Alessandro Villa1,2, Francesco Nordio3, Anita Gohel4. 1. Division of Oral Medicine and Dentistry, Brigham and Women's Hospital, Boston, MA, USA. avilla@partners.org. 2. Department of Oral Medicine, Infection and Immunity, Harvard School of Dental Medicine, Boston, MA, USA. avilla@partners.org. 3. Department of Environmental Health-Exposure, Epidemiology and Risk Program, Harvard School of Public Health, Boston, MA, USA. 4. Department of General Dentistry, Boston University Henry M. Goldman School of Dental Medicine, Boston, MA, USA.
Abstract
OBJECTIVE: We investigated the prevalence of xerostomia in dental patients and built a xerostomia risk prediction model by incorporating a wide range of risk factors. MATERIALS AND METHODS: Socio-demographic data, past medical history, self-reported dry mouth and related symptoms were collected retrospectively from January 2010 to September 2013 for all new dental patients. A logistic regression framework was used to build a risk prediction model for xerostomia. External validation was performed using an independent data set to test the prediction power. RESULTS: A total of 12 682 patients were included in this analysis (54.3%, females). Xerostomia was reported by 12.2% of patients. The proportion of people reporting xerostomia was higher among those who were taking more medications (OR = 1.11, 95% CI = 1.08-1.13) or recreational drug users (OR = 1.4, 95% CI = 1.1-1.9). Rheumatic diseases (OR = 2.17, 95% CI = 1.88-2.51), psychiatric diseases (OR = 2.34, 95% CI = 2.05-2.68), eating disorders (OR = 2.28, 95% CI = 1.55-3.36) and radiotherapy (OR = 2.00, 95% CI = 1.43-2.80) were good predictors of xerostomia. For the test model performance, the ROC-AUC was 0.816 and in the external validation sample, the ROC-AUC was 0.799. CONCLUSION: The xerostomia risk prediction model had high accuracy and discriminated between high- and low-risk individuals. Clinicians could use this model to identify the classes of medications and systemic diseases associated with xerostomia.
OBJECTIVE: We investigated the prevalence of xerostomia in dental patients and built a xerostomia risk prediction model by incorporating a wide range of risk factors. MATERIALS AND METHODS: Socio-demographic data, past medical history, self-reported dry mouth and related symptoms were collected retrospectively from January 2010 to September 2013 for all new dental patients. A logistic regression framework was used to build a risk prediction model for xerostomia. External validation was performed using an independent data set to test the prediction power. RESULTS: A total of 12 682 patients were included in this analysis (54.3%, females). Xerostomia was reported by 12.2% of patients. The proportion of people reporting xerostomia was higher among those who were taking more medications (OR = 1.11, 95% CI = 1.08-1.13) or recreational drug users (OR = 1.4, 95% CI = 1.1-1.9). Rheumatic diseases (OR = 2.17, 95% CI = 1.88-2.51), psychiatric diseases (OR = 2.34, 95% CI = 2.05-2.68), eating disorders (OR = 2.28, 95% CI = 1.55-3.36) and radiotherapy (OR = 2.00, 95% CI = 1.43-2.80) were good predictors of xerostomia. For the test model performance, the ROC-AUC was 0.816 and in the external validation sample, the ROC-AUC was 0.799. CONCLUSION: The xerostomia risk prediction model had high accuracy and discriminated between high- and low-risk individuals. Clinicians could use this model to identify the classes of medications and systemic diseases associated with xerostomia.
Authors: Eva Onjukka; Claes Mercke; Einar Björgvinsson; Anna Embring; Anders Berglund; Gabriella Alexandersson von Döbeln; Signe Friesland; Giovanna Gagliardi; Clara Lenneby Helleday; Helena Sjödin; Ingmar Lax Journal: Front Oncol Date: 2020-08-14 Impact factor: 6.244
Authors: Ida G Fostad; Jon R Eidet; Tor P Utheim; Sten Ræder; Neil S Lagali; Edvard B Messelt; Darlene A Dartt Journal: PLoS One Date: 2016-05-05 Impact factor: 3.240