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Craniofacial growth predictors for class II and III malocclusions: A systematic review

Objective To evaluate the validity of craniofacial growth predictors in class II and III malocclusion. Material and methods An electronic search was conducted until August 2020 in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Scopus, Bireme, Lilacs and Scielo including all languages. T...

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Published in:Clinical and experimental dental research 2021-04, Vol.7 (2), p.242-262
Main Authors: Jiménez‐Silva, Antonio, Carnevali‐Arellano, Romano, Vivanco‐Coke, Sheilah, Tobar‐Reyes, Julio, Araya‐Díaz, Pamela, Palomino‐Montenegro, Hernán
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creator Jiménez‐Silva, Antonio
Carnevali‐Arellano, Romano
Vivanco‐Coke, Sheilah
Tobar‐Reyes, Julio
Araya‐Díaz, Pamela
Palomino‐Montenegro, Hernán
description Objective To evaluate the validity of craniofacial growth predictors in class II and III malocclusion. Material and methods An electronic search was conducted until August 2020 in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Scopus, Bireme, Lilacs and Scielo including all languages. The articles were selected and analyzed by two authors independently and the selected studies was assessed using the 14‐item Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS‐2). The quality of evidence and strength of recommendation was assessed by the GRADE tool. Results In a selection process of two phases, 10 articles were included. The studies were grouped according to malocclusion growth predictor in (1) class II (n = 4); (2) class III (n = 5) and (3) class II and III (n = 1). The predictors were mainly based on data extracted from cephalometries and characterized by: equations, structural analysis, techniques and computer programs among others. The analyzed studies were methodologically heterogeneous and had low to moderate quality. For class II malocclusion, the predictors proposed in the studies with the best methodological quality were based on mathematical models and the Fishman system of maturation assessment. For class III malocclusion, the Fishman system could provide adequate growth prediction for short‐ and long‐term. Conclusions Because of the heterogeneity of the design, methodology and the quality of the articles reviewed, it is not possible to establish only a growth prediction system for class II and III malocclusion. High‐quality cohort studies are needed, well defined data extraction from cephalometries, radiographies and clinical characteristics are required to design a reliable predictor.
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Material and methods An electronic search was conducted until August 2020 in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Scopus, Bireme, Lilacs and Scielo including all languages. The articles were selected and analyzed by two authors independently and the selected studies was assessed using the 14‐item Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS‐2). The quality of evidence and strength of recommendation was assessed by the GRADE tool. Results In a selection process of two phases, 10 articles were included. The studies were grouped according to malocclusion growth predictor in (1) class II (n = 4); (2) class III (n = 5) and (3) class II and III (n = 1). The predictors were mainly based on data extracted from cephalometries and characterized by: equations, structural analysis, techniques and computer programs among others. The analyzed studies were methodologically heterogeneous and had low to moderate quality. For class II malocclusion, the predictors proposed in the studies with the best methodological quality were based on mathematical models and the Fishman system of maturation assessment. For class III malocclusion, the Fishman system could provide adequate growth prediction for short‐ and long‐term. Conclusions Because of the heterogeneity of the design, methodology and the quality of the articles reviewed, it is not possible to establish only a growth prediction system for class II and III malocclusion. High‐quality cohort studies are needed, well defined data extraction from cephalometries, radiographies and clinical characteristics are required to design a reliable predictor.</description><identifier>ISSN: 2057-4347</identifier><identifier>EISSN: 2057-4347</identifier><identifier>DOI: 10.1002/cre2.357</identifier><identifier>PMID: 33274551</identifier><language>eng</language><publisher>United States: John Wiley &amp; Sons, Inc</publisher><subject>Bias ; Cephalometry ; class II malocclusion ; class III malocclusion ; Dental occlusion ; Discriminant analysis ; growth and development ; growth predictors ; Humans ; Malocclusion ; Malocclusion, Angle Class II - diagnosis ; Malocclusion, Angle Class III - diagnosis ; Mathematical models ; Orthodontics ; Review ; Semantics ; Statistical analysis ; Systematic review</subject><ispartof>Clinical and experimental dental research, 2021-04, Vol.7 (2), p.242-262</ispartof><rights>2020 The Authors. published by John Wiley &amp; Sons Ltd.</rights><rights>2020 The Authors. 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Material and methods An electronic search was conducted until August 2020 in PubMed, Cochrane Library, Embase, EBSCOhost, ScienceDirect, Scopus, Bireme, Lilacs and Scielo including all languages. The articles were selected and analyzed by two authors independently and the selected studies was assessed using the 14‐item Quality Assessment Tool for Diagnostic Accuracy Studies (QUADAS‐2). The quality of evidence and strength of recommendation was assessed by the GRADE tool. Results In a selection process of two phases, 10 articles were included. The studies were grouped according to malocclusion growth predictor in (1) class II (n = 4); (2) class III (n = 5) and (3) class II and III (n = 1). The predictors were mainly based on data extracted from cephalometries and characterized by: equations, structural analysis, techniques and computer programs among others. The analyzed studies were methodologically heterogeneous and had low to moderate quality. For class II malocclusion, the predictors proposed in the studies with the best methodological quality were based on mathematical models and the Fishman system of maturation assessment. For class III malocclusion, the Fishman system could provide adequate growth prediction for short‐ and long‐term. Conclusions Because of the heterogeneity of the design, methodology and the quality of the articles reviewed, it is not possible to establish only a growth prediction system for class II and III malocclusion. 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subjects Bias
Cephalometry
class II malocclusion
class III malocclusion
Dental occlusion
Discriminant analysis
growth and development
growth predictors
Humans
Malocclusion
Malocclusion, Angle Class II - diagnosis
Malocclusion, Angle Class III - diagnosis
Mathematical models
Orthodontics
Review
Semantics
Statistical analysis
Systematic review
title Craniofacial growth predictors for class II and III malocclusions: A systematic review
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