Nolla 法推断中国北方汉族儿童年龄的准确性

Objective: To study the accuracy of Nolla method for age estimation of Northern Chinese Han children aged between 5.00 and 14.99 years based on original transformation tables and multiple regression model. Methods: A total of 2 000 orthopantomographs (OPGs) were collected from the Hospital of Stomatology, Xi'an Jiaotong University, including 1 000 males and 1 000 females. Development stage of 7 left mandibular permanent teeth (except third molars) was assessed based on Nolla method, then age estimation was conducted through transformation tables and multiple regression model, respectively. Firstly, the development stage results of 7 permanent teeth were added up and the estimated age was obtained through the original transformation tables. Secondly, 80% of the samples (80 males and 80 females in each age group) were randomly selected from 2 000 OPGs as the train set. The chronological age of the selected patients was taken as the dependent variable, while gender and the development stage results of 7 permanent teeth were taken as the independent variable to establish multiple regression model. The remaining 20% of the samples were substituted into the model as the test set, to verify the accuracy of age estimation by multiple regression model. Results: Mean chronological ages of males and females were 10.03±0.09 years and 10.01±0.09 years, respectively. The age estimated by original transformation tables showed an overestimation for males (0.18 years on average) and an underestimation for females (0.02 years on average), with mean absolute error (MAE) of 0.94 years and 0.97 years, respectively. While the results by multiple regression model showed that males were overestimated by 0.06 years on average and females were underestimated by 0.02 years on average. The MAE was 0.66 years and 0.77 years, respectively. Conclusion: The Nolla method is suitable for age estimation of Northern Chinese Han children. Compared with the original transformation tables method, the multiple regression model is more accurate for age estimation.