Mapping health-related quality of life scores from FACT-G, FAACT, and FACIT-F onto preference-based EQ-5D-5L utilities in non-small cell lung cancer cachexia

Abstract

BackgroundHealth-related quality of life (HRQoL) measurements from disease-specific tools cannot be directly used in economic evaluations. This study aimed to develop and validate mapping algorithms that predicted EuroQol 5-Dimensions 5-Levels (EQ-5D-5L) utilities from Functional Assessment of Anorexia-Cachexia Therapy (FAACT) and Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F) and their common component (Functional Assessment of Cancer Therapy-General—FACT-G) in patients with non-small cell lung cancer cachexia.MethodsData were collected on five occasions over a 12-week period in two multicenter placebo-controlled trials. EQ-5D-5L utilities were calculated using both English and Dutch value sets. The study sample was divided into development and validation datasets according to patients’ geographical residence. Generalized estimating equations were applied to five different sets of independent variables including overall, Trial Outcome Index (TOI), and individual subscales results. The best performing models were selected based on mean absolute error (MAE) and root-mean square error (RMSE).ResultsEQ-5D-5L and FAACT/FACIT-F results were available for 96 patients. The developed algorithms showed a good predictive performance, with acceptable MAE/RMSE and small differences between mean observed and predicted EQ-5D-5L utilities. In FACT-G models, Physical Well-Being had the highest explanatory value, while Emotional Well-Being did not significantly affect the EQ-5D-5L score; Anorexia-Cachexia and Fatigue subscales were highly statistically significant in FAACT and FACIT-F models, respectively, as well as the TOI scores. The Eastern Cooperative Oncology Group status was included as covariate in all models.ConclusionThe developed algorithms enable the estimation of EQ-5D-5L utilities from three cancer-specific instruments when preference-based HRQoL data are missing.