Clinical Ocular Diagnostic Model of Marfan Syndrome in Patients With Congenital Ectopia Lentis by Pentacam AXL System

Tianhui Chen, Jiahui Chen, Guangming Jin, Min Zhang, Zexu Chen, Danying Zheng, Yongxiang Jiang, Tianhui Chen, Jiahui Chen, Guangming Jin, Min Zhang, Zexu Chen, Danying Zheng, Yongxiang Jiang

Abstract

Purpose: To construct an ocular diagnostic model of Marfan syndrome (MFS) distinguishing MFS from congenital ectopia lentis by the Pentacam AXL system.

Methods: Multivariable logistic regression was performed for the MFS ocular model. Furthermore, discrimination and calibration were validated externally. Data for 96 patients with ectopia lentis were assigned to the training cohort. Eighty patients with ectopia lentis were assigned to the test cohort. Diagnosis of MFS was based on the Ghent-2 criteria and diagnosis of congenital ectopia lentis in the control did not comply with the Ghent-2 criteria.

Results: The clinical model was based on the axial length/total corneal refractive power ratio. In the training cohort, the area under the receiver operating characteristic curve was 0.816 (95% confidence interval, 0.754-0.878) in the final model, which showed better performance than the previous minor criteria for diagnosis MFS of myopia of more than 3 diopters. In the test cohort, the area under the receiver operating characteristic curve was 0.818 (95% confidence interval, 0.718-0.918). In decision curve analysis, the net benefit of the model was better between threshold probabilities of 40% to 80%.

Conclusions: We demonstrated the value of the axial length/total corneal refractive power ratio as a potential diagnostic marker of MFS and clinical performance of diagnostic models, which may assist ophthalmologists in rapid identification of the patients at high risk of MFS.

Translational relevance: This clinical ocular diagnostic model can be easily applied using the Pentacam AXL system. This model aids in the early differential diagnosis of MFS from other forms of congenital ectopia lentis, which may decrease the risk of developing severe ocular symptoms.

Conflict of interest statement

Disclosure: T. Chen, None; J. Chen, None; G. Jin, None; M. Zhang, None; Z. Chen, None; D. Zheng, None; Y. Jiang, None

Figures

Figure 1.
Figure 1.
Study flow diagram.
Figure 2.
Figure 2.
Nomogram to predict the probability of MFS in a patient with congenital ectopia lentis. By drawing a line straight downward from the AL/TCRP ratio axis to the diagnostic possibility axis, the corresponding point on the diagnostic possibility axis represents the probability risk of MFS. For example, if a patient's AL/TCRP ratio is 65, the straight line drawn downwards to the axis of the diagnostic possibility shows their probability of MFS is 78% and a thorough examination is recommended for a definitive diagnosis.
Figure 3.
Figure 3.
Calibration curve and ROC curve. (A) Calibration curve of the training cohort. The solid curve represents the relationship between the predicted and observed probabilities of MFS diagnosis. The ideal calibration is the represented by the solid curve that fits the gray line exactly. (B) Calibration curve of the test cohort. (C) ROC curve of the training cohort. The black curve of the new model is above the red curve of the myopia >−3D model. The AUC of the new model is 0.816 (95% CI, 0.754–0.878), whereas the AUC of the myopia >−3D is 0.567 (95% CI, 0.484–0.65). (D) ROC curve of the test cohort. The AUC of the new model in the test cohort is 0.818 (95% CI, 0.718–0.98). An AUC equal to 0.5 indicates no discrimination, whereas an AUC equal to 1.0 shows perfect discrimination.
Figure 4.
Figure 4.
Decision curve analysis. (A) Training cohort. The net benefit of the new model between the threshold probabilities of 40% to 80% is obviously better than that of the myopia >−3D, because its curve is significantly lower than that of the new model. (B) Test cohort.

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