What Is a Valid Mapping Algorithm in Cost-Utility Analyses? A Response From a Missing Data Perspective

Development of algorithms to estimate the EQ-5D-5L from the FACT-L in patients with lung cancer: a mapping study

OBJECTIVE

This study aimed to develop a mapping algorithm to evaluate the EQ-5D-5L according to the FACT-L when the EQ-5D-5L is not available.

METHODS

EQ-5D-5L and FACT-L data were collected from patients with lung cancer in Departments of Thoracic Surgery, Medical Oncology, Radiation Oncology, Sichuan Cancer Hospital. We used the ordinary least squares model (OLS), Tobit model (Tobit), two-part model (TPM), beta mixture regression (BM), and censored least absolute deviation model (CLAD) to map the results of the FACT-L according to EQ-5D-5L scores. To establish these models, the total score, dimension scores, squared items, and interaction items were introduced. Performance metrics including Adjusted R2, root mean square error (RMSE), and mean absolute error (MAE) were used to select the optimized model.

RESULTS

The model with the best mapping performance was the BM model (BETAMIX4) with the PWB (physical well-being) dimension, FWB (functional well-being) dimension, the squared term of the PWB dimension, and the squared term of the FWB dimension as covariates. The final prediction metrics were Adjusted R2 = 0.695, RMSE = 0.206, and MAE = 0.109. Fivefold cross-validation (CV) results also demonstrated that the BM model had the best mapping power.

CONCLUSIONS

This study developed an optimized mapping algorithm to predict the utility index from the FACT-L to the EQ-5D-5L, which provides an effective alternative reference for EQ-5D-5L estimation when the preference-based health utility values were unavailable.

Estimating health related quality of life effects in vitiligo. Mapping EQ-5D-5 L utilities from vitiligo specific scales: VNS, VitiQoL and re-pigmentation measures using data from the HI-Light trial

BACKGROUND

Vitiligo is reported to affect 2% of the world's population and has a significant impact on health related quality of life (HRQoL). The relationship between HRQoL and clinical outcomes used in vitiligo require further examination. Mapping condition specific measures of HRQoL: vitiligo specific quality of life instrument (VitiQoL), vitiligo noticeability scale (VNS) and vitiligo re-pigmentation scores (RPS) to the EQ-5D have not yet been reported.

METHODS

Data collected from a randomised clinical trial (HI-Light) in vitiligo was used to develop mapping algorithms for the EQ-5D-5 L and the relationship between HRQoL, clinical outcomes and EQ-5D were investigated. Two EQ-5D-5 L value sets (Van Hout and Alava) using linear and non-linear models were considered. Logistic regression models were used to model the probability of vitiligo noticeability (VNS) in terms of RPS, EQ-5D and VitiQoL scores.

RESULTS

Mapping from RPS appeared to perform better followed by VNS for the Alava crosswalks using polynomial models: Mean observed vs. predicted utilities of 0.9008 (0.005) vs. 0.8984 (0.0004) were observed for RPS. For VNS, mean observed vs. predicted utilities of 0.9008 (0.005) vs. 0.8939 (0.0003) were observed. For VitiQoL, mean observed vs. predicted utilities of 0.9008 (0.005) vs. 0.8912 (0.0002) were observed. For patients with the least re-pigmentation (RPS < 25%), a Total VitiQoL score of about 20 points gives around an 18% chance of vitiligo being no longer or a lot less noticeable.

CONCLUSION

The algorithm based on RPS followed by VNS performed best. The relationship between effects from vitiligo specific HRQoL instruments and clinical RPS was established allowing for plausible clinically relevant differences to be identified, although further work is required in this area.

Mapping the Seattle Angina Questionnaire to EQ-5D-5L in patients with coronary heart disease

BACKGROUND

Health economic evaluation is critical in supporting novel cardiovascular disease therapies. However, most clinical studies do not include preference-based questionnaires to calculate utilities for health economic evaluations. Thus, this study aimed to develop mapping algorithms that convert the Seattle Angina Questionnaire (SAQ) to EQ-5D-5L health utility scores for patients with coronary health disease (CHD) in China.

METHODS

Data were obtained from a longitudinal study of patients with CHD conducted at the Tianjin Medical University General Hospital in China. Convenience sampling was used to recruit patients with CHD. The inclusion criteria were having been diagnosed with CHD through a medical examination and being aged 18 years or older. The exclusion criteria were a lack of comprehension ability, serious comorbidities, mental illness, and hearing or vision impairment. All eligible patients were invited to participate, and 305 and 75 patients participated at baseline and in the follow-up, respectively. Seven regression models were developed using a direct approach. Furthermore, we predicted the five EQ-5D items using ordered logit model and derived the utility score from predicted responses using an indirect approach. Model performances were evaluated using mean absolute error (MAE), root mean squared error (RMSE), correlation coefficient (ρ), and Lin's concordance correlation coefficient (CCC). A five-fold cross-validation method was used to evaluate internal validation.

RESULTS

The average age was 63.04 years, and 53.72% of the included patients were male. Most (70.05%) patients had unstable angina pectoris, and the mean illness duration was 2.50 years. The EQ-5D scores were highly correlated with five subscales of the SAQ, with Spearman's rank correlation coefficients ranging from 0.6184 to 0.7093. The mixture beta model outperformed the other regression models in the direct approach, with the lowest MAE and RMSE and highest ρ and CCC. The ordered logit model in the indirect approach performed the same as the mixture beta regression with equal MAE, lower RMSE, and higher ρ and CCC.

CONCLUSION

Mapping algorithms developed using mixture beta and ordered logit models accurately converted SAQ scores to EQ-5D-5L health utility values, which could support health economic evaluations related to coronary heart disease.