An update of the statistical methods underlying the FELS method of skeletal maturity assessment

Abstract

Background: Evaluation of skeletal maturity provides clinicians and researchers a window into the developmental progress of the skeleton. The FELS method for maturity assessment provides a point estimate and standard error based on 98 skeletal indicators.

Aim: This paper outlines the statistical methodology used by the original FELS method and evaluates improvements that address the following: serial correlation in the calibration sample is now considered, a Bayesian estimation method is now employed to improve estimation near ages 0 and 18 years and uncertainty in the calibration due to sampling is now accounted for when computing confidence limits.

Subjects and methods: The original FELS method was calibrated using 677 Fels Longitudinal Study participants. In the improved method, serial correlation is accounted for using GEE, a Bayesian analysis with a prior centred on chronological age is used and the bootstrap is used to account for all sources of variation.

Results: Accounting for serial correlation resulted in larger slopes for ordinal indicators. The Bayesian paradigm led to narrower confidence limits and a natural interpretation of skeletal age. Sampling variability in the calibration parameters was negligible.

Conclusion: Improvements to the statistical basis of the FELS method provide a more effective method of estimating skeletal maturity.

• Bayesian
• bone age
• development
• longitudinal
• skeletal age

Acknowledgements

The authors thank the participants of the Fels Longitudinal Study and the data collection and management staff of the Lifespan Health Research Center. The authors also thank Thaddeus Tarpey for helpful comments that led to improvements in the manuscript.