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Predicting Marfan Syndrome in Children With Congenital Ectopia Lentis: Development and Validation of a Nomogram
Kityee Ng1, Bo Qu2, Qianzhong Cao1
1State Key Laboratory of Ophthalmology, Zhongshan Ophthalmic Center, Sun Yat-Sen University, Guangdong Provincial Key Laboratory of Ophthalmology and Visual Science, Guangdong Provincial Clinical Research Center for Ocular Diseases, Guangzhou, China.
Insights
This study developed a nomogram to predict Marfan syndrome (MFS) in children with congenital ectopia lentis (CEL). The tool accurately identifies MFS, enabling early intervention and improved patient outcomes.
Area of Science:
- Genetics and Ophthalmology
- Pediatric Cardiology
- Medical Diagnostics
Background:
- Marfan syndrome (MFS) is a genetic disorder affecting connective tissue.
- Congenital ectopia lentis (CEL) is a key indicator of potential MFS.
- Accurate early diagnosis is crucial for managing MFS complications.
Purpose of the Study:
- To develop a predictive nomogram for Marfan syndrome (MFS) in pediatric patients presenting with congenital ectopia lentis (CEL).
- To utilize routinely collected clinical data for effective MFS prediction.
- To create a tool for personalized risk assessment in children with CEL.
Main Methods:
- Applied Ghent nosology and genetic testing to diagnose MFS in CEL patients.
- Utilized logistic regression to build a prediction model based on identified MFS predictors.
- Validated the nomogram's predictive performance using ROC curves, calibration plots, and decision curve analysis.
Main Results:
- Identified key predictors: BMI Z-score, corneal curvature radius, and aortic root diameter.
- The nomogram demonstrated strong predictive ability with an AUC of 0.889.
- Calibration and decision curve analyses confirmed the nomogram's clinical utility and discriminatory power.
Conclusions:
- The developed nomogram offers accurate, individualized prediction of MFS in children with CEL, especially those not meeting strict Ghent criteria.
- This tool facilitates personalized treatment strategies and improved outcomes for MFS.
- Early identification via the nomogram can mitigate severe symptoms and enhance patient prognosis.
Purpose:
To derive an effective nomogram for predicting Marfan syndrome (MFS) in children with congenital ectopia lentis (CEL) using regularly collected data.
Methods:
Diagnostic standards (Ghent nosology) and genetic test were applied in all patients with CEL to determine the presence or absence of MFS. Three potential MFS predictors were tested and chosen to build a prediction model using logistic regression. The predictive performance of the nomogram was validated internally through time-dependent receiver operating characteristic curves, calibration curves, and decision curve analysis.
Results:
Eyes from 103 patients under 20 years old and with CEL were enrolled in this study. Z score of body mass index (odds ratio [OR] = 0.659; 95% confidence interval [CI], 0.453-0.958), corneal curvature radius (OR = 3.397; 95% CI, 1.829-6.307), and aortic root diameter (OR = 2.342; 95% CI, 1.403-3.911) were identified as predictors of MFS. The combination of the above predictors shows good predictive ability, as indicated by area under the curve of 0.889 (95% CI, 0.826-0.953). The calibration curves showed good agreement between the prediction of the nomogram and the actual observations. In addition, decision curve analysis showed that the nomogram was clinically useful and had better discriminatory power in identifying patients with MFS. For better individual prediction, an online MFS calculator was created.
Conclusions:
The nomogram provides accurate and individualized prediction of MFS in children with CEL who cannot be identified with the Ghent criteria, enabling clinicians to personalize treatment plans and improve MFS outcomes.
Translational Relevance:
The prediction model may help clinicians identify MFS in its early stages, which could reduce the likelihood of developing severe symptoms and improve MFS outcomes.
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