Highlights
- •The European Organisation for Research and Treatment of Cancer Quality of Life Utility-Core 10 Dimensions is a recently developed cancer-specific preference-based measure, designed to facilitate health economic evaluations in the cancer patient population.
- •The country-specific general population utility norms provide an adequate baseline in health economic evaluations if other control groups are missing.
- •Statistically significant country differences in general population utility norms, independent of the influence of national age and sex distributions, suggest the use of country-specific scoring algorithms on national data where applicable.
Abstract
Objectives
Methods
Results
Conclusion
Keywords
Introduction
Methods
Instruments
EORTC QLQ-C30 and EORTC QLU-C10D
Utility Norm Data Collection
Statistical Analyses
Results
Sociodemographic Analysis
Sociodemographic data | Characteristic | Canada (N = 1004) | Germany (N = 1006) | France (N = 1001) | Italy (N = 1036) | Poland (N = 1024) | United Kingdom (N = 1026) |
---|---|---|---|---|---|---|---|
Mean age (SD) | 46.88 (17.1) | 49.18 (17.2) | 47.88 (17.0) | 49.33 (16.9) | 45.61 (17.1) | 47.03 (17.6) | |
Sex | Male | 495 (49.3%) | 492 (48.9%) | 487 (48.7%) | 500 (48.2%) | 489 (47.8%) | 502 (48.9%) |
Female | 509 (50.7%) | 514 (51.1%) | 514 (51.3%) | 536 (51.8%) | 535 (52.2%) | 524 (51.1%) | |
Education | Less than compulsory | 27 (2.7%) | 1 (0.1%) | 1 (0.1%) | 0 (0%) | 8 (0.8%) | 15 (1.5%) |
Compulsory | 220 (21.9%) | 100 (10.0%) | 51 (5.1%) | 16 (1.6%) | 40 (3.9%) | 237 (23.1%) | |
Some postcompulsory | 0 (0%) | 370(36.7%) | 135 (13.5%) | 113 (10.9%) | 109 (10.6%) | 188 (18.3%) | |
Postcompulsory below university | 230 (22.9%) | 187 (18.6%) | 112 (11.2%) | 564 (54.4%) | 359 (35.0%) | 220 (21.4%) | |
University degree | 407 (40.5%) | 131 (13.0%) | 263 (26.3%) | 292 (28.2%) | 147 (14.4%) | 282 (27.5%) | |
Postgraduate degree | 110 (11.0%) | 211 (21.0%) | 419 (41.9%) | 49 (4.7%) | 326 (31.9%) | 72 (7.0%) | |
Prefer not to answer | 10 (1.0%) | 7 (0.7%) | 19 (1.9%) | 2 (0.2%) | 34 (3.3%) | 13 (1.3%) | |
Employment | Employed full time | 422 (42.1%) | 400 (39.7%) | 437 (43.7%) | 294 (28.4%) | 475 (46.4%) | 361 (35.2%) |
Employed part time | 82 (8.2%) | 104(10.3%) | 73 (7.3%) | 78 (7.5%) | 51 (5.0%) | 105 (10.3%) | |
Homemaker | 57 (5.7%) | 43 (4.3%) | 34 (3.4%) | 100 (9.6%) | 30 (3.0%) | 90 (8.8%) | |
Student | 35 (3.5%) | 61 (6.1%) | 50 (5.0%) | 88 (8.5%) | 63 (6.1%) | 43 (4.2%) | |
Unemployed | 55 (5.5%) | 34 (3.3%) | 80 (8.0%) | 100 (9.6%) | 39 (3.8%) | 89 (8.6%) | |
Retired | 257 (25.6%) | 276 (27.4%) | 283 (28.3%) | 240 (23.2%) | 249 (24.3%) | 242 (23.6%) | |
Self-employed | 59 (5.9%) | 53 (5.3%) | 25 (2.5%) | 124 (12.0%) | 66 (6.4%) | 64 (6.3%) | |
Other | 28 (2.8%) | 28 (2.8%) | 12 (1.2%) | 10 (1.0%) | 25 (2.4%) | 29 (2.8%) | |
Prefer not to answer/missing | 8 (0.8%) | 8 (0.8%) | 7 (0.7%) | 2 (0.2%) | 27 (2.6%) | 3 (0.2%) | |
Relationship | Single/not in a steady relationship | 282 (28.1%) | 230(22.9%) | 208 (20.8%) | 261 (25.2%) | 216 (21.1%) | 255 (24.8%) |
Married/in a steady relationship | 585 (58.2%) | 608 (60.4%) | 651 (65.0%) | 658 (63.5%) | 609 (59.5%) | 644 (62.8%) | |
Separated/divorced/widowed | 129 (12.8%) | 158 (15.7%) | 128 (12.8%) | 105 (10.1%) | 165 (16.1%) | 123 (12.0%) | |
Prefer not to answer | 8 (0.8%) | 9 (0.9%) | 14 (1.4%) | 12 (1.1%) | 34 (3.3%) | 5 (0.4%) | |
Health | No health condition selected | 396 (36.8%) | 384 (38.2%) | 455 (45.4%) | 389 (37.5%) | 367 (35.8%) | 399 (38.9%) |
