Predictive model for improvement of idiopathic sudden sensorineural hearing loss
Journal
Otology and Neurotology
Journal Volume
31
Journal Issue
3
Pages
385-393
Date Issued
2010
Author(s)
Chao T.-K.
Abstract
OBJECTIVE: To establish a predictive model for evaluating improvement in patients with idiopathic sudden sensorineural hearing loss (ISSHL). STUDY DESIGN: Bayesian cure rate model. SETTING: Tertiary referral center. PATIENTS: Two hundred patients whose conditions were diagnosed as ISSHL from January 2001 to April 2007 were enrolled to build a model and to train relevant parameters for prediction. MAIN OUTCOME MEASURES: The time to improvement and potential predictive factors were collected for analysis. Established factors and significant variables in the univariate analysis were included in the final model. A Bayesian approach with the WinBUGS program was applied to predict the median and 95% confidence intervals (CIs) for the time to improvement, long-term probability of improvement, and improvement probabilities at specific days. RESULTS: The significant predictors in the final model include distortion product otoacoustic emission, auditory brainstem response, vestibular evoked myogenic potential, and audiometric types. The overall results predicted by the different combinations of covariates were summarized and organized in an Access program file that is convenient for clinical application. The results of area under the receiver operating characteristic curves at the 7th, 14th, and 30th days were 0.709 (95% CI, 0.692-0.717), 0.752 (95% CI, 0.737-0.753), and 0.807 (95% CI, 0.788-0.811), respectively. It showed that predictive validity, particularly at 1 month or so, is satisfactory. CONCLUSION: By using the cure rate model under the context of a Bayesian survival analysis, we first identified auditory objective factors as significant predictors of improvement of ISSHL patients and further predicted the time to improvement with these correlates. The model showed a satisfactory predictive validity, particularly for 1-month individual prediction, which prompted one to make an individual prediction with an available Access program.
SDGs
Type
journal article