OBJECTIVE: To evaluate whether the diagnostic accuracy of a novel periodontal prediction model (PPM) for identification of adults with diabetes varies according to participants' characteristics . BASIC RESEARCH
DESIGN: The study was carried out among 250 adults attending primary care clinics in Riyadh (Saudi Arabia). The study adopted a case-control approach, where diabetes status was first ascertained, and data collection carried out afterwards using questionnaires and periodontal examinations . Variations in the performance of the PPM by demographic (sex and age), socioeconomic (education) and behavioural factors (smoking status and last dental visit) were evaluated using receiver-operating characteristic (ROC) regression .
RESULTS: The PPM including 3 periodontal parameters (missing teeth, percentage of sites with pocket depth ≥6mm and mean pocket depth) had an area under the ROC curve (AUC) of 0.69 (95% Confidence Interval : 0.61-0.78), which dropped to 0.64 (95% CI : 0.53-0.75) after adjustment for covariates . Larger variations in performance were found by participants' sex, age and education, but not by smoking status or last dental visit . The PPM performed better among male (adjusted AUC : 0.76; 95% CI : 0.53 to 0.99), younger (0.67; 95% CI : 0.50 to 0.84) and less educated participants (0.76; 95% CI : 0.60 , 0.92).
CONCLUSIONS: The diagnostic accuracy of a novel periodontal prediction model to identify individuals with diabetes varied according to participants' characteristics . This study highlights the importance of adjusting for covariates on studies of diagnostic accuracy.