Mapping EORTC QLQ-C30 and FACT-G onto EQ-5D-5L index for patients with cancer.

Yasuhiro HagiwawaTakeru ShiroiwaNaruto TairaTakuya KawaharaKeiko KonomuraShinichi NotoTakashi FukudaKojiro Shimozuma

Published in: Health and quality of life outcomes (2020)

The developed mapping algorithms can be used to generate the EQ-5D-5L index from EORTC QLQ-C30 or FACT-G in cost-effectiveness analyses, whose predictive performance would be similar to or better than those of previous algorithms.

Keyphrases

machine learning
high resolution
deep learning
high density
mass spectrometry