BackgroundMany studies have reported excess cancer mortality in patients with mental illness. However, scant studies evaluated the differences in cancer treatment and its impact on survival rates among mentally ill patients. Oral cancer is one of the ten most common cancers in the world. We investigated differences in treatment type and survival rates between oral cancer patients with mental illness and without mental illness.MethodsUsing the National Health Insurance (NHI) database, we compared the type of treatment and survival rates in 16687 oral cancer patients from 2002 to 2006. The utilization rate of surgery for oral cancer was compared between patients with mental illness and without mental illness using logistic regression. The Cox proportional hazards model was used for survival analysis.ResultsOral cancer patients with mental disorder conferred a grave prognosis, compared with patients without mental illness (hazard ratios [HR] = 1.58; 95% confidence interval [CI] = 1.30–1.93; P<0.001). After adjusting for patients’ characteristics and hospital characteristics, patients with mental illness were less likely to receive surgery with or without adjuvant therapy (odds ratio [OR] = 0.47; 95% CI = 0.34–0.65; P<0.001). In multivariate analysis, oral cancer patients with mental illness carried a 1.58-times risk of death (95% CI = 1.30–1.93; P<0.001).ConclusionsOral cancer patients with mental illness were less likely to undergo surgery with or without adjuvant therapy than those without mental illness. Patients with mental illness have a poor prognosis compared to those without mental illness. To reduce disparities in physical health, public health strategies and welfare policies must continue to focus on this vulnerable group.

The purpose of this study was to design a statistical classification system of audiogram shapes in order to improve and integrate shape recognition across clinical settings. The study included 1633 adult subjects with normal hearing or symmetric sensorineural hearing impairment who underwent pure-tone audiometry between July 2007 and December 2008. K-means cluster analysis was employed to categorize audiometric shapes. Eleven audiogram shapes were identified: rising, flat, peaked 8-kHz dip, 4-kHz dip, 8-kHz dip, mild sloping, severe 8-kHz dip, sloping, abrupt loss, severe sloping, and profound abrupt loss. By using the classification system and nomenclature identified for audiogram shapes as outlined in this study, errors based on personal experiences can be reduced and a consistency can be developed across clinics.

Higher rates of complications and level of critical care were needed in patients with alcohol-induced mental disorder after head and neck microsurgical reconstructions. Treatment requires a multidisciplinary approach, rapid diagnosis, and intensive medical care.