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Year : 2016  |  Volume : 13  |  Issue : 1  |  Page : 38-45

Prediction of lip response to orthodontic treatment using a multivariable regression model

1 Torabinejad Dental Research Center and Department of Orthodontics, Isfahan University of Medical Sciences, Isfahan, Iran
2 Dental Students Research Center, School of Dentistry, Isfahan University of Medical Sciences, Isfahan, Iran

Correspondence Address:
Safieh Abbasi
Dental Students Research Center, School of Dentistry, Isfahan University of Medical Sciences, Isfahan
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Source of Support: None, Conflict of Interest: None

DOI: 10.4103/1735-3327.174697

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Background: This was a retrospective cephalometric study to develop a more precise estimation of soft tissue changes related to underlying tooth movment than simple relatioship betweenhard and soft tissues. Materials and Methods: The lateral cephalograms of 61 adult patients undergoing orthodontic treatment (31 = premolar extraction, 31 = nonextraction) were obtained, scanned and digitized before and immediately after the end of treatment. Hard and soft tissues, angular and linear measures were calculated by Viewbox 4.0 software. The changes of the values were analyzed using paired t-test. The accuracy of predictions of soft tissue changes were compared with two methods: (1) Use of ratios of the means of soft tissue to hard tissue changes (Viewbox 4.0 Software), (2) use of stepwise multivariable regression analysis to create prediction equations for soft tissue changes at superior labial sulcus, labrale superius, stomion superius, inferior labial sulcus, labrale inferius, stomion inferius (all on a horizontal plane). Results: Stepwise multiple regressions to predict lip movements showed strong relations for the upper lip (adjusted R2 = 0.92) and the lower lip (adjusted R2 = 0.91) in the extraction group. Regression analysis showed slightly weaker relations in the nonextraction group. Conclusion: Within the limitation of this study, multiple regression technique was slightly more accurate than the ratio of mean prediction (Viewbox4.0 software) and appears to be useful in the prediction of soft tissue changes. As the variability of the predicted individual outcome seems to be relatively high, caution should be taken in predicting hard and soft tissue positional changes.

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