Predicting changes in mandibular length and total anterior facial height using IGF-1, cervical stage, skeletal classification, and gender.

Background: The purpose of this study was to predict the annual growth rate of the mandible and total anterior facial height using IGF-1 levels together with cervical stage, skeletal classification, and gender.

Methods: Twenty-five orthodontic patients (12 females and 13 males) had their cervical stages, blood-spot IGF-1 levels, and cephalometric parameters measured at 1-year intervals. The number of years each patient was followed up varied between 1 and 5 years resulting in 43 12-month intervals collected from 77 observations. Descriptive, bivariate, and regression analyses were used to analyze this data.

Results: The linear regression model for predicting the annual mandibular growth rate was significant at p < 0.01 with an R-square value of 0.52. We found that the average IGF-1 level for the interval, the change in IGF-1 level, and the presence of a skeletal class III pattern were statistically significant predictors of mandibular growth. The regression model for predicting the annual change in anterior facial height was significant at p < 0.01 with an R-square value of 0.42. We found that the change in IGF-1 level was the only statistically significant predictor of this outcome.

Conclusions: The proposed method which combines IGF-1 levels with information that is readily available to clinicians can be used to predict the timing and intensity of the growth spurt. These factors together explain more of the observed individual variation in growth rate than any of the factors used in isolation.