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Statistics Data were analyzed using SPSS version 22. Correlation analyses [http://www.selleckchem.com/products/obeticholic-acid.html Obeticholic Acid chemical structure] were performed to explore the relationship between OHIP and other variables including oral dryness and CARS. Because mood state was related to oral dryness in previous studies, [8,9,11] partial correlations were calculated between OHIP, oral dryness, and CARS to control for the effect of tension�Canxiety and depression�Cdejection on POMS-B. Cluster analysis was conducted to clarify the subgroups of patients based on the responses on the CARS and the symptom oral dryness. To equalize the influence of variables with different scale lengths on the cluster solution, scores from CARS and the oral dryness numerical rating scale were standardized on their ranges, then used in the cluster analysis. Variables chosen for cluster modeling were selected on the basis of correlational analysis with OHIP. An agglomerative, hierarchical cluster analysis was performed with Euclidean distances used in the proximities matrix and Ward��s method used as the clustering method. Cuts made at points of large change between successive fusion levels were used to define likely cluster boundaries. To clarify the characteristics of each cluster based on oral dryness, CARS, OHIP, age and sex, one-way analysis of variance (ANOVA) and chi-square test were conducted. Results The average oral dryness score was 4.59?��?2.43 on the 11-point scale. The average OHIP-14 score was 14.33?��?11.07. Correlation analyses were performed to explore the relationship between OHIP-14 score and each variable. The OHIP-14 score was significantly correlated [http://en.wikipedia.org/wiki/CDK9 CDK9] [http://www.selleckchem.com/products/s-gsk1349572.html this website] with oral dryness (r?=?0.57, p?