A better statistical method of predicting postsurgery soft tissue response in Class II patients

Abstract

The multivariate PLS method was more satisfactory than the OLS method in accurately predicting the soft tissue profile change after surgical correction of severe Class II malocclusions.

A more accurate soft-tissue prediction model for Class III 2-jaw surgeries

“…By the same token, because of repositioning and rotation of the mandible, the new most anterior soft-tissue point of the chin (soft-tissue pogonion) may not reflect the presurgical soft-tissue pogonion. 13,23 As in most commercial software, a Bezier spline function is used to connect the landmark points, creating a gentle smooth curve. 6 By using the Bezier spline function, a prediction error (Figs 2 and 3) that is located along the Bezier curve (Fig 4) becomes more tolerable.…”

“…26 In addition, the improved accuracy of the PLS method is most likely because the soft-tissue response at a specific point highly depends on its adjacent soft-tissue response: ie, the interdependency of soft-tissue points. 13 However, the aforementioned investigation had only been performed for mandibular setback surgeries alone. Class III 2-jaw surgery patients had not yet been included.…”

“…7,8 The partial least squares (PLS) method is a comparatively new way of formulating prediction equations, and its application to various scientific and biologic disciplines from chemical engineering to brain image analysis is becoming increasingly widespread. [9][10][11][12][13] Applying the PLS method is advantageous when there are many variables and they are highly correlated. The merit of the PLS method is its capability of taking correlation structures into account, controlling not only for the correlations between the predictor and response variables but also for the correlations within the predictor variables and the response variables.…”

Testing a better method of predicting postsurgery soft tissue response in Class II patients: A prospective study and validity assessment

“…Lee et al 1 previously suggested a multivariate prediction method for Class II surgery patients. In the study by Lee et al, 1 80 patients provided the training data set that was used to build the prediction algorithm.…”

“…1 This method was based on a multivariate partial least squares regression (PLS) that returned more accurate prediction results than conventional methods. For the validity of this new prediction method to be confirmed, its prediction errors should also be reliable for other types of patients and additional data sets.…”