Normative Data for EORTC CAT

Principal investigator(s)
Sandra Nolte
Monash University Melbourne
Melbourne, Australia

Project summary

Patient-reported outcomes (PRO) data, i.e., data that are directly obtained from the patient, are traditionally assessed using a static approach. That is, the same questions (items) are presented to each respondent regardless of their relevance to the individual. As a result, respondents often have to answer items that are irrelevant to them, which increases respondent burden and may result in less precise score estimates. Collecting data via computerised adaptive testing (CAT) can address this shortcoming as it avoids the administration of irrelevant items by tailoring the instrument to the individual. To make use of the advantages of CAT, the EORTC Quality of Life Group has developed the EORTC CAT Core (EORTC CAT Core | EORTC – Quality of Life) which measures the same dimensions as the EORTC QLQ-C30 but with increased precision and flexibility. To enhance the interpretation of scores obtained via the CAT Core, it is important to link it to reference data obtained from the general population. Therefore, to increase the interpretability of the CAT Core and give meaning to its metric (i.e., the mean of 50 representing the mean of the general population), the current project was aimed at collecting representative data of a European reference population to establish the European Norm for the EORTC CAT Core. As the QLQ-C30 items are part of the CAT Core, we simultaneously generating norm data for the QLQ-C30.

Achievements

Data collection was finalised in April 2017, with data collected across 11 countries of the European Union (EU), Turkey, Russia, the USA and Canada, with a total sample size of N=15,386. The following countries were included to form the European Norm (of note, this project took place prior to the United Kingdom leaving the EU): Austria, Denmark, France, Germany, Hungary, Italy, the Netherlands, Poland, Spain, Sweden, and the United Kingdom. All data were pooled into one large database where they were cleaned and weighted using the official 2015 population distribution statistics published by the United Nations.

Future plans

The project officially concluded in June 2019.

For patients

The computerised adaptive test of the EORTC (CAT) has the advantage that patients do not need to answer unnecessary questions. However, to understand the data we collect from patients, it is useful to obtain norm data from the general population. This was the aim of this research project. With these norm data we can then compare a patient’s score relative to the average of persons living in the same region or country matched by age and sex. This greatly helps patients, clinicians, researchers and other users of patient-reported data to interpret the data provided by patients.

Publications

The following two core and 10 country-specific norm data articles were published as a direct result of the project, with over 290 additional research articles either citing or using our general population norm data (source: Web of Science, as at 19 March 2025).

Core articles:

  1. Nolte S, Liegl G, Petersen MA, Aaronson NK, Costantini A, Fayers PM, Groenvold M, Holzner B, Johnson CD, Kemmler G, Tomaszewski KA, Waldmann A, Young TE, Rose M, EORTC Quality of Life Group (2019). General population normative data for the EORTC QLQ-C30 health-related quality of life questionnaire based on 15,386 persons across 13 European countries, Canada and the Unites States. Eur J Cancer, 107, 153–163. https://doi.org/10.1016/j.ejca.2018.11.024.
  2. Liegl G, Petersen MA, Groenvold M, Aaronson NK, Costantini A, Fayers PM, Holzner B, Johnson CD, Kemmler G, Tomaszewski KA, Waldmann A, Young TE, Rose M, Nolte S, EORTC Quality of Life Group (2019). Establishing the European Norm for the health-related quality of life domains of the computer-adaptive test EORTC CAT Core. Eur J Cancer, 107, 133–141. https://doi.org/10.1016/j.ejca.2018.11.023

 Country-specific articles:

  1. Arraras JI, Nolte S, Liegl G, Rose M, Manterola A, Illarramendi JJ, Zarandona U, Rico M, Teiejria L, Asin G, Hernandez I, Barrado M, Vera R, Efficace F, Giesinger JM, EORTC Quality of Life Group (2021). General Spanish population normative data analysis for the EORTC QLQ-C30 by sex, age, and health condition. Health Qual Life Outcomes, 19(1):275. https://doi.org/10.1186/s12955-021-01820-x.
  2. de Ligt KM, Aaronson NK, Liegl G, Nolte S (2023). Updated normative data for the EORTC QLQ-C30 in the general Dutch population by age and sex: a cross-sectional panel research study. Qual Life Res. https://doi.org/10.1007/s11136-023-03404-2.
  3. Johansson H, Lagergren P, Nolte S, Brandberg Y (2023). Comparison between Swedish EORTC QLQ-C30 general population norm data published in 2000 and 2019. Acta Oncol, 1-7. https://doi.org/1080/0284186x.2023.2271165.
  4. Lehmann J, Giesinger JM, Nolte S, Sztankay M, Wintner LM, Liegl G, Rose M, Holzner B, EORTC Quality of Life Group (2020). Normative data for the EORTC QLQ-C30 from the Austrian general population. Health Qual Life Outcomes, 18(1):275. https://doi.org/10.1186/s12955-020-01524-8.
  5. Nolte S*, Waldmann A*, Liegl G, Petersen MA, Groenvold M, Rose M, EORTC Quality of Life Group (2020). Updated EORTC QLQ-C30 general population norm data for Germany. Eur J Cancer, 137:161–70. https://doi.org/10.1016/j.ejca.2020.06.002 (*joint first authorship)
  6. Pilz MJ, Gamper E-M, Efficace F, Arraras JI, Nolte S, Liegl G, Rose M, Giesinger JM, EORTC Quality of Life Group (2022). EORTC QLQ-C30 general population normative data for Italy by sex, age and health condition: An analysis of 1,036 individuals. BMC Public Health, 22(1), 1040. https://doi.org/10.1186/s12889-022-13211-y.
  7. Pilz MJ, Loth FLC, Nolte S, Thurner AMM, Gamper E-M, Anota A, Liegl G, Giesinger JM on behalf of the EORTC Quality of Life Group (2024). General population normative values for the EORTC QLQ-C30 by age, sex, and health condition for the French general population. J Patient Rep Outcomes, 8(1):48. https://doi.org/10.1186/s41687-024-00719-7.
  8. Pilz MJ, Nolte S, Liegl G, King M, Norman R, McTaggart-Cowan H, Bottomley A, Rose M, Kemmler G, Holzner B, Gamper EM, EORTC Quality of Life Group (2023). The European Organisation for Research and Treatment of Cancer Quality of Life Utility-Core 10 Dimensions Development and Investigation of General Population Utility Norms for Canada, France, Germany, Italy, Poland, and the United Kingdom. Value Health. , 26(5):760–7, https://doi.org/10.1016/j.jval.2022.12.009.
  9. Rogge A, Snyder C, Liegl G, Rose M, Nolte S, on behalf of the EORTC Quality of Life Group (2024). EORTC QLQ-C30 general population normative data for the United States. Eur J Cancer. 202: 114030. https://doi.org/10.1016/j.ejca.2024.114030.
  10. Young T, Velikova G, Liegl G, Rose M, Nolte S EORTC Quality of Life Group (2024). EORTC QLQ-C30 normative data for the United Kingdom: Results of a cross-sectional survey of the general population. Eur J Cancer. 204:113927. https://doi.org/10.1016/j.ejca.2024.113927.

 Data Availability

Data are available upon request from the EORTC Headquarters. Please submit a formal request using the study number 1519 via: https://www.eortc.be/services/forms/erp/request.aspx.

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