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Prevalence and prediction of trismus in patients with head and neck cancer: A cross-sectional study.


ABSTRACT:

Background

Trismus occurs frequently in patients with head and neck cancer. Determining the prevalence and associated factors of trismus would enable prediction of the risk of trismus for future patients.

Methods

Based on maximal mouth opening measurements, we determined the prevalence of trismus in 730 patients with head and neck cancer. Associated factors for trismus were analyzed using univariate analyses and multivariate logistic regression analyses. Based on the regression model, a calculation tool to predict trismus was made.

Results

Prevalence of trismus was 23.6%. Factors associated with trismus were: advanced age; partial or full dentition; tumors located at the maxilla; mandible; cheek; major salivary glands; oropharynx; an unknown primary; a free soft tissue transfer after surgery; reirradiation; and chemotherapy.

Conclusion

About one-fourth of patients with head and neck cancer develop trismus. Based on prevalence and associated factors of trismus, a simple calculation tool predicts the risk of trismus in these patients.

SUBMITTER: van der Geer SJ 

PROVIDER: S-EPMC6590501 | biostudies-literature | 2019 Jan

REPOSITORIES: biostudies-literature

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Publications

Prevalence and prediction of trismus in patients with head and neck cancer: A cross-sectional study.

van der Geer Sarah J SJ   van Rijn Phillip V PV   Kamstra Jolanda I JI   Langendijk Johannes A JA   van der Laan Bernard F A M BFAM   Roodenburg Jan L N JLN   Dijkstra Pieter U PU  

Head & neck 20181218 1


<h4>Background</h4>Trismus occurs frequently in patients with head and neck cancer. Determining the prevalence and associated factors of trismus would enable prediction of the risk of trismus for future patients.<h4>Methods</h4>Based on maximal mouth opening measurements, we determined the prevalence of trismus in 730 patients with head and neck cancer. Associated factors for trismus were analyzed using univariate analyses and multivariate logistic regression analyses. Based on the regression mo  ...[more]

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