Sex-specific accuracy of various mixed dentition analysis methods : A population-based cross-sectional study

This study aimed to evaluate the accuracy of different mixed dentition analysis methods in predicting the mesiodistal diameters (MDD) of unerupted permanent canines and premolars (PCP) in a Turkish population and to determine the most reliable method for clinical application.

This research represents a retrospective, population-based cross-sectional study. Seven commonly used maxilla (Mx) and mandible (Md) unerupted PCP mesiodistal diameter prediction methods (Tanaka-Johnston, Moyers, Tränkmann, Legovic, Gross-Hasund, Bachmann, and Melgaço methods) were compared. The study included 120 Turkish children (60 males, 60 females) aged 13-16 years. MDD was measured using digital dental models. The predicted values were analyzed for accuracy by comparing them with the actual tooth diameters. Statistical analyses assessed the differences between the methods and their reliability in male and female subjects.

For the investigated Turkish population, the Gross-Hasund (Mx female: 0.32 ± 1.07 mm; Mx male: 0.22 ± 0.79 mm; Md female: 0.29 ± 0.79 mm; Md male: 0.55 ± 0.80 mm) and Bachmann methods (Mx female: 0.26 ± 1.04; Mx male: 0.24 ± 0.82 mm; Md female: 0.17 ± 0.72 mm; Md male: 0.52 ± 0.83 mm) provided the most accurate predictions, with minimal deviation from actual tooth sizes. The Tanaka-Johnston and Moyers methods tended to overestimate tooth sizes in males and underestimate them in females. The Tränkmann method showed the highest prediction error, particularly in males (Mx: 2.98 ± 1.40 mm; Md: 3.05 ± 0.78 mm). Sex differences were statistically significant in most methods, highlighting the necessity for population- and sex-specific adjustments in mixed dentition analyses.

The findings suggest that currently available prediction methods may not fully apply to the Turkish population without modifications. The Gross-Hasund and Bachmann methods were the most dependable, whereas the Tränkmann method showed significant discrepancies. Developing population-specific regression equations may improve the accuracy of mixed dentition analysis and enhance orthodontic treatment planning in Turkish individuals.