Browsing by Author "Marín-Franch, Iván"

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    Prediction accuracy of a novel dynamic structure-function model for glaucoma progression
    (Association for Research in Vision and Opthalmology, 2014-12) Hu, Rongrong; Marín-Franch, Iván; Racette, Lyne; Department of Ophthalmology, IU School of Medicine
    PURPOSE: To assess the prediction accuracy of a novel dynamic structure-function (DSF) model to monitor glaucoma progression. METHODS: Longitudinal data of paired rim area (RA) and mean sensitivity (MS) from 220 eyes with ocular hypertension or primary open-angle glaucoma enrolled in the Diagnostic Innovations in Glaucoma Study or the African Descent and Glaucoma Evaluation Study were included. Rim area and MS were expressed as percent of mean normal based on an independent dataset of 91 healthy eyes. The DSF model uses centroids as estimates of the current state of the disease and velocity vectors as estimates of direction and rate of change over time. The first three visits were used to predict the fourth visit; the first four visits were used to predict the fifth visit, and so on up to the 11th visit. The prediction error (PE) was compared to that of ordinary least squares linear regression (OLSLR) using Wilcoxon signed-rank test. RESULTS: For predictions at visit 4 to visit 7, the average PE for the DSF model was significantly lower than OLSLR by 1.19% to 3.42% of mean normal. No significant difference was observed for the predictions at visit 8 to visit 11. The DSF model had lower PE than OLSLR for 70% of eyes in predicting visit 4 and approximately 60% in predicting visits 5, 6, and 7. CONCLUSIONS: The two models had similar prediction capabilities, and the DSF model performed better in shorter time series. The DSF model could be clinically useful when only limited follow-ups are available. (ClinicalTrials.gov numbers, NCT00221923, NCT00221897.).
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    Prediction Accuracy of the Dynamic Structure-Function Model for Glaucoma Progression Using Contrast Sensitivity Perimetry and Confocal Scanning Laser Ophthalmoscopy
    (Wolters Kluwer, 2018-09) Ramezani, Koosha; Marín-Franch, Iván; Hu, Rongrong; Swanson, William H.; Racette, Lyne; Ophthalmology, School of Medicine
    PURPOSE: The purpose of this study was to determine whether combining a structural measure with contrast sensitivity perimetry (CSP), which has lower test-retest variability than static automated perimetry (SAP), reduces prediction error with 2 models of glaucoma progression. METHODS: In this retrospective analysis, eyes with 5 visits with rim area (RA), SAP, and CSP measures were selected from 2 datasets. Twenty-six eyes with open-angle glaucoma were included in the analyses. For CSP and SAP, mean sensitivity (MS) was obtained by converting the sensitivity values at each location from decibel (SAP) or log units (CSP) to linear units, and then averaging all values. MS and RA values were expressed as percent of mean normal based on independent normative data. Data from the first 3 and 4 visits were used to calculate errors in prediction for the fourth and fifth visits, respectively. Prediction errors were obtained for simple linear regression and the dynamic structure-function (DSF) model. RESULTS: With linear regression, the median prediction errors ranged from 6% to 17% when SAP MS and RA were used and from 9% to 17% when CSP MS and RA were used. With the DSF model, the median prediction errors ranged from 6% to 11% when SAP MS and RA were used and from 7% to 16% when CSP MS and RA were used. CONCLUSIONS: The DSF model had consistently lower prediction errors than simple linear regression. The lower test-retest variability of CSP in glaucomatous defects did not, however, result in lower prediction error.