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Machine learning-based nomogram to predict poor response to overnight orthokeratology in Chinese myopic children: A
Wenting Tang1, Jiaqian Li2, Xuelin Fu3
1Department of Ophthalmology, The First Affiliated Hospital of Chengdu Medical College, Chengdu Medical College, Chengdu, China.
Insights
A new nomogram accurately predicts poor response to orthokeratology in children. This tool helps identify individuals who may not benefit from myopia control treatment.
Area of Science:
- Ophthalmology
- Pediatric Optometry
Background:
- Orthokeratology is a myopia control treatment.
- Predicting treatment response is crucial for effective myopia management.
Purpose of the Study:
- To develop and validate a nomogram for predicting poor response to orthokeratology in myopic children.
Main Methods:
- A logistic regression model with least absolute shrinkage and selection operator was used.
- Data from Chinese myopic children (aged 8-15) were used for training, validation, and external testing.
- Model performance was assessed using AUC, calibration plots, and decision curve analysis.
Main Results:
- The nomogram included baseline age, spherical equivalent, axial length, pupil diameter, surface asymmetry index, and parental myopia.
- The nomogram demonstrated excellent discrimination with AUCs of 0.871 (training), 0.863 (validation), and 0.817 (external cohort).
- An online calculator is available for predicting orthokeratology response.
Conclusions:
- The developed nomogram provides accurate individual prediction of poor response to overnight orthokeratology.
- This tool can aid clinicians in managing myopia in children.
Purpose:
To develop and validate an effective nomogram for predicting poor response to orthokeratology.
Methods:
Myopic children (aged 8-15 years) treated with orthokeratology between February 2018 and January 2022 were screened in four hospitals of different tiers (i.e. municipal and provincial) in China. Potential predictors included 32 baseline clinical variables. Nomogram for the outcome (1-year axial elongation ≥0.20 mm: poor response; <0.20 mm: good response) was computed from a logistic regression model with the least absolute shrinkage and selection operator. The data from the First Affiliated Hospital of Chengdu Medical College were randomly assigned (7:3) to the training and validation cohorts. An external cohort from three independent multicentre was used for the model test. Model performance was assessed by discrimination (the area under curve, AUC), calibration (calibration plots) and utility (decision curve analysis).
Results:
Between January 2022 and March 2023, 1183 eligible subjects were screened from the First Affiliated Hospital of Chengdu Medical College, then randomly divided into training (n = 831) and validation (n = 352) cohorts. A total of 405 eligible subjects were screened in the external cohort. Predictors included in the nomogram were baseline age, spherical equivalent, axial length, pupil diameter, surface asymmetry index and parental myopia (p < 0.05). This nomogram demonstrated excellent calibration, clinical net benefit and discrimination, with the AUC of 0.871 (95% CI 0.847-0.894), 0.863 (0.826-0.901) and 0.817 (0.777-0.857) in the training, validation and external cohorts, respectively. An online calculator was generated for free access (http://39.96.75.172:8182/#/nomogram).
Conclusion:
The nomogram provides accurate individual prediction of poor response to overnight orthokeratology in Chinese myopic children.
