 20%, the V30P cutoff was 14.5%.

CONCLUSIONS:

This study identified the intermediate dose-volume parameters V20P and V30P with better prediction performance for acute RP2 than low-dose metrics V5G and V5P. Among all studied predictors, the V30P had the best discriminating power, and should be considered as a supplement to the traditional dose constraints in lung cancer treated with IMRT.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2020 Tipo de documento: Article