Evidence map›Paper›PMID 37938402›Full record

ArticleQuality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation2024

Mapping the EORTC QLQ-C30 and QLQ H&N35 to the EQ-5D-5L and SF-6D for papillary thyroid carcinoma.

Deyu Huang, Dingfen Zeng, Yuan Tang, Longlin Jiang, Qing Yang

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Article in Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 1 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

6 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. 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
  3. Article
  4. Development of mapping algorithms for gastric cancer: translating EORTC QLQ-C30 and QLQ-STO22 to EQ-5D-5L health utilities.Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation · 2025
    Article
  5. Article
  6. Article
4 · The record

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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

5 authors.

Deyu HuangSchool of Nursing, Chengdu Medical College, Chengdu, 610500, China.
Dingfen ZengNursing 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.
Yuan TangNursing 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.
Longlin JiangNursing 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 YangNursing 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. yangqingsc@163.com.ORCID http://orcid.org/0000-0002-9730-0901

Funding

The Department of Science and Technology of Sichuan Province, China 2020YFS0397
6 · The paper itself

Abstract

purposeEmpirical evidence for the EORTC QLQ C30 scale in thyroid cancer mapping algorithms has not been found in China, which limits the cost-utility analysis of patients with papillary thyroid carcinoma (PTC) population. We developed mapping algorithms that use the EORTC QLQ-C30 and QLQ H&N35 to predict EQ-5D-5L and SF-6D health utility scores for PTC patients.

methodsData from 1050 Chinese PTC patients who completed the EORTC QLQ-C30, QLQ H&N35, EQ-5D-5L and SF-6D instruments were collected. Direct mapping (OLS, Tobit, Betamix) and indirect mapping functions (Order Probit) were used to estimate algorithms. The goodness-of-fit of mapping performance was assessed by MAE, RMSE, AIC, BIC, AE, and ICC. A fivefold cross-validation and random sample validation approach were used to test the stability of the models.

resultsThe mean EQ-5D-5L and SF-6D utility scores were 0.8704 and 0.6368, respectively. We recommend the Betamix model for the EQ-5D-5L (MAE = 0.0363, RMSE = 0.0505, AIC = -3458.73, BIC = -3096.91, AE > 0.05(%) = 48.38, AE > 0.1(%) = 8.67, ICC = 0.8288 for the full sample dataset) and the Betamix model for the SF-6D (MAE = 0.0328, RMSE = 0.0417, AIC = -2788.91, BIC = -2605.51, AE > 0.05(%) = 42.76, AE > 0.1(%) = 3.62, ICC = 0.8657 for the full sample dataset), with EORTC QLQ-C30 all items, QLQ H&N35 all items, age and gender as the predicted variables showing the best performance.

conclusionIn the absence of preference-based quality of life tools, the mapping algorithms reported here are effective alternative for predicting the health utility of PTC patients, contributing to the cost-utility analysis studies.

Indexed as

CarbamatesQuality of LifeThyroid NeoplasmsHumansResearch DesignSurveys and QuestionnairesThyroid Cancer, PapillarybetamixCarbamatesEORTC QLQ-C30EQ-5D-5LMappingPapillary thyroid carcinomaQLQ H&N35SF-6D

Identifiers

PMID37938402

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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.