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

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Abstract

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.

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Data availability

The datasets generated and/or analyzed during the current study are available from the corresponding author upon reasonable request.

Abbreviations

ARV:

Average ranking value

CLAD:

Censored least absolute deviations

CUA:

Cost-utility analysis

CV:

Cross-validation

EWB:

Emotional well-being

FACT-L:

Functional Assessment of Cancer Therapy-Lung

FWB:

Functional well-being

HRQoL:

Health-related quality of life

LCS:

Lung Cancer Subscale

MAE:

Mean absolute error

MID:

Minimally important difference

OLS:

Ordinary least squares

PWB:

Physical well-being

QALY:

Quality-adjusted life year

QoL:

Quality of life

RMSE:

Root mean square error

SWB:

Social/family well-being

TPM:

Two-part model

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Acknowledgements

The authors thank all participants for their time and effort.

Funding

This study was supported by Foundation of Department of Science and Technology of Sichuan Province, China, Grant Number: 2020YFS0397, and Sichuan Province Clinical Key Specialty Construction Project.

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Author notes

  1. Longlin Jiang and Hong Zhou contributed to this work equally.

Authors and Affiliations

  1. Department of Thoracic Surgery Sichuan Clinical Research Center for Cancer Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China

    Longlin Jiang, Hong Zhou & Xi Luo

  2. Nursing Department, Sichuan Clinical Research Center for Cancer, Sichuan Cancer Hospital & Institute, Sichuan Cancer Center, Affiliated Cancer Hospital of University of Electronic Science and Technology of China, Chengdu, China

    Qing Yang

  3. School of Nursing, Chengdu Medical College, Chengdu, China

    Deyu Huang

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  1. Longlin Jiang
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  5. Deyu Huang
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Contributions

QY conceived and designed this study; LLJ, XL, and DYH participated in the acquisition of the data; LLJ analyzed the data, interpreted the results, and wrote the first draft of the manuscript; and HZ supervised the statistical analysis, gave feedback on the manuscript, and revised it critically for important intellectual content. All authors have read and approved the final version of the manuscript.

Corresponding author

Correspondence to Qing Yang.

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The authors declare no conflicts of interest.

Ethical approval

The study has been approved by the Ethics Committee of Sichuan Cancer Hospital (Reference No. SCCHEC-02-2020-042). The study followed the principle of the Declaration of Helsinki.

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Informed consent was obtained from all individual participants included in the study.

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Jiang, L., Zhou, H., Yang, Q. et al. Development of algorithms to estimate the EQ-5D-5L from the FACT-L in patients with lung cancer: a mapping study. Qual Life Res 33, 805–816 (2024). https://doi.org/10.1007/s11136-023-03567-y

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