SynthesisClinical and experimental dental research2021
Craniofacial growth predictors for class II and III malocclusions: A systematic review.
Synthesis in Clinical and experimental dental research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 papers, 1 of them a synthesis that pooled it.
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Who cites it
11 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Craniofacial growth predictors for class II and III malocclusions: A systematic review.Clinical and experimental dental research · 2021Pooled it
- Machine Learning-Based Model for Predicting Short- and Long-Term Growth in Untreated Class III Malocclusion.Orthodontics & craniofacial research · 2026Article
- Epigenetic Connections in Malocclusion.International journal of molecular sciences · 2026Review
- Finite element analysis of temporomandibular joint stress distribution during treatment with novel digital composite plates and invisible aligners.BMC oral health · 2025Article
- Morphologic predictors of mandibular changes induced by Sander's Bite Jumping Appliance.Orthodontics & craniofacial research · 2025Article
- The Role of Mandibular Thickness in Determining Anteroposterior Skeletal Relationships.Dentistry journal · 2024Article
- Convolutional Neural Network-Based Deep Learning Methods for Skeletal Growth Prediction in Dental Patients.Journal of imaging · 2024Article
- Article
- Evaluation of the Co-Go-Me angle as a predictor in Class II patients treated with Herbst appliance and skeletal anchorage: a retrospective cohort study.Frontiers in oral health · 2024Article
- Prediction of Pubertal Mandibular Growth in Males with Class II Malocclusion by Utilizing Machine Learning.Diagnostics (Basel, Switzerland) · 2023Article
- Treatment of Class III Malocclusion and Anterior Crossbite with Aligners: A Case Report.Medicina (Kaunas, Lithuania) · 2022Article
Corrections and comments
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Authors and funding
6 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo evaluate the validity of craniofacial growth predictors in class II and III malocclusion. MATERIAL AND
methodsAn 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.
resultsIn 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.
conclusionsBecause 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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