Health-Related Quality of Life Scores and Values as Predictors of Mortality: A Scoping Review

Abstract

Health-related quality of life (HRQoL) can be assessed through measures that can be generic or disease specific, encompass several independent scales, or employ holistic assessment (i.e., the derivation of composite scores). HRQoL measures may identify patients with differential risk profiles. However, the usefulness of generic and holistic HRQoL measures in identifying patients at higher risk of death is unclear. The aim of the present study was to undertake a scoping review of generic, holistic assessments of HRQoL as predictors of mortality in general non-patient populations and clinical sub-populations with specified conditions or risk factors in persons 18 years or older. Five databases were searched from 18 June to 29 June 2020 to identify peer-reviewed published articles. The searches were updated in August 2022. Reference lists of included and cited articles were also searched. Of 2552 articles screened, 110 met criteria for inclusion. Over one-third of studies were from North America. Most studies pertained to sub-populations with specified conditions and/or risk factors, almost a quarter for people with cardiovascular diseases. There were no studies pertaining to people with mental health conditions. Nearly three-quarters of the studies used a RAND Corporation QoL instrument, predominantly the SF-36, and nearly a quarter, a utility instrument, predominantly the EQ-5D. HRQoL was associated with mortality in 67 of 72 univariate analyses (92%) and 100 of 109 multivariate analyses (92%). HRQoL was found to be associated with mortality in the general population and clinical sub-populations with physical health conditions. Whether this relationship holds in people with mental health conditions is not known. HRQoL assessment may be useful for screening and/or monitoring purposes to understand how people perceive their health and well-being and as an indicator of mortality risk, encouraging better-quality and timely patient care to support and maximize what may be a patient's only modifiable outcome.

Keywords: health states; health-related quality of life; mortality; predictive model; utility.

Fig. 1

Prisma diagram of study selection.

Fig. 2

Bubble plots of univariate and multivariate predictions of mortality by study population and instrument employed, for identified relationships. Legend: The size of a bubble is proportional to the number of prediction of mortality in the population group and instrument corresponding to the bubble coordinates, reported in the articles included in the review. 15D, 15-Dimensional instrument; ED, emergency department; EQ-5D, EuroQol five dimensions questionnaire; HUI3, Health Utilities Index Mark 3; ICU, intensive care unit; MCS, mental component score; NHP, Nottingham Health Profile; PCS, physical component score; pEQ-5D, predicted EQ-5D; SF-12, Short Form Health Survey 12-Item; SF-36, SF 36-Item; SF-6D, SF Six-Dimension; VAS, visual analogue scale. *Including veterans. ^†Including dialysis and haemodialysis.