Related Experiment Video
Updated: Jun 12, 2025

Binocular Dynamic Visual Acuity in Eyeglass-Corrected Myopic Patients
Published on: March 29, 2022
Multivariable Model to Predict Toric Ortho-K Lens Prescription
Hsiuwan Wendy Yang1, Chihkai Leon Liang, Hsinhui Wang
1Department of Biomedical Engineering (H.W.Y., H.K.C.), National Yang Ming Chiao Tung University, Taipei, Taiwan; and Ophthalmology Clinics (C.L.L., H.W.), Eyeplus Group, Taiwan.
Objective:
Orthokeratology (Ortho-K) effectively controls myopia progression. Toric Ortho-K lenses are used for moderate-to-high astigmatism, but predictive models with multiple corneal parameters are limited. This study aimed to identify key predictors for toric lens prescription in Ortho-K.
Methods:
A retrospective analysis was conducted on 506 patients undergoing Ortho-K treatment, incorporating 15 parameters such as age, sex, refractive error, corneal astigmatism, and flat eccentricity. Using both univariate and multivariate models, significant predictors were identified using logistic regression and refined with backward stepwise regression, evaluated by receiver operating characteristic curve analysis.
Results:
The 4-variable model (corneal astigmatism [∆K], steep eccentricity [Steep e], Sagittal Height Difference at 8 mm [SD8], and Corneal Cylindrical to Spherical [C/S] ratio) achieved an area under the curve (AUC) of 0.92 (sensitivity 89.7%, specificity 79.5%). Receiver operating characteristic analysis validated thresholds: ∆K>1.50 D (AUC 0.87), SD8 greater than 34 μm (AUC 0.82), flat eccentricity greater than 0.68 (AUC 0.73), and C/S ratio greater than 0.59 (AUC 0.63).
Conclusion:
This study developed the 4-variable model for toric Ortho-K lens fitting, identifying corneal astigmatism and SD8 as key predictors for detecting limbus-to-limbus astigmatism. Steep and flat eccentricities offered predictive and clinical insights, respectively.
Related Concept Videos
One-Compartment Open Model: Wagner-Nelson and Loo Riegelman Method for ka Estimation
On...
Pharmacokinetic Models: Comparison and Selection Criterion
Physiological models take a detailed approach by considering specific molecular processes. They can predict drug distribution, metabolism, and elimination changes, providing a comprehensive understanding of how drugs interact with the body.
Multicompartment Models: Overview
These models offer a more comprehensive representation of drug behavior in the body than one-compartment models. They accommodate the complexity of drug distribution,...
Analysis Methods of Pharmacokinetic Data: Model and Model-Independent Approaches
The model approach uses mathematical models to describe changes in drug concentration over time. Pharmacokinetic models help characterize drug behavior in patients, predict drug concentration in the body fluids, calculate optimum dosage regimens, and evaluate the risk of toxicity. However, ensuring that the model fits the experimental data accurately...
Model Approaches for Pharmacokinetic Data: Distributed Parameter Models
The distributed parameter models are specifically designed to account for variations and differences in some drug classes. This model is particularly useful for assessing regional concentrations of anticancer or...
Model Approaches for Pharmacokinetic Data: Compartment Models
Two primary types of compartment models are recognized: mammillary and catenary. The more...

