Physics and Imaging in Radiation Oncology (Oct 2022)

Independent validation of a dysphagia dose response model for the selection of head and neck cancer patients to proton therapy

  • Petros Kalendralis,
  • Matthijs Sloep,
  • Nibin Moni George,
  • Jasper Snel,
  • Joeri Veugen,
  • Frank Hoebers,
  • Frederik Wesseling,
  • Mirko Unipan,
  • Martijn Veening,
  • Johannes A. Langendijk,
  • Andre Dekker,
  • Johan van Soest,
  • Rianne Fijten

Journal volume & issue
Vol. 24
pp. 47 – 52

Abstract

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Background and purpose: The model based approach involves the use of normal tissue complication models for selection of head and neck cancer patients to proton therapy. Our goal was to validate the clinical utility of the related dysphagia model using an independent patient cohort. Materials and Methods: A dataset of 277 head and neck cancer (pharynx and larynx) patients treated with (chemo)radiotherapy between 2019 and 2021 was acquired. For the evaluation of the model discrimination we used statistical metrics such as the sensitivity, specificity and the area under the receiver operating characteristic curve. After the validation we evaluated if the dysphagia model can be improved using the closed testing procedure, the Brier and the Hosmer-Lemeshow score. Results: The performance of the original normal tissue complication probability model for dysphagia grade II-IV at 6 months was good (AUC = 0.80). According to the graphical calibration assessment, the original model showed underestimated dysphagia risk predictions. The closed testing procedure indicated that the model had to be updated and selected a revised model with new predictor coefficients as an optimal model. The revised model had also satisfactory discrimination (AUC = 0.83) with improved calibration. Conclusion: The validation of the normal tissue complication probability model for grade II-IV dysphagia was successful in our independent validation cohort. However, the closed testing procedure indicated that the model should be updated with new coefficients.