Validity of age estimation methods and reproducibility of bone/dental maturity indices for chronological age estimation

Abstract

Aim

This systematic review sought to assess the validity of age estimation methods based on bone or dental maturity indices and their reproducibility through a meta-analysis of validation and reproducibility studies.

Data sources

A systematic online search was conducted in PubMed and Google Scholar.

Study selection

Cross-sectional studies were included. The authors excluded articles without information on validity and reproducibility outcomes, articles not written in English or Italian, and those where it was impossible to obtain pooled reproducibility estimates of Cohen’s kappa or the intraclass correlation coefficient (ICC) due to a lack of information on the variability measure.

Data extraction and synthesis

The authors tried to follow the preferred reporting items for systematic reviews and meta-analyses (PRISMA) protocol. They also considered the PICOS/PECOS strategy to assess the research questions in their included studies; nevertheless, no particular guideline was reported to be consistently followed in their study.

Results

Twenty-three (23) studies were selected for data extraction and critical appraisal. The pooled male mean error of the age prediction was 0.08 years (95% CI: −0.12; 0.29), and the pooled female mean error was 0.09 years (95% CI: −0.12; 0.30). Studies using Nolla’s method had a mean error closest to zero with a slight overestimation: mean male age prediction error of 0.02 (95% CI: −0.37; 0.41) and mean female age prediction error of 0.03 (95% CI: −0.34; 0.41). Haavikko’s method had a mean error of −1.12 (95% CI: −2.29; 0.06) and −1.33 (95% CI: −2.54; −0.13) for males and females, respectively. Cameriere’s method also underestimated the chronological age and was the only method with a higher absolute mean error for males than females (males: −0.22 [95% CI: −0.44; 0.00]; females: −0.17 [95% CI: −0.34; −0.01]). Overall, Demirjian’s and Willems’s methods tended to overestimate chronological age in both males (Demirjian: 0.59 [95% CI: 0.28; 0.91]; Willems: 0.07 [95% CI: −0.17; 0.31]) and females (Demirjian: 0.64 [95% CI 0.38; 0.90]; Willems: 0.09 [95% CI: −0.13; 0.31]). The prediction intervals (PI) overlapped zero for all methods, rendering the difference between estimated and chronological ages not statistically significant for males and females. Cameriere’s method showed the smallest PI for both biological genders, while the Haavikko and other methods had the widest intervals. No heterogeneity was observed in inter-examiner (heterogeneity: Q = 5.78, p = 0.888) and intra-examiner (heterogeneity: Q = 9.11, p = 0.611) agreement, so a fixed-effects model was used. For inter-examiner agreement, the ICC ranged from 0.89 to 0.99, and the meta-analytic pooled ICC was 0.98 (95% CI 0.97; 1.00), which was near-perfect reliability. Concerning intra-examiner agreement, the ICCs ranged from 0.90 to 1.00, and the meta-analytic pooled ICC was 0.99 (95% CI 0.98; 1.00), which was also close to perfect reliability.

Conclusions

This study recommended the Nolla and Cameriere methods as preferred approaches while mentioning that the Cameriere method was validated on a smaller sample size than Nolla’s, thus requiring further testing on additional populations to better assess the mean error estimates by sex. However, the evidence in this paper is of very low quality and offers no certainty.