Orthodontics, Adams School of Dentistry, The University of North Carolina at Chapel Hill, Chapel Hill, NC.
Department of Mathematical Sciences, Binghamton University, State University of New York, Binghamton, NY.
Am J Orthod Dentofacial Orthop. 2022 Jan;161(1):e1-e11. doi: 10.1016/j.ajodo.2021.06.012. Epub 2021 Sep 15.
The conundrum of determining how to treat a patient with Class III malocclusion is significant, creating a burden on the patient and challenging the orthodontist. The objective of this study was to employ a statistical prediction model derived from our previous cephalometric data on 5 predominant subtypes of skeletal Class III malocclusion to test the hypothesis that Class III subtypes are associated with treatment modalities (eg, surgical vs nonsurgical) and treatment outcome.
Pretreatment lateral cephalometric records of 148 patients were digitized for 67 cephalometric variables, and measurements were applied to a mathematical equation to assign a Class III subtype. Subjects were assigned to either a surgical or nonsurgical group depending on the treatment received. Treatment outcome was determined by facial profile and clinical photographs. Log binomial models were used for statistical analysis.
Subtype 1 (mandibular prognathic) patients were 3.5 × more likely to undergo orthognathic surgery than subtypes 2/3 (maxillary deficient) and 5.3 × more likely than 4/5 (combination). Subtype 1 patients were also 1.5 × more likely to experience treatment failure than subtypes 2/3 (maxillary deficient) and 4/5 (combination).
This assessment of a systematic method to characterize patients with Class III malocclusion into subtypes revealed that subtype 1 (mandibular prognathic) showed a likelihood to undergo orthognathic surgery while subtypes 2/3 experienced significantly lower treatment failure (in response to orthodontics alone). Further refinement of the equation may yield a reliable prediction model for earlier identification of surgical patients and also provide predictive power of Class III treatment outcomes.
如何治疗 III 类错颌患者是一个难题，这给患者带来了负担，也给正畸医生带来了挑战。本研究的目的是利用我们以前的头颅侧位片数据中 5 种主要的骨骼 III 类错颌亚类的统计预测模型来检验以下假设：III 类错颌亚类与治疗方式（如手术与非手术）和治疗效果相关。
对 148 名患者的治疗前头颅侧位片记录进行数字化处理，共 67 项头影测量值，将测量值应用于一个数学方程，以确定 III 类错颌的亚类。根据治疗方法，患者被分为手术组或非手术组。通过面部轮廓和临床照片来确定治疗效果。采用对数二项式模型进行统计学分析。
1 型（下颌前突）患者接受正颌手术的可能性是 2/3 型（上颌不足）和 4/5 型（混合型）的 3.5 倍，是 4/5 型的 5.3 倍。1 型患者的治疗失败率也比 2/3 型（上颌不足）和 4/5 型（混合型）高 1.5 倍。
本研究评估了一种将 III 类错颌患者分类为亚类的系统方法，结果表明 1 型（下颌前突）患者有接受正颌手术的倾向，而 2/3 型（上颌不足）患者的治疗失败率明显较低（仅接受正畸治疗）。进一步改进该方程可能会产生一个可靠的预测模型，以便更早地识别手术患者，并对 III 类错颌的治疗效果提供预测能力。
