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Adult Height Prediction Models

  • Hans Henrik Thodberg
  • Anders Juul
  • Jens Lomholt
  • David D. Martin
  • Oskar G. Jenni
  • Jon Caflisch
  • Michael B. Ranke
  • Sven Kreiborg
Chapter

Abstract

We review seven methods for adult height prediction (AHP) based on bone age, ranging from the Bayley–Pinneau method, published in 1952, to the BoneXpert method, published in 2009. These models are based on four different methods for bone age assessment including Greulich–Pyle, Tanner–Whitehouse, Fels, and the automated BoneXpert method. The aim of this chapter is to convey an understanding of the various parameters which contribute to AHP and how to best incorporate them into the AHP methods. The starting point is the Bayley–Pinneau method which predicts the fraction of adult height achieved from the bone age. Children with advanced bone age (early maturers) tend to have a stronger growth spurt, and late maturers have a weaker growth spurt. Accordingly, Bayley and Pinneau provided special AHP tables for early, average, and late maturers. The other five AHP methods reviewed are the three variants of the Tanner–Whitehouse method, TW Mark I (1975), TW Mark II (1983), and TW3 (2001), and the RWT methods of 1975 and 1993. They all model the expected adult height of children at each age using a linear model of height and bone age, and for the RWT models, also by using terms with midparental height and body weight. The main shortcoming of these models is that the linear bone age dependence is unable to describe children with constitutional delay of growth and puberty or precocious puberty. The recently developed automated BoneXpert method improves the Bayley–Pinneau method by modelling the growth potential (the fraction of adult height left to grow) as a non-linear function of two variables, bone age and bone age delay. The BoneXpert AHP method was based on the original images from the First Zürich Longitudinal Study and was subsequently validated on the more recent Third Zürich Longitudinal Study of 198 Swiss children. An additional validation study on 164 Danish children is also presented. The main advantage of the BoneXpert method is that it is based on an automated bone age which removes rater variability.

Keywords

Standard Deviation Score Turner Syndrome Adult Height Tanner Stage Body Mass Index Standard Deviation Score 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Abbreviations

AHP

Adult height prediction

BA

Bone age

BMI

Body mass index

BP

Bayley–Pinneau

BX

BoneXpert

CA

Chronological age

GH

Growth hormone

GHD

Growth hormone deficiency

GP

Greulich–Pyle

gp

Growth potential = (Hh)/H

H

Adult height

h

Current height

RMSE

Root mean square error

RUS

Radius, ulna, and short bones

RWT

Roche–Wainer–Thissen

SDS

Standard deviation score

TW

Tanner–Whitehouse

1ZLS

First Zürich Longitudinal Study

3ZLS

Third Zürich Longitudinal Study

Notes

Acknowledgements

We thank Elisabeth Kaelin and Luciano Molinari for data management and Julia Neuhof for scanning of X-rays in Zürich. The Zurich Longitudinal Studies are supported by a research grant of the Swiss National Science Foundation (Grant 32473B_129956 to O.G.J.).

We acknowledge Novo Nordisk for providing the scanner used to digitize the Zürich and Björk studies.

