Mapping the EORTC QLQ-C30 and QLQ-LC13 to the SF-6D utility index in patients with lung cancer using machine learning and traditional regression methods

Mapping the EORTC QLQ-C30 and QLQ-LC13 to the SF-6D utility index in patients with lung cancer using machine learning and traditional regression methods

Abstract Background Preference-based measures of health-related quality of life (HRQoL), such as the Short Form Six-Dimension (SF-6D) is essential for health economic evaluations. However, these measures are rarely included in clinical trials for lung cancer. This study aims to develop mapping algor...

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Bibliographic Details
Main Authors: Longlin Jiang, Kexun Li, Simiao Lu, Zhou Hong, Yifang Wang, Qin Xie, Qin He, Sirui Wei, Aoru Zhou, Hong Kang, Xuefeng Leng, Qing Yang, Yan Miao
Format: Article
Language:English
Published: BMC 2025-07-01
Series:Health and Quality of Life Outcomes
Subjects:
Lung Cancer
Quality of life
QLQ-C30
QLQ-LC13
Mapping
SF-6D
Online Access:https://doi.org/10.1186/s12955-025-02394-8
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