A predictive nomogram for trismus after radiotherapy for head and neck cancer

Background: The aim of this study is to develop a prediction model for trismus (maximal interincisal distance equal to or less than 35 mm) based on a multivariable analysis of dosimetric and clinical factors. Methods: The maximum interincisal opening (MIO) of hean and neck cancer (HNC) patients who under-went radiotherapy (RT) +/- concurrent chemotherapy with radical intent, was prospectively measured prior to RT (baseline) and 6 months post-RT. The outcome variable is trismus. The potential risk factors (clinical and dosimetric) were first screened by univariate analysis and then by multivariate analysis. At the end of this process, we used the features identified as relevant, to fit a logistic regression model and calculate the probability of observed trismus during the 6-month follow-up after RT. Results: One hundred and four consecutive patients were included (mean age 63 years, range 25-87), 68 males, 36 females. In the univariate analysis, the MIO at baseline, as an independent variable, and several Vdoses of different masticatory structures were found as significant. Additionally, using a bivariate model, a feature selection process was performed. Finally, we considered as best performing model the MIO at baseline and V42 at masseter muscles. The area under curve (AUC) of Receiver Operating Characteristic (ROC) curve value was 0.8255 (95% CI 0.74-0.9). The Hosmer and Lemeshow goodness-of-fit test, used to calibrate our model, was not-significant. Conclusions: A prediction nomogram was developed to assess trismus risk in planning process. An exter-nal validation of the model is required to apply it for current clinical use. (C) 2022 Elsevier B.V. All rights reserved. Radiotherapy and Oncology 173 (2022) 231-239

Automated summary

This study developed a prediction model for trismus based on a multivariable analysis of dosimetric and clinical factors. By measuring the maximum interincisal opening and dosimetry of masticatory structures, it is possible to accurately predict whether patients will develop trismus after radiotherapy.