Prediction of soft-tissue changes after mandibular advancement surgery with an equation developed with multivariable regression.
BACKGROUND
This was a retrospective cephalometric study in patients undergoing mandibular advancement surgery. Our aim was to provide a more precise estimation of the postsurgical soft-tissue outcomes than can be achieved by using simple ratios of the hard and soft tissues.


METHODS
The lateral cephalograms of 64 patients undergoing mandibular advancement, from before and near the end of treatment, were scanned and digitized with a customized software program. Multivariable regression analyses were used to create prediction equations for soft-tissue changes at pogonion, inferior labial sulcus, labrale inferius, and stomion inferius (all in the horizontal plane).


CONCLUSIONS
This method of using multiple explanatory variables appears to be useful in the prediction of soft-tissue changes. At least 96% of the variation of each dependent variable was explained by its relationship with the explanatory variables in the relevant multivariable regression equation, and the results appeared to be clinically useful.
Kneafsey
Louise C
LC
UCL Eastman Dental Institute, London, United Kingdom.
Cunningham
Susan J
SJ
Petrie
Aviva
A
Hutton
Tim J
TJ
D000465:Algorithms; D002508:Cephalometry / Q000379:methods*; D005145:Face / Q000033:anatomy & histology* / Q000000981:diagnostic imaging; D005544:Forecasting; D006801:Humans; D007091:Image Processing, Computer-Assisted / Q000379:methods*; D008310:Malocclusion / Q000601:surgery; D019186:Mandibular Advancement; D015233:Models, Statistical; D011237:Predictive Value of Tests; D011859:Radiography; D012044:Regression Analysis; D012189:Retrospective Studies; D012886:Skull / Q000033:anatomy & histology / Q000000981:diagnostic imaging; D012986:Software Validation