June 2020
Volume 61, Issue 7
Open Access
ARVO Annual Meeting Abstract  |   June 2020
Using Discrete Choice Analysis to Model Patient Decision-Making for Ocular Stem Cell Therapies
Author Affiliations & Notes
  • Peter Y Zhao
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Paula Anne Newman-Casey
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Chris A Andrews
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Angeline Lonardi
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Sunjong Ji
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Olivia Bennett
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Duyhoang Dinh
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Nidhi Talwar
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • David W Hutton
    University of Michigan, Michigan, United States
  • Rajesh C Rao
    Kellogg Eye Center, Ann Arbor, Michigan, United States
  • Footnotes
    Commercial Relationships   Peter Zhao, None; Paula Anne Newman-Casey, None; Chris Andrews, None; Angeline Lonardi, None; Sunjong Ji, None; Olivia Bennett, None; Duyhoang Dinh, None; Nidhi Talwar, None; David Hutton, None; Rajesh Rao, None
  • Footnotes
    Support  None
Investigative Ophthalmology & Visual Science June 2020, Vol.61, 869. doi:
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    • Get Citation

      Peter Y Zhao, Paula Anne Newman-Casey, Chris A Andrews, Angeline Lonardi, Sunjong Ji, Olivia Bennett, Duyhoang Dinh, Nidhi Talwar, David W Hutton, Rajesh C Rao; Using Discrete Choice Analysis to Model Patient Decision-Making for Ocular Stem Cell Therapies. Invest. Ophthalmol. Vis. Sci. 2020;61(7):869.

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

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Abstract

Purpose : Patient perspectives on stem cell therapy and regenerative medicine are not well understood despite the proliferation of stem cell research and unproven stem cell treatments. Using a discrete choice survey, we tested the hypothesis that patients given the option of a theoretical stem cell treatment would value the potential benefit of restoring vision despite the unique potential risk of cancer in the eye.

Methods : An in-person survey was read aloud to patients at an academic medical center. The survey included discrete choice questions asking patients to choose between two options. Each option had a level of visual acuity (20/20, 20/40, 20/70, 20/100, 20/200, each with a description of typical visual function) and a level of cancer risk (1%, 5%, 20%). The survey included the Abbreviated National Eye Institute Visual Function Questionnaire (VFQ-9). Demographic and clinical characteristics were abstracted from the medical record. A conditional logistic regression model was used to determine part-worth estimates of utility and the effects of patient variables.

Results : 178 of 243 patients approached completed the survey (73% response rate). Mean age was 62.2 (SD=17.9) and mean visual acuity was logMAR 0.4 (SD=0.7), equivalent to Snellen 20/50. Mean VFQ-9 score was 72.5 (SD=19.4). Estimates of utility for visual acuity were: 20/20, 2.36 (SE=0.21); 20/40, 2.31 (SE=0.18); 20/70, 1.60 (SE=0.14); 20/100, 0.36 (SE=0.12); and 20/200, 0 (reference). Estimates of utility for risk of cancer were 1%, 0.63 (SE=0.14); 5%, 0.84 (SE=0.10); and 20%, 0 (reference). The greatest changes in utility of visual acuity occurred at the 20/40-20/70 and 20/70-20/100 levels. Relative importance of visual acuity was 71%, and relative importance of risk of cancer was 29%. Higher VFQ-9 score correlated with greater importance of visual acuity (p<0.01), and greater age correlated with less importance of risk of cancer (p<0.05).

Conclusions : Patients placed substantial value on visual acuity when asked to make trade-offs between levels of visual acuity and risk of cancer. Individual factors such as age and VFQ-9 score affect decision-making. Confirmatory studies on a larger, national cohort would improve ophthalmologists’ and scientists’ understanding of the drivers of patient decision-making, allowing for more personalized clinical care and clinical trials.

This is a 2020 ARVO Annual Meeting abstract.

 

 

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