Evidence map›Paper›PMID 33143687›Full record

ArticleHealth and quality of life outcomes2020

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

Yasuhiro Hagiwara, Takeru Shiroiwa, Naruto Taira, Takuya Kawahara, Keiko Konomura, Shinichi Noto, Takashi Fukuda, Kojiro Shimozuma

Abstract readValidation Study
In one paragraph

Article in Health and quality of life outcomes, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 30 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
30citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

30 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Trial
  4. Article
  5. Mapping EORTC-QLQ-C30 scores to EQ-5D-5L utility values for gynecological cancer survivors in follow-up care.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2026
    Article
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  7. Predicting EQ-5D-3L utility values from clinical data in a prospective cohort of kidney transplant recipients.The European journal of health economics : HEPAC : health economics in prevention and care · 2026
    Observational
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  12. The role of stem cells in precision medicine: next-generation cancer treatment.Journal of the Egyptian National Cancer Institute · 2025
    Review
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  18. Japanese value set for the EORTC QLU-C10D: A multi-attribute utility instrument based on the EORTC QLQ-C30 cancer-specific quality-of-life questionnaire.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
  19. Mapping the EORTC QLQ-C30 and QLQ H&N35 to the EQ-5D-5L and SF-6D for papillary thyroid carcinoma.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2024
    Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Yasuhiro HagiwaraDepartment of Biostatistics, Division of Health Sciences and Nursing, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, 113-0033, Japan. hagiwara@epistat.m.u-tokyo.ac.jp.ORCID http://orcid.org/0000-0003-3792-5368
Takeru ShiroiwaCenter for Outcomes Research and Economic Evaluation for Health, National Institute of Public Health, Wako, Japan.
Naruto TairaBreast and Endocrine Surgery Department, Okayama University Hospital, Okayama, Japan.
Takuya KawaharaClinical Research Promotion Center, The University of Tokyo Hospital, Tokyo, Japan.
Keiko KonomuraCenter for Outcomes Research and Economic Evaluation for Health, National Institute of Public Health, Wako, Japan.
Shinichi NotoCenter for Health Economics and QOL Research, Niigata University of Health and Welfare, Niigata, Japan.
Takashi FukudaCenter for Outcomes Research and Economic Evaluation for Health, National Institute of Public Health, Wako, Japan.
Kojiro ShimozumaDepartment of Biomedical Sciences, College of Life Sciences, Ritsumeikan University, Kusatsu, Japan.

Funding

Japan Society for the Promotion of Science 19K24193
6 · The paper itself

Abstract

backgroundTo develop direct and indirect (response) mapping algorithms from the European Organization for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) and the Functional Assessment of Cancer Therapy General (FACT-G) onto the EQ-5D-5L index.

methodsWe conducted the QOL-MAC study where EQ-5D-5L, EORTC QLQ-C30, and FACT-G were cross-sectionally evaluated in patients receiving drug treatment for solid tumors in Japan. We developed direct and indirect mapping algorithms using 7 regression methods. Direct mapping was based on the Japanese value set. We evaluated the predictive performances based on root mean squared error (RMSE), mean absolute error, and correlation between the observed and predicted EQ-5D-5L indexes.

resultsBased on data from 903 and 908 patients for EORTC QLQ-C30 and FACT-G, respectively, we recommend two-part beta regression for direct mapping and ordinal logistic regression for indirect mapping for both EORTC QLQ-C30 and FACT-G. Cross-validated RMSE were 0.101 in the two methods for EORTC QLQ-C30, whereas they were 0.121 in two-part beta regression and 0.120 in ordinal logistic regression for FACT-G. The mean EQ-5D-5L index and cumulative distribution function simulated from the recommended mapping algorithms generally matched with the observed ones except for very good health (both source measures) and poor health (only FACT-G).

conclusionsThe 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.

Indexed as

Quality of LifeAdultAgedAlgorithmsFemaleHumansJapanLogistic ModelsMaleMiddle AgedNeoplasmsSurveys and QuestionnairesCancerEORTC QLQ-C30EQ-5D-5LFACT-GMappingPreference-based measure

Identifiers

PMID33143687
PMCPMC7641825

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.