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American Journal of Epidemiology Vol. 151, No. 10: 965-974
Copyright © 2000 by The Johns Hopkins University School of Hygiene and Public Health

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Methods to Quantify the Relation between Disease Progression in Paired Eyes

Robert J. Glynn1, and Bernard Rosner2

1Division of Preventive Medicine, Brigham and Women's Hospital and Harvard Medical School, and Department of Biostatistics, Harvard School of Public Health Boston, MA
2Channing Laboratory, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, and Department of Biostatistics, Harvard School of Public Health Boston, MA

For information on the authors' Fortran program, contact Dr. Robert J. Glynn, Division of Preventive Medicine, Brigham and Women's Hospital, 900 Commonwealth Avenue East, Boston, MA 02215-1204 (e-mail: rglynn@rics.bwh.harvard.edu).

The authors compared, in the context of diabetic retinopathy, alternative methods of quantifying the extent to which disease progression in one eye increases the risk of subsequent progression in the other eye. Data were gathered on 478 US patients with insulin-dependent diabetes mellitus who participated in the 1983–1988 Sorbinil Retinopathy Trial and were followed up for a median of 41 months. During that time, diabetic retinopathy progressed in 93 right eyes and 77 left eyes. Crude incidence rates of progression for right eyes were 7.7 times higher after the left eye had progressed and, for left eyes, were 4.4 times higher after the right eye had progressed. In eye-specific proportional hazards models that adjusted for increasing rates of progression over time and for baseline risk factors, the comparable relative risks associated with progression in the other eye were 2.6 (95% confidence interval (Cl): 1.5, 4.7) for right eyes and 1.4 (95% Cl: 0.72, 2.9) for left eyes. Two alternative proportional hazards models that included data on both eyes and accounted for their correlation produced estimated relative risks of 1.9 (95% Cl: 1.2, 2.9) and 2.7 (95% Cl: 1.8, 3.5), respectively. The more complex models for joint survival integrate information on both eyes and provide more stable estimates than do separate analyses of right or left eyes. Am J Epidemiol 2000; 151: 965-74.

diabetes mellitus, insulin-dependent; epidemiologic methods; eye diseases; models, statistical; regression analysis; survival analysis


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