At least 1 health condition selected | 580 (57.7%) | 542 (53.9%) | 498 (49.8%) | 600 (57.9%) | 590 (57.6%) | 588 (57.3%) | |
Missing as ticked “prefer not to answer” | 40 (4.0%) | 77 (7.7%) | 39 (3.9%) | 42 (4.1%) | 59 (5.8%) | 36 (3.5%) | |
Set missing as filled out incorrectly | 15 (1.5%) | 2 (0.2%) | 9 (0.9%) | 5 (0.5%) | 8 (0.8%) | 3 (0.3%) |
EORTC QLU-C10D Utility Norm Data Table for Countries

EORTC QLU-C10D utility norm | Canada | Germany | France | Italy | Poland | United Kingdom |
---|---|---|---|---|---|---|
Mean (SD) | 0.743 (0.24) | 0.763 (0.23) | 0.769 (0.25) | 0.843 (0.18) | 0.803 (0.17) | 0.724 (0.26) |
EORTC QLU-C10D Utility Norm Data Table for Countries, Age, and Sex Groups
Country | Mean utility (SD) | |||||||||||
---|---|---|---|---|---|---|---|---|---|---|---|---|
18-29 years | 30-39 years | 40-49 years | 50-59 years | 60-69 years | 70+ years | |||||||
Male | Female | Male | Female | Male | Female | Male | Female | Male | Female | Male | Female | |
Canada | 0.779 (0.230) | 0.726 (0.208) | 0.664 (0.308) | 0.766 (0.234) | 0.767 (0.242) | 0.737 (0.254) | 0.736 (0.256) | 0.727 (0.246) | 0.731 (0.253) | 0.754 (0.213) | 0.779 (0.197) | 0.761 (0.186) |
Germany | 0.755 (0.283) | 0.830 (0.121) | 0.811 (0.227) | 0.791 (0.255) | 0.808 (0.195) | 0.793 (0.225) | 0.799 (0.202) | 0.702 (0.238) | 0.748 (0.203) | 0.730 (0.260) | 0.720 (0.235) | 0.684 (0.238) |
France | 0.780 (0.279) | 0.733 (0.281) | 0.790 (0.277) | 0.742 (0.253) | 0.781 (0.259) | 0.738 (0.266) | 0.783 (0.271) | 0.752 (0.222) | 0.811 (0.221) | 0.781 (0.216) | 0.804 (0.208) | 0.751 (0.210) |
Italy | 0.857 (0.206) | 0.839 (0.195) | 0.796 (0.231) | 0.819 (0.188) | 0.832 (0.205) | 0.807 (0.187) | 0.887 (0.163) | 0.845 (0.159) | 0.877 (0.148) | 0.833 (0.166) | 0.899 (0.128) | 0.834 (0.174) |
Poland | 0.837 (0.175) | 0.779 (0.205) | 0.787 (0.186) | 0.792 (0.169) | 0.837 (0.134) | 0.802 (0.187) | 0.816 (0.166) | 0.808 (0.158) | 0.815 (0.147) | 0.794 (0.174) | 0.814 (0.125) | 0.759 (0.198) |
United Kingdom | 0.674 (0.308) | 0.758 (0.193) | 0.747 (0.281) | 0.673 (0.258) | 0.745 (0.295) | 0.697 (0.276) | 0.695 (0.289) | 0.692 (0.279) | 0.755 (0.237) | 0.752 (0.225) | 0.787 (0.183) | 0.746 (0.185) |

Regression Models
Country | Constant (C) | P value | Age | P value | Sex ( | P value |
---|---|---|---|---|---|---|
Canada | 0.708 | < .001 | 0.001 | .071 | 0.003 | .821 |
Germany | 0.875 | < .001 | −0.002 | < .001 | −0.039 | .015 |
France | 0.835 | < .001 | 0.001 | .073 | −0.039 | .002 |
Italy | 0.811 | < .001 | 0.001 | .002 | −0.048 | < .001 |
Poland | 0.782 | < .001 | <0.000 | .884 | −0.040 | .002 |
United Kingdom | 0.688 | < .001 | 0.002 | .004 | −0.024 | .153 |
Discussion
Guidelines for the economic evaluation of health technologies: CADTH methods and guidelines. CADTH. https://www.cadth.ca/guidelines-economic-evaluation-health-technologies-canada-0. Accessed January 16, 2023.
Guide to the processes of technology appraisal. National Institute for Health and Care Excellence. https://www.nice.org.uk/Media/Default/About/what-we-do/NICE-guidance/NICE-technology-appraisals/technology-appraisal-processes-guide-apr-2018.pdf. Accessed January 16, 2023.
Employment population ratios. OECD Stat. https://stats.oecd.org/Index.aspx?QueryId=64196. Accessed January 16, 2023.
OECD family database. OECD Stat. https://www.oecd.org/els/family/database.htm. Accessed January 16, 2023.
Conclusion
Article and Author Information
Supplemental Material
- Supplemental table 1
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