Individualized Dynamic Prediction Model for Patient‐Reported Voice Quality in Early‐Stage Glottic Cancer
Maarten C. Dorr, Eleni‐Rosalina Andrinopoulou, Aniel Sewnaik, Diako Berzenji, Kira S. van Hof, Emilie A.C. Dronkers, Simone E. Bernard, Arta Hoesseini, Dimitirs Rizopoulos, Robert J. Baatenburg de Jong, Marinella P.J. Offerman- Otorhinolaryngology
- Surgery
Abstract
Objective
Early‐stage glottic cancer (ESGC) is a malignancy of the head and neck. Besides disease control, preservation and improvement of voice quality are essential. To enable expectation management and well‐informed decision‐making, patients should be sufficiently counseled with individualized information on expected voice quality. This study aims to develop an individualized dynamic prediction model for patient‐reported voice quality. This model should be able to provide individualized predictions at every time point from intake to the end of follow‐up.
Study Design
Longitudinal cohort study.
Setting
Tertiary cancer center.
Methods
Patients treated for ESGC were included in this study (N = 294). The Voice Handicap Index was obtained prospectively. The framework of mixed and joint models was used. The prognostic factors used are treatment, age, gender, comorbidity, performance score, smoking, T‐stage, and involvement of the anterior commissure. The overall performance of these models was assessed during an internal cross‐validation procedure and presentation of absolute errors using box plots.
Results
The mean age in this cohort was 67 years and 81.3% are male. Patients were treated with transoral CO2 laser microsurgery (57.8%), single vocal cord irradiation up to (24.5), or local radiotherapy (17.5%). The mean follow‐up was 43.4 months (SD 21.5). Including more measurements during prediction improves predictive performance. Including more clinical and demographic variables did not provide better predictions. Little differences in predictive performance between models were found.
Conclusion
We developed a dynamic individualized prediction model for patient‐reported voice quality. This model has the potential to empower patients and professionals in making well‐informed decisions and enables tailor‐made counseling.