Transverse skeletal proportionality in the prognostic evaluation of facemask therapy for skeletal class III malocclusion: a retrospective cephalometric study

BACKGROUND: This study aimed to identify prognostic skeletal factors associated with long-term stability following early orthopedic treatment in growing patients with skeletal Class III malocclusion by integrating lateral (LAT) and posteroanterior (PA) cephalometric analyses. MATERIALS AND METHODS: Forty-four growing patients with skeletal Class III malocclusion and maxillary retrusion treated with facemask therapy were retrospectively analyzed. Cephalometric records were obtained at pretreatment (T0), posttreatment (T1), and post-growth completion (T2). Patients were classified into favorable growth (FG) and unfavorable growth (UG) groups based on occlusal and skeletal outcomes at T2. Twenty lateral and fourteen posteroanterior cephalometric variables were assessed. Principal factor analysis with Varimax rotation was performed to derive latent skeletal components, which were subsequently evaluated using multiple linear regression to identify predictors of ANB at T2. A classification decision tree was constructed using T0 variables to classify long-term growth outcomes. RESULTS: Factor analysis yielded five principal variables (PV1-PV5), of which transverse maxillary structure (PV1), maxillomandibular transverse relationship (PV2), and vertical skeletal pattern (PV3) demonstrated significant associations with ANB at T2. A classification decision tree identified the transverse differential between mandibular and maxillary width (Mn. width - Mx. width) as the strongest initial discriminator of long-term prognosis, followed by AB-mandibular plane angle and Sum. The model achieved a classification accuracy of 93.2% in distinguishing favorable and unfavorable growth outcomes. CONCLUSIONS: Transverse skeletal proportionality plays a central role in determining the long-term stability of early orthopedic treatment in skeletal Class III malocclusion. Prognostic assessment may benefit from incorporating transverse, sagittal, and vertical skeletal dimensions including measurements from LAT and PA cephalograms, to improve individualized treatment planning and outcome prediction.