上海口腔医学

上海口腔医学 ›› 2026, Vol. 35 ›› Issue (3): 265-270.doi: 10.19439/j.sjos.2026.03.007

• 论著 • 上一篇    下一篇

青少年患者口腔正畸疗效的影响因素分析及logistic回归模型构建

马辉1, 孙晗2, 濮陈洁2, 许倩1, 蒙明梅3, 贺涵4   

  1. 1.四川口腔医院 正畸科,四川 成都 610031;
    2.无锡口腔医院 正畸科,江苏 无锡 214003;
    3.四川大学华西口腔医院,四川 成都 610041;
    4.成都市第三人民医院 正畸科,四川 成都 610031
  • 收稿日期:2026-02-10 修回日期:2026-03-27 发布日期:2026-07-02
  • 通讯作者: 贺涵,E-mail：13619840557@163.com
  • 作者简介:马辉（1990—）,女,硕士研究生,主治医师,E-mail：mahui00163@163.com
  • 基金资助:
    四川省自然科学基金青年科学基金项目（2022NSFSC1455）; 无锡市卫生健康委科研青年项目（Q202463）

Analysis of influencing factors on orthodontic efficacy in adolescent patients and construction of logistic regression model

Ma Hui1, Sun Han2, Pu Chenjie2, Xu Qian1, Meng Mingmei3, He Han4   

  1. 1. Department of Orthodontics, Sichuan Stomatology Hospital. Chengdu 610031, Sichuan Province;
    2. Department of Orthodontics, Wuxi Stomatology Hospital. Wuxi 214003, Jiangsu Province;
    3. West China Hospital of Stomatology, Sichuan University. Chengdu 610041, Sichuan Province;
    4. Department of Orthodontics, The Third People's Hospital of Chengdu. Chengdu 610031, Sichuan Province, China
  • Received:2026-02-10 Revised:2026-03-27 Published:2026-07-02

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摘要： 目的: 分析青少年患者口腔正畸疗效的影响因素,并构建logistic回归模型。方法: 选择2019年1月—2023年12月收治的260例青少年口腔正畸患者,采用正畸同行评价（peer assessment rating,PAR）指数评估疗效。治疗结束满2年时,PAR指数较治疗刚结束时降低>5分为疗效不佳组（n=53）,其余为疗效良好组（n=207）。采用二元logistic回归分析青少年口腔正畸患者疗效不佳的危险因素,并通过危险因素构建logistic回归模型。结果: 二元logistic回归分析显示,焦虑（OR=8.467,95%CI=2.800~25.609,P<0.001）、安氏Ⅱ类错（OR=9.624,95%CI=2.504~36.990,P=0.001）、安氏Ⅲ类错（OR=4.210,95%CI=1.146~15.467,P=0.030）、牙根形态异常（OR=5.927,95%CI=2.276~15.435,P<0.001）、口腔卫生较差（OR=2.943,95%CI=1.139~7.604,P=0.026）和患者依从性较差（OR=9.620,95%CI=3.047~30.376,P<0.001）是青少年口腔正畸患者疗效不佳的危险因素,保持器佩戴时间（OR=0.773,95%CI=0.691~0.864,P<0.001）是保护因素。使用危险因素构建logistic回归模型,Hosmer-Lemeshow拟合度检验显示,χ2=6.648,P=0.575,模型预测青少年口腔正畸患者疗效不佳的曲线下面积（area under the curve,AUC）为0.939,95%CI为0.908~0.971,敏感度、特异度分别为92.5%、83.6%,实际应用准确率为89.2%。结论: 青少年口腔正畸患者疗效与焦虑、错畸形类型、牙根形态异常、口腔卫生、依从性和保持器佩戴时间有关,通过危险因素构建的logistic回归模型具有较高预测价值。

关键词: 青少年, 口腔正畸, 临床疗效, 影响因素, Logistic回归模型

Abstract: PURPOSE: To analyze the influencing factors of orthodontic efficacy in adolescent patients and construct a logistic regression model. METHODS: A total of 260 adolescent orthodontic patients treated from January 2019 to December 2023 were selected. The therapeutic effect was evaluated using the peer assessment rating (PAR) index. At the 2-year follow-up after treatment completion, patients with a reduction of more than 5 points in the PAR index compared with immediately post-treatment were assigned to the poor efficacy group (n=53), and the remaining patients were assigned to the favorable efficacy group (n=207). Binary logistic regression was used to analyze the risk factors for poor efficacy in adolescent orthodontic patients, and logistic regression model was constructed based on the risk factors. RESULTS: The binary logistic regression analysis showed that anxiety (OR=8.467, 95%CI=2.800-25.609, P<0.001), Angle Class Ⅱ malocclusion (OR=9.624, 95%CI=2.504-36.990, P=0.001), Angle Class Ⅲ malocclusion (OR=4.210, 95%CI=1.146-15.467, P=0.030), root morphology abnormalities (OR=5.927, 95%CI=2.276-15.435, P<0.001), poor oral hygiene (OR=2.943, 95%CI=1.139-7.604, P=0.026) and poor patient compliance (OR=9.620, 95%CI =3.047-30.376, P<0.001) were risk factors for poor treatment outcome in adolescent orthodontic patients, while retainer wearing time (OR=0.773, 95%CI=0.69-0.864, P<0.001) was a protective factor. A logistic regression model was constructed using the risk factors. The Hosmer-Lemeshow goodness-of-fit test showed that χ2=6.648, P=0.575. The area under the curve (AUC) of the model for predicting poor treatment outcomes in adolescent orthodontic patients was 0.939, with a 95%CI of 0.908-0.971. The sensitivity and specificity were 92.5% and 83.6%, respectively, and the practical application accuracy was 89.2%. CONCLUSIONS: The orthodontic efficacy of adolescent orthodontic patients is related to anxiety, types of malocclusions, abnormal root morphology, oral hygiene, compliance and duration of retainer wearing. A logistic regression model constructed through risk factors has high predictive value.

Key words: Adolescent, Orthodontics, Treatment efficacy, Influencing factors, Logistic regression model

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