AIM: Mixed dentition analysis allows the prediction of the tooth width of non erupted permanent canines and premolars (SPCP). It is an essential factor in treatment planning since it could predict a tooth-size to arch-length discrepancy. The aim of this study was to determine which group of permanent teeth presented the best prediction capability for the width sums of the unerupted canine and premolars in an Italian sample. MATERIALS AND METHODS: A total of 150 subjects with complete permanent dentition were selected. Their dental casts were measured to 0.01 mm with a digital caliper. Pearson correlation and T-test were used for the statistical analysis. RESULTS/STATISTICS: The combination of the sums of the four lower incisors and the first upper molars showed the best prediction capability for the SPCP in the Italian sample. Moreover new regression equations were formulated including sex and arch as additional predictor variables. In 80% of the cases estimated differences between the predicted and the actual values were smaller than 1 mm. CONCLUSION: It can be concluded that the new regression equations proposed seemed to show good accuracy.
AIM: Mixed dentition analysis allows the prediction of the tooth width of non erupted permanent canines and premolars (SPCP). It is an essential factor in treatment planning since it could predict a tooth-size to arch-length discrepancy. The aim of this study was to determine which group of permanent teeth presented the best prediction capability for the width sums of the unerupted canine and premolars in an Italian sample. MATERIALS AND METHODS: A total of 150 subjects with complete permanent dentition were selected. Their dental casts were measured to 0.01 mm with a digital caliper. Pearson correlation and T-test were used for the statistical analysis. RESULTS/STATISTICS: The combination of the sums of the four lower incisors and the first upper molars showed the best prediction capability for the SPCP in the Italian sample. Moreover new regression equations were formulated including sex and arch as additional predictor variables. In 80% of the cases estimated differences between the predicted and the actual values were smaller than 1 mm. CONCLUSION: It can be concluded that the new regression equations proposed seemed to show good accuracy.