Literature DB >> 33015973

Bayesian approach to longitudinal craniofacial growth: The Craniofacial Growth Consortium Study.

Richard J Sherwood1,2,3, Hee Soo Oh4, Manish Valiathan3, Kieran P McNulty5, Dana L Duren1,2, Ryan P Knigge1,2, Anna M Hardin1, Christina L Holzhauser1,2, Kevin M Middleton1.   

Abstract

Early in the 20th century, a series of studies were initiated across North America to investigate and characterize childhood growth. The Craniofacial Growth Consortium Study (CGCS) combines craniofacial records from six of those growth studies (15,407 lateral cephalograms from 1,913 individuals; 956 females, 957 males, primarily European descent). Standard cephalometric points collected from the six studies in the CGCS allows direct comparison of craniofacial growth patterns across six North American locations. Three assessors collected all cephalometric points and the coordinates were averaged for each point. Twelve measures were calculated from the averaged coordinates. We implemented a multilevel double logistic equation to estimate growth trajectories fitting each trait separately by sex. Using Bayesian inference, we fit three models for each trait with different random effects structures to compare differences in growth patterns among studies. The models successfully identified important growth milestones (e.g., age at peak growth velocity, age at cessation of growth) for most traits. In a small number of cases, these milestones could not be determined due to truncated age ranges for some studies and slow, steady growth in some measurements. Results demonstrate great similarity among the six growth studies regarding craniofacial growth milestone estimates and the overall shape of the growth curve. These similarities suggest minor variation among studies resulting from differences in protocol, sample, or possible geographic variation. The analyses presented support combining the studies into the CGCS without substantial concerns of bias. The CGCS, therefore, provides an unparalleled opportunity to examine craniofacial growth from childhood into adulthood.
© 2021 American Association for Anatomy.

Entities:  

Keywords:  Bayesian inference; cephalometrics; craniofacial growth; double logistic; growth modeling

Mesh:

Year:  2020        PMID: 33015973      PMCID: PMC8577187          DOI: 10.1002/ar.24520

Source DB:  PubMed          Journal:  Anat Rec (Hoboken)        ISSN: 1932-8486            Impact factor:   2.227


  46 in total

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Journal:  Angle Orthod       Date:  1991       Impact factor: 2.079

2.  American Association of Orthodontists Foundation Craniofacial Growth Legacy Collection: Overview of a powerful tool for orthodontic research and teaching.

Authors:  Sheldon Baumrind; Sean Curry
Journal:  Am J Orthod Dentofacial Orthop       Date:  2015-08       Impact factor: 2.650

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Journal:  J Orthod       Date:  2009-03

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Journal:  Angle Orthod       Date:  1972-01       Impact factor: 2.079

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7.  Predicting adult facial type from mandibular landmark data at young ages.

Authors:  Heesoo Oh; Ryan Knigge; Anna Hardin; Richard Sherwood; Dana Duren; Manish Valiathan; Emily Leary; Kieran McNulty
Journal:  Orthod Craniofac Res       Date:  2019-05       Impact factor: 1.826

8.  Growth of a species, an association, a science: 80 years of growth and development research.

Authors:  Richard J Sherwood; Dana L Duren
Journal:  Am J Phys Anthropol       Date:  2013-01       Impact factor: 2.868

9.  Skeletal growth and the changing genetic landscape during childhood and adulthood.

Authors:  Dana L Duren; Maja Seselj; Andrew W Froehle; Ramzi W Nahhas; Richard J Sherwood
Journal:  Am J Phys Anthropol       Date:  2013-01       Impact factor: 2.868

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Journal:  J Bone Joint Surg Am       Date:  1993-06       Impact factor: 5.284

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  2 in total

1.  Craniofacial growth and morphology among intersecting clinical categories.

Authors:  Ryan P Knigge; Anna M Hardin; Kevin M Middleton; Kieran P McNulty; Hee Soo Oh; Manish Valiathan; Dana L Duren; Richard J Sherwood
Journal:  Anat Rec (Hoboken)       Date:  2022-02-11       Impact factor: 2.227

2.  Estimating Craniofacial Growth Cessation: Comparison of Asymptote- and Rate-Based Methods.

Authors:  Anna M Hardin; Ryan P Knigge; Hee Soo Oh; Manish Valiathan; Dana L Duren; Kieran P McNulty; Kevin M Middleton; Richard J Sherwood
Journal:  Cleft Palate Craniofac J       Date:  2021-05-17
  2 in total

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