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Are we blinded by standardisation?

  • Writer: Acaster Lloyd
    Acaster Lloyd
  • Aug 14
  • 3 min read
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by Arya Pimprikar and Andrew Lloyd


Health state utilities are important in determining the cost-effectiveness of new treatments. We recently conducted a systematic literature review with the aim to explore utility measurement approaches in advanced age-related macular degeneration (AMD), including geographic atrophy (GA) and how this was incorporated into cost-effectiveness modelling [1]. Our findings revealed quite substantial limitations in the available utility data and measures for vision disorders.


But first, some AMD basics. AMD is a progressive retinal disease that causes central vision loss. The disease has three distinct stages: early, intermediate and advanced AMD. Advanced AMD can manifest in two forms: wet AMD and dry AMD. GA is the advanced form of dry AMD that leads to central vision loss over time [2] (Figure 1).


Source: Bright Focus Foundation Programme
Source: Bright Focus Foundation Programme

GA interferes with daily activities such as driving, reading, writing and recognising faces, which in turn impacts patients’ quality of life, mobility, autonomy and independence. However, measuring the impact of vision loss on health-related quality of life (HRQoL) to support cost-effectiveness analyses is challenging [3].


Evidence suggests that generic preference-based measures such as the EQ-5D are not sensitive in capturing the burden of disease in vision disorders due to the under-representation of vision-specific items [4,5]. If EQ-5D scores don’t reflect differences between patients with different levels of vision loss, then this could impact upon patients' access to treatments. In our review, the EQ-5D was identified as one of the most commonly used instruments for utility elicitation in AMD [6,7]. Feedback from Health Technology Assessment (HTA) reviews suggest that they still prefer the Health Utilities Index-3 (HUI-3) or EQ-5D for measuring HRQL.


One alternative to measures like the HUI-3 and EQ-5D is the Visual Function Questionnaire-25 (VFQ-25), which is a vision-specific measure. A scoring algorithm can be used to generate utilities from the VFQ - utility index (VFQ-UI) and has demonstrated evidence of both known-groups8–11 and convergent validity [10-13]. Specifically, it was able to distinguish between individuals with GA, those with early or intermediate AMD, and those without [8-11]. 

Additionally, associations between the area of atrophy and vision-related quality of life (VRQoL) were found to be influenced by the location of the atrophy [10-13]. However, the VFQ-25 has not been widely used as a utility measure in cost-effectiveness analyses, despite being developed nearly 15 years ago. Other new vision-specific measures are also now being developed and validated (e.g., Vision Impairment in Low Luminance - Utility Index; VULL-UI and Visual Impairment Symptom Severity Assessment; VISSA-10) [14-16]. The EuroQol Group is also exploring the addition of a vision bolt-on to the EQ-5D.


One other issue to consider is whether vision should be looked at as simply a dimension of health. The loss of vision may have a substantial impact on a person that arguably goes beyond health. The loss of vision may changes individuals’ entire experience of the world and could have a considerable impact on their ability to undertake roles in life. Therefore, any treatment which can preserve or restore sight may need to be considered with additional weight beyond the Full health to Dead scale. 




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References


1. Williams, E., et al. Value in Health 27, S389 - S390. (2024)

2. Bakri, S. J. JMCP, 29(5-a Suppl), S2-S11 (2023)

3. Sarda, S. P. et alOphthalmol, 15, 4629-4644 (2021)

4. De, R. et alEye 35, 3333–3341 (2021).

5. Tosh, J., Brazier, J. Value in Health 15, 118–127 (2012).

6. Heier, J. S. et al. Ophthalmology 119, 2537–2548 (2012).

7. Lloyd, A. et alBr J Ophthalmol 103, 1610 (2019).

8. Patnaik, J. L. et al. Acta Ophthalmol 99, 750–755 (2021).

9. Patel, P. J. et al. Clinical Ophthalmology 14, 15–28 (2020).

10. Sivaprasad, S. et alAm J Ophthalmol 190, 1–8 (2018).

11. Burguera-Giménez, N. et alClinical Ophthalmology 14, 1533–1545 (2020).

12. Künzel, S. H. et al. Ophthalmol Retina 8, 794–803 (2024).

13. Ahluwalia, A. et al. Graefes Arch. 261, 699–708 (2023).

14. Sampson, C. et al. Value in Health 22, S733 (2019).

15. Rowen, D. et al. Value in Health 27, 642–654 (2024).

16. Morga, A. et al. Ophthalmol Ther 12, 1181–1193 (2023).

 
 
 

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