Mapping EORTC QLQ-C30 onto EQ-5D for the assessment of cancer patients

Health and Quality of Life Outcomes

Jin-Hee Ahn¹  Hwa-Jung Kim²  Min-Woo Jo³  Seon Ha Kim³ 

[1] Division of Oncology, Asan Medical Center, University of Ulsan College of Medicine, 86, Asanbyeongwon-gil, Songpa-gu, Seoul, 138-736, Korea;Department of Clinical Epidemiology and Biostatistics, Asan Medical Center, 86, Asanbyeongwon-gil, Songpa-gu, Seoul, 138-736, Korea;Department of Preventive Medicine, University of Ulsan College of Medicine, 86, Asanbyeongwon-gil, Songpa-gu, Seoul, 138-736, Korea

关键词: Quality of life;    Mapping;    Cancer;    EORTC QLQ-C30;    EQ-5D;   

Others  :  824775
DOI  :  10.1186/1477-7525-10-151

 received in 2012-07-27, accepted in 2012-12-13,  发布年份 2012

【 摘 要 】

Background

The European Organisation for Research and Treatment of Cancer Quality of Life Questionnaire Core 30 (EORTC QLQ-C30) is the instrument most frequently used to measure quality of life in cancer patients, whereas the EQ-5D is widely used to measure and evaluate general health status. Although the EORTC QLQ-C30 has been mapped to EQ-5D utilities, those studies were limited to patients with a single type of cancer. The present study aimed to develop a mapping relationship between the EORTC QLQ-C30 and EQ-5D-based utility values at the individual level.

Methods

The model was derived using patients with different types of cancer who were receiving chemotherapy. The external validation set comprised outpatients with colon cancer. Ordinary least squares regression was used to estimate the EQ-5D index from the EORTC QLQ-C30 results. The predictability, goodness of fit, and signs of the estimated coefficients of the model were assessed. Predictive ability was determined by calculating the mean absolute error, the estimated proportions with absolute errors > 0.05 and > 0.1, and the root-mean-squared error (RMSE).

Results

A model that included global health, physical, role, emotional functions, and pain was optimal, with a mean absolute error of 0.069 and an RMSE of 0.095 (normalized RMSE, 8.1%). The explanatory power of this model was 51.6%. The mean absolute error was higher for modeled patients in poor health.

Conclusions

This mapping algorithm enabled the EORTC QLQ-C30 to be converted to the EQ-5D utility index to assess cancer patients in Korea.

【 授权许可】

   
2012 Kim et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

【 参考文献 】

• [1]Torrance GW, Feeny DH, Furlong WJ, Barr RD, Zhang Y, Wang Q: Multiattribute utility function for a comprehensive health status classification system. Health Utilities Index Mark 2. Med Care 1996, 34:702-722.
• [2]Feeny D, Furlong W, Torrance GW, Goldsmith CH, Zhu Z, DePauw S, Denton M, Boyle M: Multiattribute and single-attribute utility functions for the health utilities index mark 3 system. Med Care 2002, 40:113-128.
• [3]Brooks R: EuroQol: the current state of play. Health Policy 1996, 37:53-72.
• [4]Brazier J, Roberts J, Deverill M: The estimation of a preference-based measure of health from the SF-36. J Health Econ 2002, 21:271-292.
• [5]Kontodimopoulos N, Aletras VH, Paliouras D, Niakas D: Mapping the cancer-specific EORTC QLQ-C30 to the preference-based EQ-5D, SF-6D, and 15D instruments. Value Health 2009, 12:1151-1157.
• [6]Patrick DL, Deyo RA: Generic and disease-specific measures in assessing health status and quality of life. Med Care 1989, 27:S217-S232.
• [7]Aaronson NK, Ahmedzai S, Bergman B, Bullinger M, Cull A, Duez NJ, Filiberti A, Flechtner H, Fleishman SB, de Haes JC, et al.: The European Organization for Research and Treatment of Cancer QLQ-C30: a quality-of-life instrument for use in international clinical trials in oncology. J Natl Cancer Inst 1993, 85:365-376.
• [8]Yun YH, Park YS, Lee ES, Bang SM, Heo DS, Park SY, You CH, West K: Validation of the Korean version of the EORTC QLQ-C30. Qual Life Res 2004, 13:863-868.
• [9]Rowen D, Brazier J, Young T, Gaugris S, Craig BM, King MT, Velikova G: Deriving a preference-based measure for cancer using the EORTC QLQ-C30. Value Health 2011, 14:721-731.
• [10]Brooks R, Rabin R, De Charro F: The Measurement and Valuation of Health Status Using Eq-5D: A European Perspective: Evidence from the Euroqol Biomed Research Programme. Dordrecht, the Netherlands: Kluwer Academic Publishers; 2003.
• [11]Lee YK, Nam HS, Chuang LH, Kim KY, Yang HK, Kwon IS, Kind P, Kweon SS, Kim YT: South Korean time trade-off values for EQ-5D health states: modeling with observed values for 101 health states. Value Health 2009, 12:1187-1193.
• [12]Crott R, Briggs A: Mapping the QLQ-C30 quality of life cancer questionnaire to EQ-5D patient preferences. Eur J Health Econ 2010, 11:427-434.
• [13]McKenzie L, van der Pol M: Mapping the EORTC QLQ-C30 onto the EQ-5D instrument: the potential to estimate QALYs without generic preference data. Value Health 2009, 12:167-171.
• [14]Kim EJ, Ko SK, Kang HY: Mapping the cancer-specific EORTC QLQ-C30 and EORTC QLQ-BR23 to the generic EQ-5D in metastatic breast cancer patients. Qual Life Res 2012, 21:1193-1203.
• [15]Kim SH, Kim HJ, Lee SI, Jo MW: Comparing the psychometric properties of the EQ-5D-3L and EQ-5D-5L in cancer patients in Korea. Qual Life Res 2012, 21:1065-1073.
• [16]Kim SH, Hwang JS, Kim TW, Hong YS, Jo MW: Validity and reliability of the EQ-5D for cancer patients in Korea. Support Care Cancer 2012, 20:3155-3160.
• [17]Fayer PL: On behalf of EORTC quality of life study group. 2nd edition. Brussells Belgium: Eortc; 1998. [Eortc QLQ-C30 Scoring Manual]
• [18]Brazier JE, Yang Y, Tsuchiya A, Rowen DL: A review of studies mapping (or cross walking) non-preference based measures of health to generic preference-based measures. Eur J Health Econ 2010, 11:215-225.
• [19]Versteegh MM, Leunis A, Luime JJ, Boggild M, Uyl-de Groot CA, Stolk EA: Mapping QLQ-C30, HAQ, and MSIS-29 on EQ-5D. Med Decis Making 2012, 32:554-568.
• [20]Dolan P: Modeling valuations for EuroQol health states. Med Care 1997, 35:1095-1108.
• [21]Versteegh MM, Rowen D, Brazier JE, Stolk EA: Mapping onto Eq-5 D for patients in poor health. Health Qual Life Outcomes 2010, 8:141. BioMed Central Full Text
• [22]Rowen D, Brazier J, Roberts J: Mapping SF-36 onto the EQ-5D index: how reliable is the relationship? Health Qual Life Outcomes 2009, 7:27. BioMed Central Full Text