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.
| Original language | English |
|---|---|
| Article number | 584756 |
| Journal | Frontiers in Oncology |
| Volume | 10 |
| DOIs | |
| State | Published - Oct 15 2020 |
Bibliographical note
Publisher Copyright:© Copyright © 2020 Meng, Luo, Wang, Zhou, Zhou, Tang, Hou, Kong and Yang.
Funding
This work was funded by the National Natural Science Foundation of China (81874221), and Taizhou Science and Technology Bureau (20ywa09 and 1802ky07).
| Funders | Funder number |
|---|---|
| National Natural Science Foundation of China (NSFC) | 81874221 |
| Taizhou Municipal Science and Technology Bureau | 1802ky07, 20ywa09 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- dosimetric parameters
- intensity modulated radiotherapy (IMRT)
- lung cancer
- prediction model
- radiation pneumonitis (RP)
ASJC Scopus subject areas
- Oncology
- Cancer Research
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