Updated EORTC QLQ-C30 general population norm data for Germany. (September 2020) - Nolte, Sandra; Waldmann, Annika; Liegl, Gregor; Petersen, Morten Aa; Groenvold, Mogens; Rose, Matthias; ,
Abstract: Objective: The European Organisation for Research and Treatment of Cancer (EORTC) core questionnaire, QLQ-C30, is a frequently used patient-reported outcome (PRO) instrument to assess health-related quality of life of patients with cancer. To enhance the understanding and interpretation of PRO data, it is important to obtain norm data from the general population. This article presents updated general population norm data for the EORTC QLQ-C30 for Germany. Methods: Data were obtained as part of a larger study collecting EORTC QLQ-C30 norm data across 15 countries via an online survey. After linear transformation of EORTC QLQ-C30 raw scores, data were weighted based on the United Nations' population distribution statistics. Data are presented by age and sex/age. Results: A total of 1006 Germans responded to the survey. Across EORTC QLQ-C30 domains, different response patterns were observed, with men generally scoring better, that is, higher in most function scales and lower in most symptom scales/items than women. For age, mixed patterns were observed. While older respondents scored worse/lower in physical and role functioning, emotional functioning scores appeared to increase with increasing age. For the symptom scales/items, some symptoms were relatively stable across age groups, while others either increased or decreased with increasing age. Conclusions: This study presents updated EORTC QLQ-C30 general population norm data for Germany that can readily be used for comparative purposes with data obtained from patients with cancer. Highlights: General population norm data enhance the interpretation of patient-reported outcomes (PRO) data. This article presents updated EORTC QLQ-C30 normative data for Germany. Data were collected as part of a multi-national survey enabling intra- & intercountry comparisons. These new norm data can be readily used for comparative purposes with PRO data from cancer patients.