OBJECTIVES: The aim of this study was to develop and validate mapping algorithms to predict EQ-5D-5L utilities from two questionnaires (Functional Assessment of Anorexia/Cachexia Treatment – 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 (NSCLC-C). METHODS: Data were collected at five occasions over a 12-week period in two multicenter, placebo-controlled trials (ROMANA 1 and ROMANA 2). The study sample was divided into development and validation datasets according to patient’s country of origin. Generalized estimating equations (GEEs) were performed to predict EQ-5D utilities from FACT-G, FAACT and FACIT-F scores. Five different sets of independent variables were tested 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). RESULTS: A subset of 96 patients completed both EQ-5D-5L and FAACT/FACIT-F questionnaires. Models using the individual domains separately yielded the lowest MAE/RMSE in most of study time points; however, even algorithms modeling the overall scores showed a high predictive performance. In FACT-G models, Physical Well-Being had the highest explanatory value (0.0094; p<0.001), while Emotional Well-Being did not significantly affect the EQ-5D score; Anorexia-Cachexia (0.0035; p=0.007) and Fatigue (0.0059; p<0.001) subscales were highly statistically significant in FAACT and FACIT-F models, respectively. The Eastern Cooperative Oncology Group status was the only covariate retained in the final models after backward selection. All the differences between mean observed and predicted EQ-5D utility were below the Minimal Important Difference (0.08) established in cancer for UK-index scores. CONCLUSIONS:  The developed algorithms enable the estimation of Quality-Adjusted Life Years (QALYs) from three cancer-specific instruments in cost-effectiveness analyses where EQ-5D data are missing. Further research evaluating model performance in an independent sample of NSCLC-C patients is encouraged.