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.

An investigation of symptom burden and quality of life in Chinese chemo-naïve advanced lung cancer patients by using the Instrument-Cloud QOL System

OBJECTIVES

This study was designed to assess the disease-related symptom burden and quality of life (QOL) in Chinese chemo-naïve advanced lung cancer patients.

MATERIALS AND METHODS

Chemo-naïve patients with stage III/IV lung cancer were enrolled. 43 centers from 16 provinces of China participated in the study. Functional Assessment of Cancer Therapy-Lung (FACT-L) scale and Cloud QOL System were applied in the study.

RESULTS

376 eligible patients were analyzed. The three most common and severe symptoms were appetite loss (84.3%, scored 2.46), breathing difficulty (79.0%, scored 2.56), and cough (75.5%, scored 2.81). Significant correlation was found between QOL and symptoms. Regression analysis of QOL indicated that almost every symptom item (except shortness of breath) was the negative indicator of QOL. Moreover, pulmonary diseases, pleural metastases and brain metastases had significant negative impact on both symptoms and QOL. Relatively poor performance status affected the QOL only, while cardiovascular diseases merely affected the symptoms. And patients with EGFR mutations had less symptom burden than those with wild-type EGFR.

CONCLUSION

QOL evaluation by using the Cloud QOL System was feasible. Appetite loss, breathing difficulty and cough were the three most common and severe symptoms seen in Chinese chemo-naïve advanced lung cancer patients. Almost all symptoms had negative impact on QOL. And some clinical characteristics could predict the symptoms and QOL.