Hui Zhang1,2, Xue Zhang1, Lin Hua1,3, Lin Li1,3, Lei Tian4,5, Xinxin Zhang6, Haixia Zhang7,8. 1. School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China. 2. Department of Medical Engineering, Peking Union Medical College Hospital, Chinese Academy of Medical Sciences, Beijing, 100730, China. 3. Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China. 4. Beijing Tongren Eye Center, Beijing Key Laboratory of Ophthalmology and Visual Sciences, Beijing Institute of Ophthalmology, Beijing Tongren Hospital, Capital Medical University, Beijing, 100730, China. 5. Beijing Advanced Innovation Center for Big Data-Based Precision Medicine, Beijing Tongren Hospital, Beihang University & Capital Medical University, Beijing, 100730, China. 6. School of Statistics, Capital University of Economics and Business, Beijing, 100070, China. 7. School of Biomedical Engineering, Capital Medical University, Beijing, 100069, China. Zhanghx@ccmu.edu.cn. 8. Beijing Key Laboratory of Fundamental Research on Biomechanics in Clinical Application, Capital Medical University, Beijing, 100069, China. Zhanghx@ccmu.edu.cn.
Abstract
PURPOSE: To secondary statistical analysis of the Pentacam or Corvis ST parameters from literatures, and to obtain more sensitive diagnostic parameters for clinical keratoconus (CKC) and forme fruste keratoconus (FFKC), respectively. METHODS: The parameters and the corresponding area of ROC curve (AUC) in previous studies were extracted and screened to obtain the database of CKC (Data-CKC) and FFKC (Data-FFKC), respectively. Two different importance evaluation methods (%IncMSE and IncNodePurity) of random forest were used to preliminary select the important parameters. Then, based on the partial dependency analysis, the sensitive diagnostic parameters that had promotion to the diagnostic performance were obtained. Data-FFKC was analyzed in the same way. Finally, a diagnostic test meta-analysis on the sensitive parameter of interest was conducted to verify the reliability of the above analysis methods. RESULTS: There were 88 parameters with 766 records in Data-CKC, 57 parameters with 346 records in Data-FFKC. Based on two importance evaluation methods, 60 important parameters were obtained, of which 20 were further screened as sensitive parameters of keratoconus, and most of these parameters were related to the thinnest point of cornea. The stiffness parameter at first applanation (SPA1) was the only Corvis ST output parameter sensitive to FFKC except the Tomographic and Biomechanical Index and the Corvis Biomechanical Parameter (CBI). A total of 4 records were included in the meta-analysis of diagnostic tests on SPA1. The results showed that there was threshold effect, but no significant heterogeneity (I2 = 33%), and the area under the SROC curve was 0.87 (95% CI, 0.84-0.90). CONCLUSIONS: For the diagnosis of FFKC, the sensitivity of SPA1 is not inferior to the well-known CBI, and may be the earliest Corvis ST output parameter to reflect the changes of corneal biomechanics during keratoconus progression. The elevation parameters based on the typical position of the thinnest point of corneal thickness are of great significance for the diagnosis of keratoconus.
PURPOSE: To secondary statistical analysis of the Pentacam or Corvis ST parameters from literatures, and to obtain more sensitive diagnostic parameters for clinical keratoconus (CKC) and forme fruste keratoconus (FFKC), respectively. METHODS: The parameters and the corresponding area of ROC curve (AUC) in previous studies were extracted and screened to obtain the database of CKC (Data-CKC) and FFKC (Data-FFKC), respectively. Two different importance evaluation methods (%IncMSE and IncNodePurity) of random forest were used to preliminary select the important parameters. Then, based on the partial dependency analysis, the sensitive diagnostic parameters that had promotion to the diagnostic performance were obtained. Data-FFKC was analyzed in the same way. Finally, a diagnostic test meta-analysis on the sensitive parameter of interest was conducted to verify the reliability of the above analysis methods. RESULTS: There were 88 parameters with 766 records in Data-CKC, 57 parameters with 346 records in Data-FFKC. Based on two importance evaluation methods, 60 important parameters were obtained, of which 20 were further screened as sensitive parameters of keratoconus, and most of these parameters were related to the thinnest point of cornea. The stiffness parameter at first applanation (SPA1) was the only Corvis ST output parameter sensitive to FFKC except the Tomographic and Biomechanical Index and the Corvis Biomechanical Parameter (CBI). A total of 4 records were included in the meta-analysis of diagnostic tests on SPA1. The results showed that there was threshold effect, but no significant heterogeneity (I2 = 33%), and the area under the SROC curve was 0.87 (95% CI, 0.84-0.90). CONCLUSIONS: For the diagnosis of FFKC, the sensitivity of SPA1 is not inferior to the well-known CBI, and may be the earliest Corvis ST output parameter to reflect the changes of corneal biomechanics during keratoconus progression. The elevation parameters based on the typical position of the thinnest point of corneal thickness are of great significance for the diagnosis of keratoconus.