Salivary IGF-1 and Alkaline Phosphatase-Based Modeling for Skeletal Maturity Prediction in Orthodontic Patients - Sookhakian, Asma; Zahed, Maryam; Pakshir, Hamidreza; Ajami, Shabnam (BioMed research international, 2022)
Background/Objectives. The correct identification of the different stages of skeletal maturity is a crucial issue in orthodontic diagnosis and treatment planning decisions. The hand-wrist analysis and cervical vertebral maturation (CVM) methods are the most frequently employed methods for determining the stage of skeletal maturity in orthodontics. Since these methods require X-ray exposure, a new objective and less invasive method is needed. The aim of this study was to develop other models for prediction of cervical vertebral maturational stages and also growth phases using chronological age (CA), salivary insulin-like growth factor-1 (IGF-1), and alkaline phosphatase (ALP). Subjects and Methods. In this cross-sectional study, 55 healthy subjects in the age range of 7 to 20 years were included. Their skeletal maturity was assessed through Baccetti’s 6-stage CVM method. In addition, their salivary IGF-1 level, salivary ALP level, and CA were determined. Multinomial logistic regressions were utilized to predict the cervical stage and also growth phase based on CA, salivary IGF-1, and salivary ALP in 7 different models. Results. A strong positive correlation was found between CA and cervical stages (r=0.836, P<0.001). Based on the regression model analysis, the model which combined IGF-1, ALP, and CA provided the best prediction at P<0.001 with McFadden’s pseudo R2 value of 0.552 for cervical stage prediction and 0.646 for growth phase prediction. In particular, its predictive ability for the prepubertal, pubertal, and postpubertal growth phases was 95%, 80%, and 90%, respectively. Conclusions. A new model with the combination of salivary IGF-1 and ALP with CA can be used as a less invasive method to determine the cervical stage and also growth phase with high predictive ability in healthy subjects.