Ophthalmic research · 2016
Risk Prediction Model for Progression of Age-Related Macular Degeneration.
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Shin Ko Un, Song Su Jeong, Bae Jeong Hun, Lee Mi Yeon
Аннотация
AIMS: The aim of this paper was to develop a risk prediction model for the progression of age-related macular degeneration (AMD) in Koreans using systemic and environmental factors.
METHODS: The study sample included 10,890 individuals 50 years of age or older; 318 (2.92%) presented with early AMD findings in baseline examinations. Re-examinations were performed in 157 (49.37%) who were followed up for 4.4 years. The multivariate analysis of covariates included demographic and environmental factors. After using these data to develop a risk prediction model, the individual algorithm was made, and receiver operating characteristic curves were calculated to assess the predictive ability of the risk model for AMD progression.
RESULTS: The individual algorithm to predict the AMD progression risk based on systemic and ocular factors was as follows: Y = -9.565 + 1.709 (drusen locationcenter) + 0.795 (drusen locationparacentral) + 1.074 (both eyes) + 0.094 (drusen sizeintermediate) + 0.034 (drusen sizelarge) + 0.614 (drusen number10-20) + 2.278 (drusen number>20) + 0.577 (hyperpigmentation) + 0.725 (hypopigmentation) + 0.079 (male) - 0.025 (age) - 0.921 (SMKex) + 1.574 (SMKcurrent) + 0.363 (total protein) + 1.626 (globulin), where SMK means smoking status. The C statistics for the model was 0.84 (0.75-0.92) indicating a good predictive power.
CONCLUSION: A comprehensive risk prediction model for AMD progression was made to calculate the individual AMD progression risk using personal systemic and environmental factors.
METHODS: The study sample included 10,890 individuals 50 years of age or older; 318 (2.92%) presented with early AMD findings in baseline examinations. Re-examinations were performed in 157 (49.37%) who were followed up for 4.4 years. The multivariate analysis of covariates included demographic and environmental factors. After using these data to develop a risk prediction model, the individual algorithm was made, and receiver operating characteristic curves were calculated to assess the predictive ability of the risk model for AMD progression.
RESULTS: The individual algorithm to predict the AMD progression risk based on systemic and ocular factors was as follows: Y = -9.565 + 1.709 (drusen locationcenter) + 0.795 (drusen locationparacentral) + 1.074 (both eyes) + 0.094 (drusen sizeintermediate) + 0.034 (drusen sizelarge) + 0.614 (drusen number10-20) + 2.278 (drusen number>20) + 0.577 (hyperpigmentation) + 0.725 (hypopigmentation) + 0.079 (male) - 0.025 (age) - 0.921 (SMKex) + 1.574 (SMKcurrent) + 0.363 (total protein) + 1.626 (globulin), where SMK means smoking status. The C statistics for the model was 0.84 (0.75-0.92) indicating a good predictive power.
CONCLUSION: A comprehensive risk prediction model for AMD progression was made to calculate the individual AMD progression risk using personal systemic and environmental factors.