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

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Abstract

Purpose

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.

Methods

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.

Result

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.

Conclusions

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.

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Abbreviations

CUA:

Cost-utility analysis.

ECOG:

Eastern cooperative oncology group

EORTC QLQ-BR23 (or QLQ-BR23):

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-VAS:

EQ-5D visual analogue scale

ISPOR:

International society for pharmacoeconomics and outcomes research

MBC:

Metastatic breast cancer

NHI:

National health insurance

OLS:

Ordinary least squares

QALYs:

Quality-adjusted life years

QOL:

Quality of life

RPE:

Relative prediction error

VIF:

Variance inflation factor

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Acknowledgments

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

Author information

Authors and Affiliations

  1. Graduate School of Public Health, Seoul National University, Seoul, South Korea

    Eun-ju Kim

  2. Graduate School of Public Health, Yonsei University, Seoul, South Korea

    Su-Kyoung Ko

  3. Department of Market Access, Pfizer Pharmaceuticals Korea Limited, Seoul, South Korea

    Su-Kyoung Ko

  4. College of Pharmacy, Yonsei Institute of Pharmaceutical Sciences, Yonsei University, 162-1 Songdo-dong, Yeonsu-gu, Incheon, 406-840, South Korea

    Hye-Young Kang

Authors
  1. Eun-ju Kim
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  2. Su-Kyoung Ko
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Corresponding author

Correspondence to Hye-Young Kang.

Appendices

Appendix 1: Technical summary: principles of scoring of QLQ-C30

This was taken from the EORTC QLQ-C30 Scoring Manual [12].

  1. 1.

    Calculate raw score

If items I 1, I 2,…I n are included in a scale, then the raw score of a scale is calculated as follows:

$$ {\text{Raw score}} = {\text{RS}} = \left( {I_{1} + I_{2} + \cdots + I_{n} } \right)/n $$
  1. 2.

    Linear transformation

Apply the linear transformation to 0–100 to obtain the score S,

Functional scales: score = {1−(RS−1)/range} × 100

Symptom scales/items: score = {(RS−1)/range} × 100

Global health status/QOL: score = {(RS−1)/range} × 100

Range is the difference between the maximum possible value of RS and the minimum possible value. The QLQ-C30 has been designed so that all the items in any scale take the same range of values. Therefore, the range of RS equals the range of the item values. Most items are scored 1–4, giving a range = 3. The exceptions are the items contributing to the global health status/QOL, which are 7-point questions with a range = 6, and the initial yes/no item on the earlier versions of the QLQ-C30, which have range = 1.

Appendix 2

See Table 6.

Table 6 Covariance matrix of model 1
Full size table

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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 21, 1193–1203 (2012). https://doi.org/10.1007/s11136-011-0037-y

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