References

  1. Bayley N. Tables for predicting adult height from skeletal age and present height. J Pediatr. 1946;28:49–64.PubMedCrossRefGoogle Scholar
  2. Bayley N, Pinneau SR. Tables for predicting adult height from skeletal age: revised for use with the Greulich-Pyle hand standards. J Pediatr. 1952;40:423–41.PubMedCrossRefGoogle Scholar
  3. Binder G, Grauer ML, Wehner AV, Wehner F, Ranke MB. Outcome in tall stature. Final height and psychological aspects in 220 patients with and without treatment. Eur J Pediatr. 1997;156:905–10.PubMedCrossRefGoogle Scholar
  4. Björk A. The use of metallic implants in the study of facial growth in children: method and application. Am J Phys Anthropol. 1968;29:155–310.CrossRefGoogle Scholar
  5. Brämswig JE, Fasse M, Holthoff ML, Von Lengerke HJ, Von Petrykowski W, Schellong G. Adult height in boys and girls with untreated short stature and constitutional delay of growth and puberty: accuracy of five different methods of height prediction. J Pediatr. 1990;117:886–91.PubMedCrossRefGoogle Scholar
  6. de Waal WJ, Greyn-Fokker MH, Stijnen T, van Gurp EA, Toolens AM, de Munick Keizer-Schrama SM, Aarsen RS, Drop SL. Accuracy of final height prediction and effect of growth-reductive therapy in 362 constitutionally tall children. J Clin Endocrinol Metab. 1996;81:1206–16.PubMedCrossRefGoogle Scholar
  7. Galton F. Regression towards mediocrity in hereditary stature. J Anthropol Inst Great Br Ireland. 1886;15:246–63. http://galton.org/essays/1880-1889/galton-1886-jaigi-regression-stature.pdf.CrossRefGoogle Scholar
  8. Greulich WW, Pyle SI. Radiographic atlas of skeletal development of the hand and wrist. 2nd ed. California: Stanford University Press; 1959.Google Scholar
  9. Joss EE, Temperli R, Mullis PE. Adult height in constitutionally tall stature: accuracy of five different height prediction methods. Arch Dis Child. 1992;67:1357–62.PubMedCrossRefGoogle Scholar
  10. Khamis HJ, Guo S. Improvement in the Roche-Wainer-Thissen stature prediction model: a comparative study. Am J Hum Biol. 1993;5:669–79.CrossRefGoogle Scholar
  11. Martin DD, Deusch D, Schweizer R, Binder G, Thodberg HH, Ranke MB. Clinical application of automated Greulich-Pyle bone age in children with short stature. Pediatr Radiol. 2009;39:598–607.PubMedCrossRefGoogle Scholar
  12. Martin DD, Neuhof J, Jenni OG, Ranke MB, Thodberg HH. Automatic determination of left-and right-hand bone age in the First Zurich Longitudinal Study. Horm Res. 2010;74:50–5.CrossRefGoogle Scholar
  13. Onat T. Multifactorial prediction of adult height of girls during early adolescence allowing for genetic potential, skeletal and sexual maturity. Hum biol. 1983;55:443–61.PubMedGoogle Scholar
  14. Prader A, Largo RH, Molinari L, Issler C. Physical growth of Swiss children from birth to 20 years of age. First Zurich longitudinal study of growth and development. Helv Paediatr Acta Suppl. 1989;52:1–125 available from: PM:2737921.PubMedGoogle Scholar
  15. Roche AF, Wainer H, Thissen D. The RWT method for the prediction of adult stature. Pediatrics. 1975;56:1026–33.Google Scholar
  16. Roche AF, Chumlea W, Thissen D. Assessing the skeletal maturity of the hand-wrist: Fels method. Springfield, IL: Charles C. Thomas; 1988.Google Scholar
  17. Sandhu J, Ben-Shlomo Y, Cole TJ, Holly J, Davey SG. The impact of childhood body mass index on timing of puberty, adult stature and obesity: a follow-up study based on adolescent anthropometry recorded at Christ’s Hospital (1936–1964). Int J Obes (Lond) 2006;30:14–22.CrossRefGoogle Scholar
  18. Tanner JM. Review of Assessing the skeletal maturity of the hand-wrist: FELS method. Am J Hum Biol. 1989;1:493–4.CrossRefGoogle Scholar
  19. Tanner JM, Whitehouse RH, Healy MJR. A new system for estimating skeletal maturity from the hand and wrist, with standards derived from a study of 2,600 healthy British children. Paris: Centre International de l’Enfance; 1962.Google Scholar
  20. Tanner JM, Whitehouse RH, Marshall WA, Carter BS. Prediction of adult height from height, bone age, and occurrence of menarche, at ages 4 to 16 with allowance for midparent height. Arch Dis Child. 1975a;50:14–26.PubMedCrossRefGoogle Scholar
  21. Tanner JM, Whitehouse RH, Marshall WA, Healy MJR, Goldstein H. Assessment of skeletal maturity and prediction of adult height. London: Academic; 1975b.Google Scholar
  22. Tanner JM, Landt KW, Cameron N, Carter BS, Patel J. Prediction of adult height from height and bone age in childhood. A new system of equations (TW Mark II) based on a sample including very tall and very short children. Arch Dis Child. 1983a;58:767–76.PubMedCrossRefGoogle Scholar
  23. Tanner JM, Whitehouse RH, Cameron N, Marshall WA, Healy MJR, Goldstein H. Assessment of skeletal maturity and prediction of adult height. London, Acad. Press; 1983b.Google Scholar
  24. Tanner JM, Healy MJR, Goldstein H, Cameron N. Assessment of skeletal maturity and prediction of adult height (TW3 Method). London: WB Saunders; 2001.Google Scholar
  25. Thodberg HH. Clinical review: an automated method for determination of bone age. J Clin Endocrinol Metab. 2009;94:2239–44.PubMedCrossRefGoogle Scholar
  26. Thodberg HH, Jenni OG, Caflisch J, Ranke MB, Martin DD. Prediction of adult height based on automated determination of bone age. J Clin Endocrinol Metab. 2009a;94:4868–74.PubMedCrossRefGoogle Scholar
  27. Thodberg HH, Kreiborg S, Juul A, Pedersen KD. The BoneXpert method for automated determination of skeletal maturity. IEEE Trans Med Imaging 2009b;28:52–66.PubMedCrossRefGoogle Scholar
  28. Thodberg HH, Rijn RR, Tanaka T, Martin DD, Kreiborg S. A pediatric bone index derived automated radiogrammetry. Osteoporosis Int. 2009c;21:1391–1400.CrossRefGoogle Scholar
  29. Thodberg HH, Neuhof J, Ranke MB, Jenni OG, Martin DD. Validation of bone age methods through their ability to predict adult height. Horm Res. 2010;74:15–22.CrossRefGoogle Scholar
  30. van Rijn RR, Lequin MH, Thodberg HH. Automatic determination of Greulich and Pyle bone age in healthy Dutch children. Pediatr Radiol. 2009;39:591–7.PubMedCrossRefGoogle Scholar
  31. Zachmann M, Sobradillo B, Frank M, Frisch H, Prader A. Bayley-Pinneau, Roche-Wainer-Thissen, and Tanner height predictions in normal children and in patients with various pathologic conditions. J Pediatr. 1978;93:749–55.PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC 2012

Authors and Affiliations

  • Hans Henrik Thodberg
    • 1
  • Anders Juul
    • 2
  • Jens Lomholt
    • 3
  • David D. Martin
    • 4
  • Oskar G. Jenni
    • 5
  • Jon Caflisch
    • 5
  • Michael B. Ranke
    • 4
  • Sven Kreiborg
    • 3
  1. 1.VisianaHolteDenmark
  2. 2.Department of Growth and ReproductionRigshospitaletCopenhagenDenmark
  3. 3.Copenhagen UniversityCopenhagenDenmark
  4. 4.University Children’s Hospital TübingenTübingenGermany
  5. 5.Child Development Centre, University Children’s Hospital ZürichZurichSwitzerland

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