title: Prediction of periodontal disease from multiple self-reported items in a German practice-based sample.
abstract: BACKGROUND
  Ascertainment of periodontal disease using self-reported measures would be useful for large epidemiologic studies. This study evaluates whether a combination of self-reported items with established risk factors in a predictive model can assess periodontal disease accurately.
  
  
  METHODS
  Responses of 246 subjects to a detailed questionnaire were compared to their periodontal disease history as assessed from radiographs. Multiple regression modeling was used to construct predictive models using self-reported items and established risk factors.
  
  
  RESULTS
  Depending on the definition of gold-standard periodontal disease, two or three self-reported items were selected for the predictive models, in addition to age, gender, and smoking. Self-reported tooth mobility was associated strongly with periodontal disease independent of other risk factors and was selected in all models. For dichotomous definitions of periodontal disease, discrimination of predictive logistic regression models was good with areas under the receiver operating characteristic curve >0.80. Assessment of periodontal disease history based on extreme quantiles of model-predicted values yielded high sensitivity and specificity.
  
  
  CONCLUSIONS
  The combination of several self-reported items may be useful for ascertainment of periodontal disease in epidemiologic studies.
authors.affiliation: Department of Health Policy and Health Services Research, Boston University Goldman School of Dental Medicine, Boston, MA, USA. tdietric@bu.edu
authors.forename: T
authors.initials: T
authors.lastname: Dietrich
authors.forename: U
authors.initials: U
authors.lastname: Stosch
authors.forename: D
authors.initials: D
authors.lastname: Dietrich
authors.forename: W
authors.initials: W
authors.lastname: Kaiser
authors.forename: J-P
authors.initials: JP
authors.lastname: Bernimoulin
authors.forename: K
authors.initials: K
authors.lastname: Joshipura
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D016301:Alveolar Bone Loss / Q000453:epidemiology; D005260:Female; D005544:Forecasting; D005858:Germany / Q000453:epidemiology; D006801:Humans; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D010510:Periodontal Diseases / Q000453:epidemiology*; D011862:Radiography, Panoramic / Q000706:statistics & numerical data; D012307:Risk Factors; D012680:Sensitivity and Specificity; D012737:Sex Factors; D016037:Single-Blind Method; D012907:Smoking / Q000453:epidemiology; D011795:Surveys and Questionnaires; D014086:Tooth Mobility / Q000453:epidemiology