Improved method for predicting adult height of pubertal boys using a mathematical model

Area of Science:

• Pediatrics
• Endocrinology
• Growth and Development

Background:

• Current adult height prediction methods often have significant errors, potentially due to reliance on bone age estimation.
• The 'Infancy-Childhood-Puberty' (ICP) model offers an alternative approach to growth prediction.

Purpose of the Study:

• To evaluate the accuracy of the ICP model for predicting adult height in pubertal boys.
• To compare the ICP model's predictive accuracy against established methods like Bayley-Pinneu (BP) and Tanner-Whitehouse (TW).
• To develop and validate a new prediction equation (ICPN) incorporating paternal height based on the ICP model.

Main Methods:

• Review of growth data from 39 normal boys followed from infancy to adult height.
• Application of the ICP model without bone age estimation.
• Comparison of prediction errors (absolute and maximal range) with BP and TW methods.
• Derivation and validation of the ICP-New (ICPN) equation including paternal height.

Main Results:

• The ICP model alone showed significantly lower absolute error (3.4 cm) and maximal error range (10 cm) compared to BP (5.3 cm, 22 cm) and TW (4.9 cm, 21 cm) methods.
• The ICPN equation further improved accuracy, with an absolute error of 2.3 cm and a maximal error range of 6 cm.
• Both ICP and ICPN demonstrated statistically significant improvements in prediction accuracy (p < 0.05).

Conclusions:

• The ICP model provides a more accurate prediction of adult height in pubertal boys than methods relying on bone age.
• The ICPN equation, incorporating paternal height, offers enhanced accuracy for adult height prediction.
• These findings suggest that the ICP model and ICPN equation are valuable tools for predicting adult height in clinical practice.