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| Home > Publications database > Parotid gland mean dose as a xerostomia predictor in low-dose domains. |
| Journal Article | DKFZ-2017-06210 |
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2017
Taylor & Francis Group
Abingdon
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Please use a persistent id in citations: doi:10.1080/0284186X.2017.1324209
Abstract: Xerostomia is a common side effect of radiotherapy resulting from excessive irradiation of salivary glands. Typically, xerostomia is modeled by the mean dose-response characteristic of parotid glands and prevented by mean dose constraints to either contralateral or both parotid glands. The aim of this study was to investigate whether normal tissue complication probability (NTCP) models based on the mean radiation dose to parotid glands are suitable for the prediction of xerostomia in a highly conformal low-dose regime of modern intensity-modulated radiotherapy (IMRT) techniques.We present a retrospective analysis of 153 head and neck cancer patients treated with radiotherapy. The Lyman Kutcher Burman (LKB) model was used to evaluate predictive power of the parotid gland mean dose with respect to xerostomia at 6 and 12 months after the treatment. The predictive performance of the model was evaluated by receiver operating characteristic (ROC) curves and precision-recall (PR) curves.Average mean doses to ipsilateral and contralateral parotid glands were 25.4 Gy and 18.7 Gy, respectively. QUANTEC constraints were met in 74% of patients. Mild to severe (G1+) xerostomia prevalence at both 6 and 12 months was 67%. Moderate to severe (G2+) xerostomia prevalence at 6 and 12 months was 20% and 15%, respectively. G1 + xerostomia was predicted reasonably well with area under the ROC curve ranging from 0.69 to 0.76. The LKB model failed to provide reliable G2 + xerostomia predictions at both time points.Reduction of the mean dose to parotid glands below QUANTEC guidelines resulted in low G2 + xerostomia rates. In this dose domain, the mean dose models predicted G1 + xerostomia fairly well, however, failed to recognize patients at risk of G2 + xerostomia. There is a need for the development of more flexible models able to capture complexity of dose response in this dose regime.
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