Glaucoma in large-scale population-based epidemiology: a questionnaire-based proxy

Abstract

Purpose To improve upon self-reported glaucoma status in population-based cohorts by developing a questionnaire-based proxy incorporating self-reported status in conjunction with glaucoma-specific visual complaints. Methods A vision specific questionnaire, including questions from the National Eye Institute Visual Functioning Questionnaire-25 (NEI-VFQ-25) was administered to 79,866 Lifelines participants, a population-based cohort study in the Northern Netherlands. We compared NEI-VFQ-25 responses between 'definite' glaucoma cases (n = 90; self-reported surgical cases) and an age-and gender-matched subset of controls (n = 1,800) to uncover glaucoma-specific visual complaints, using a case-control logistic regression. We defined 'probable glaucoma' as both self-reported disease status and visual complaints, and 'possible glaucoma' as either. To evaluate the resulting proxy, we determined age-stratified glaucoma prevalences in the remaining cohort and compared the result to the literature. Results Per unit increase in the vision subscales (range 0-100) distance, peripheral and low luminance, we observed significantly increased odds of definite glaucoma (2% [P = 0.03], 4% [P = 1.2 × 10 −8 ] and 2% [P = 0.02], respectively); the associated area under the curve was 0.73. We identified 300 probable and 3,015 (1,434 by self-report) possible glaucoma cases. Standardised prevalences of definite, probable and possible glaucoma for 55+ were 0.4%, 1.1% and 7.3%, respectively. For self-reported glaucoma (combining definite, probable and possible by self-report), this was 5.2%. Conclusions The combination of self-reported glaucoma status and visual complaints can be used to capture glaucoma cases in population-based settings. The resulting prevalence of combined definite and probable glaucoma (1.5%) appears to be more consistent with previous reports than the prevalence estimate of 5.2% based only on self-report.

Autonomic Dysfunction and Blood Pressure in Glaucoma Patients: The Lifelines Cohort Study

“…We used a previously described algorithm for defining glaucoma in LifeLines, 36 which was based on self-report of glaucoma diagnosis and treatment in combination with the NEI-VFQ-25 33 (for details, see Neustaeter et al 36 ). In short, this algorithm classifies participants as definite , probable , or possible glaucoma cases, or as healthy.…”

Repurposing Antihypertensive Drugs for the Prevention of Glaucoma: A Mendelian Randomization Study

“… 19 , 36 Self-reported disease status may miss some suspected cases of glaucoma and mistakenly include some cases of ocular hypertension. 37 – 40 Second, the number of instrumental variables for glaucoma is slightly small, and the heritability to explain glaucoma is limited. Third, our results only apply to European lineages, and the effect of BP on glaucoma in other lineages remains to be studied.…”

Evaluating machine learning classifiers for glaucoma referral decision support in primary care settings

“…Self-reporting of glaucoma diagnosis is a limitation; it may be subject to inaccuracies due to the lack of a widely accepted method of confirming diagnosis, the associated potential for misdiagnosis from a provider, and/or misunderstanding of a diagnosis (or lack thereof) by the patient. However, self-reported glaucoma status has been regularly used in previous studies 46 – 48 , and its usefulness and performance has been explored 49 .…”