June 2017
Volume 58, Issue 8
Open Access
ARVO Annual Meeting Abstract  |   June 2017
Quality of Life Among Glaucoma Patients: Key Clinical and Demographic Variables
Author Affiliations & Notes
  • Lavanya Uruthiramoorthy
    Epidemiology and Biostatistics, University of Western Ontario, Markham, Ontario, Canada
  • Dan Lizotte
    Epidemiology and Biostatistics, University of Western Ontario, Markham, Ontario, Canada
  • Monali Malvankar
    Epidemiology and Biostatistics, University of Western Ontario, Markham, Ontario, Canada
  • Cindy Hutnik
    Ivey Eye Institute, London Health Sciences Centre, London, Ontario, Canada
  • Footnotes
    Commercial Relationships   Lavanya Uruthiramoorthy, None; Dan Lizotte, None; Monali Malvankar, None; Cindy Hutnik, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2017, Vol.58, 3742. doi:
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      Lavanya Uruthiramoorthy, Dan Lizotte, Monali Malvankar, Cindy Hutnik; Quality of Life Among Glaucoma Patients: Key Clinical and Demographic Variables. Invest. Ophthalmol. Vis. Sci. 2017;58(8):3742.

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      © ARVO (1962-2015); The Authors (2016-present)

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Abstract

Purpose : Measuring health-related quality of life (HRQoL) is useful for glaucoma management but burdensome for clinicians and patients. We performed a cross-sectional, observational study to identify which among a comprehensive set of commonly-measured clinical and demographic variables are most strongly associated with HRQoL in patients treated for glaucoma.

Methods : A cohort of glaucoma suspect and diagnosed glaucoma patients (N=250) were recruited from Ivey Eye Institute in London, Ontario from February to August 2016. Medical records were abstracted to collect clinical variables. In-person questionnaires were conducted to obtain patient demographics, Visual Function Questionnaire-25 (VFQ-25); Community Integration Questionnaire (CIQ); and utility scores as measured by the Time-Trade off (TTO) technique. Linear and logistic regression were used to estimate the effect of age, first line treatment, income, education, number of comorbidities, ocular conditions, ocular procedures, best corrected visual acuity (BCVA) and glaucoma stage in the worse-seeing eye. Ethics approval was obtained for this study.

Results : The mean composite score of the VFQ-25 was 88.73±12.4. Income greater than $50,000 (4.30±1.81, 95% CI=0.73 to 7.87, p=0.019), moderate visual acuity loss (-9.15±2.13, 95% CI=-13.36 to -4.94, p<0.001), legal blindness (-17.75±2.31, 95% CI=-22.39 to -13.20, p<0.001) and number of ocular conditions (1.71±0.71, 95% CI= -3.19 to -0.31, p=0.017) were significantly associated with the VFQ composite score. The average CIQ score of the patients was 17.9±4.99 out of a possible 29. Age (0.15±0.37, 95% CI=-0.22 to -0.07, p<0.001), income greater than $50,000 (2.38±0.80, 95% CI=0.80 to 3.97, p=0.003) and moderate visual acuity loss (-1.95±0.95, 95% CI=-3.81 to -0.08, p<0.041) were significantly associated with the CIQ score. On average, patients had a TTO utility score of 0.91±0.18, representing a high preference-based HRQoL. Age (OR=1.04, 95% CI=1.00 to 1.08, p=0.048), first line treatment (OR=2.56, 95% CI=1.12 to 5.88, p=0.026) and number of ocular conditions (OR=1.49, 95% CI=1.08 to 2.05, p=0.014) were significantly associated with the TTO utility score.

Conclusions : Age, income, BCVA and number of ocular conditions were significantly associated with at least two of the three HRQoL measures. These variables hold the most promise for developing an algorithm to predict HRQoL.

This is an abstract that was submitted for the 2017 ARVO Annual Meeting, held in Baltimore, MD, May 7-11, 2017.

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