Evaluating the Impact of Therapy on Quality of Life in Type 2 Diabetes: A Literature Review of Utilities Associated with Treatment-Related Attributes

INTRODUCTION: Treatment-related attributes and process characteristics such as dosing frequency, timing flexibility, ease of use of injection devices and unpleasant side-effects may have small but measurable effects on quality of life (QoL) in people with type 2 diabetes (T2D). A literature review was performed to identify recently published utility values quantifying the effect of treatment-related attributes on QoL. METHODS: Literature search strategies were designed using high-level medical subject heading (MeSH) terms supplemented with free-text terms and searches were run in March 2020 in the PubMed, Embase and Cochrane Library databases. For inclusion, studies were required to be published in full-text form, in English, since 2010 and report utility values (elicited using either direct or indirect methods) for treatment-related attributes or process characteristics including side effects, change in weight/body mass index (BMI), dosing frequency and timing flexibility, device attributes (e.g. needle handling, requirement for reconstitution) and convenience (e.g. waiting time). RESULTS: A total of 30 studies were included in the review, of which all but three were conducted in people with T2D. The EQ-5D was the most commonly used elicitation method (fourteen studies), followed by time tradeoff (TTO) methodology. Treatment-related adverse events and inconveniences such as needle handling in administration devices and waiting time were consistently associated with lower QoL, whereas lower dosing frequency and increased timing flexibility with dosing were consistently associated with utility benefits. The relationship between change in BMI and QoL was non-linear and influenced by baseline BMI. CONCLUSION: Treatment-related attributes and process characteristics are associated with minor changes in QoL, which should be taken into account in long-term health economic modeling of new treatments and administration devices.