Quality of Life Research

, Volume 21, Issue 7, pp 1193–1203 | Cite as

Mapping the cancer-specific EORTC QLQ-C30 and EORTC QLQ-BR23 to the generic EQ-5D in metastatic breast cancer patients

  • Eun-ju Kim
  • Su-Kyoung Ko
  • Hye-Young KangEmail author



To develop a mapping algorithm for a conversion of the EORTC QLQ-C30 and EORTC QLQ BR-23 into the EQ-5D-derived utilities in metastatic breast cancer (MBC) patients.


We enrolled 199 patients with MBC from four leading Korean hospitals in 2009. EQ-5D utility, cancer-specific (QLQ-C30) and breast cancer-specific quality of life data (QLQ-BR23) and selected clinical and demographic information were collected from the study participants. Ordinary least squares regression models were used to model the EQ-5D using QLQ-C30 and QLQ-BR23 scale scores. To select the best model specification, six different sets of explanatory variables were compared.


Regression analysis with the multiitem scale scores of QLQ-C30 was the best-performing model, explaining for 48.7% of the observed EQ-5D variation. Its mean absolute error between the observed and predicted EQ-5D utilities (0.092) and relative prediction error (2.784%) was among the smallest. Also, this mapping model showed the least systematic errors according to disease severity.


The mapping algorithms developed have good predictive validity, and therefore, they enable researchers to translate cancer-specific health-related quality of life measures to the preference-adjusted health status of MBC patients.


EORTC QLQ-C30 EORTC QLQ-BR 23 EQ-5D Mapping Utility Quality of life 



Cost-utility analysis.


Eastern cooperative oncology group


European Organization for Research and Treatment of Cancer quality of life questionnaire breast cancer-23

EORTC QLQ-C30 (or QLQ-C 30)

European Organization for Research and Treatment of Cancer quality of life questionnaire core-30


EQ-5D visual analogue scale


International society for pharmacoeconomics and outcomes research


Metastatic breast cancer


National health insurance


Ordinary least squares


Quality-adjusted life years


Quality of life


Relative prediction error


Variance inflation factor



This study was supported by an unrestricted grant from Pfizer Pharmaceuticals Korea Limited.


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Copyright information

© Springer Science+Business Media B.V. 2011

Authors and Affiliations

  1. 1.Graduate School of Public HealthSeoul National UniversitySeoulSouth Korea
  2. 2.Graduate School of Public HealthYonsei UniversitySeoulSouth Korea
  3. 3.Department of Market AccessPfizer Pharmaceuticals Korea LimitedSeoulSouth Korea
  4. 4.College of Pharmacy, Yonsei Institute of Pharmaceutical SciencesYonsei UniversityYeonsu-guSouth Korea

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