Predicting EQ-5D-5L crosswalk from the PROMIS-29 profile for the United Kingdom, France, and Germany

Abstract

Background EQ-5D health state utilities (HSU) are commonly used in health economics to compute quality-adjusted life years (QALYs). The EQ-5D, which is country-specific, can be derived directly or by mapping from self-reported health-related quality of life (HRQoL) scales such as the PROMIS-29 profile. The PROMIS-29 from the Patient Reported Outcome Measures Information System is a comprehensive assessment of self-reported health with excellent psychometric properties. We sought to find optimal models predicting the EQ-5D-5L crosswalk from the PROMIS-29 in the United Kingdom, France, and Germany and compared the prediction performances with that of a US model. Methods We collected EQ-5D-5L and PROMIS-29 profiles and three samples representative of the general populations in the UK (n = 1509), France (n = 1501), and Germany (n = 1502). We used stepwise regression with backward selection to find the best models to predict the EQ-5D-5L crosswalk from all seven PROMIS-29 domains. We investigated the agreement between the observed and predicted EQ-5D-5L crosswalk in all three countries using various indices for the prediction performance, including Bland–Altman plots to examine the performance along the HSU continuum. Results The EQ-5D-5L crosswalk was best predicted in France (nRMSEFRA = 0.075, nMAEFRA = 0.052), followed by the UK (nRMSEUK = 0.076, nMAEUK = 0.053) and Germany (nRMSEGER = 0.079, nMAEGER = 0.051). The Bland–Altman plots show that the inclusion of higher-order effects reduced the overprediction of low HSU scores. Conclusions Our models provide a valid method to predict the EQ-5D-5L crosswalk from the PROMIS-29 for the UK, France, and Germany.

Protocol for a multicenter, randomised controlled trial of surgeon-directed home therapy vs. outpatient rehabilitation by physical therapists for reverse total shoulder arthroplasty: the SHORT trial

“…To analyze quality of life and cost-effectiveness differences between the PT and HT groups, two formal steps will be followed. Step one will involve a crosswalk of PROMIS 29.2 measures to EQ5D quality of life measures, [ 49 ] which is a standardized utility measure. Utilities are measured on a cardinal scale of 0–1, where 0 indicates death and 1 indicates full health.…”

“…EQ5D = (1.0266+0.0077) X (PROMIS physical functioning t score -0.0021) X (PROMIS fatigue t score – 0.0040) X (PROMIS pain interference t score – 0.0023) X (PROMIS anxiety t score-0.0022) x (PROMIS depression t score) [ 49 ]…”

“…Step one will involve a crosswalk of PROMIS 29.2 measures to EQ5D quality of life measures, [49] which is a standardized utility measure. Utilities are measured on a cardinal scale of 0-1, where 0 indicates death and 1 indicates full health.…”

“…We will use the formula by Revicki and colleagues to complete the crosswalk [51]. EQ5D = (1.0266+0.0077) X (PROMIS physical functioning t score -0.0021) X (PROMIS fatigue t score -0.0040) X (PROMIS pain interference t score -0.0023) X (PROMIS anxiety t score-0.0022) x (PROMIS depression t score) [49] The formulaic calculations will result in a quality -adjusted life year value (QALY). QALY's reflect two key elements-health related quality of life and survival.…”

Validity, reliability, and ceiling and floor effects of the PROMIS Preference score (PROPr) in patients with rheumatological and psychosomatic conditions

“…A ceiling effect can be expressed as u(SOC) ⟶ 1, and consequently, ∆u ⟶ 0 and ICER⟶ ∞, resulting in denial of reimbursement and limiting patient access to new treatments. Furthermore, when condition-specific instruments are used for assessment, mapping is needed to predict HSU, resulting in further loss in precision, exacerbating the impact on the ICER (15)(16)(17).…”