Literature DB >> 28502238

Parotid gland mean dose as a xerostomia predictor in low-dose domains.

Hubert Szymon Gabryś1,2, Florian Buettner3, Florian Sterzing2,4,5, Henrik Hauswald2,4,5, Mark Bangert1,2.   

Abstract

PURPOSE: 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.
MATERIAL AND METHODS: 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.
RESULTS: 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.
CONCLUSIONS: 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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Year:  2017        PMID: 28502238     DOI: 10.1080/0284186X.2017.1324209

Source DB:  PubMed          Journal:  Acta Oncol        ISSN: 0284-186X            Impact factor:   4.089


  7 in total

Review 1.  Head and Neck Cancer Adaptive Radiation Therapy (ART): Conceptual Considerations for the Informed Clinician.

Authors:  Jolien Heukelom; Clifton David Fuller
Journal:  Semin Radiat Oncol       Date:  2019-07       Impact factor: 5.934

2.  A prediction model for xerostomia in locoregionally advanced nasopharyngeal carcinoma patients receiving radical radiotherapy.

Authors:  Minying Li; Jingjing Zhang; Yawen Zha; Yani Li; Bingshuang Hu; Siming Zheng; Jiaxiong Zhou
Journal:  BMC Oral Health       Date:  2022-06-17       Impact factor: 3.747

3.  Early Changes in Serial CBCT-Measured Parotid Gland Biomarkers Predict Chronic Xerostomia After Head and Neck Radiation Therapy.

Authors:  Benjamin S Rosen; Peter G Hawkins; Daniel F Polan; James M Balter; Kristy K Brock; Justin D Kamp; Christina M Lockhart; Avraham Eisbruch; Michelle L Mierzwa; Randall K Ten Haken; Issam El Naqa
Journal:  Int J Radiat Oncol Biol Phys       Date:  2018-07-10       Impact factor: 7.038

4.  Incorporation of Dosimetric Gradients and Parotid Gland Migration Into Xerostomia Prediction.

Authors:  Rosario Astaburuaga; Hubert S Gabryś; Beatriz Sánchez-Nieto; Ralf O Floca; Sebastian Klüter; Kai Schubert; Henrik Hauswald; Mark Bangert
Journal:  Front Oncol       Date:  2019-07-31       Impact factor: 6.244

5.  A Risk Prediction Model by LASSO for Radiation-Induced Xerostomia in Patients With Nasopharyngeal Carcinoma Treated With Comprehensive Salivary Gland-Sparing Helical Tomotherapy Technique.

Authors:  Feng Teng; Wenjun Fan; Yanrong Luo; Shouping Xu; Hanshun Gong; Ruigang Ge; Xinxin Zhang; Xiaoning Wang; Lin Ma
Journal:  Front Oncol       Date:  2021-02-26       Impact factor: 6.244

6.  Design and Selection of Machine Learning Methods Using Radiomics and Dosiomics for Normal Tissue Complication Probability Modeling of Xerostomia.

Authors:  Hubert S Gabryś; Florian Buettner; Florian Sterzing; Henrik Hauswald; Mark Bangert
Journal:  Front Oncol       Date:  2018-03-05       Impact factor: 6.244

7.  Can the Risk of Dysphagia in Head and Neck Radiation Therapy Be Predicted by an Automated Transit Fluence Monitoring Process During Treatment? A First Comparative Study of Patient Reported Quality of Life and the Fluence-Based Decision Support Metric.

Authors:  Seng Boh Lim; Nancy Lee; Kaveh Zakeri; Peter Greer; Todsaporn Fuangrod; Frederick Coffman; Laura Cerviño; D Michael Lovelock
Journal:  Technol Cancer Res Treat       Date:  2021 Jan-Dec
  7 in total

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