Updated normative data for the EORTC QLQ-C30 in the general Dutch population by age and sex: a cross-sectional panel research study

Patient-Reported Outcome Measures (PROMs) are questionnaires completed by patients to measure their quality of life. The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Core Questionnaire, the QLQ-C30, is a questionnaire widely used for cancer patients. To help interpret the scores that result from this questionnaire, scores can be compared with the scores from the general population, so-called normative scores. This study generated updated EORTC QLQ-C30 data for the Dutch general population that had been collected as part of a large European Norm Data project. This is important, because national normative data allows for more meaningful interpretation of scores within a specific country. Scores are presented separately for men and women, and for different age groups. We found that with increasing age, worse physical but better emotional functioning was reported. Men generally reported better functioning and fewer symptoms compared to women. The normative EORTC QLQ-C30 data for the Dutch general population can be used to better interpret data obtained from Dutch cancer patients.

Patient-Reported Outcome Measures (PROMs), designed to quantify patients’ experiences with disease and treatment, have been increasingly applied in oncology trials and observational studies over the past decades [1]. The European Organisation for Research and Treatment of Cancer (EORTC) Quality of Life Core Questionnaire, the QLQ-C30, is a validated PROM available in many languages. The EORTC QLQ-C30 assesses 15 domains of functional health and symptoms commonly experienced by cancer patients [2]. It is widely used in clinical trials and as part of clinical research [3]. Nowadays, PROMs are also increasingly integrated into daily clinical practice for assessing and managing health-related quality of life (HRQoL) in individual patients [4, 5], following the paradigm shift to patient-centred healthcare [5, 6]. The International Consortium for Health Outcomes Measurement (ICHOM) recommends the adoption of the EORTC QLQ-C30 in clinical practice, for example, for patients with breast [7], lung [8], advanced prostate [9], and colorectal cancer [10].

An important strategy to aid in the interpretation of cancer patients’ HRQoL is to compare these with general population scores, so-called normative data [11]. In 2017, normative data for the original EORTC QLQ-C30 and its computer-adaptive test version (EORTC CAT Core [12]) were systematically collected via an online research panel in the general populations of 11 European Union (EU) countries, and Russia, Turkey, Canada, and the United States in a large international study [13, 14]. To date, this has resulted in two core publications [13], 14 and separate national norm data papers for the German [15], Austrian [16], Spanish [17] and Italian [18] general populations, respectively. For studies conducted at the local or national level, it is important to have country-specific normative data available, because normative data can vary between countries and cultures [13]. Thus, national normative data allows for more meaningful score interpretation within a specific country.

Van de Poll-Franse et al. [19] published Dutch EORTC QLQ-C30 data for the general population based on a 2009 survey of 1700 individuals. Subsequently, Mols et al. [20] carried out five consecutive annual assessments (2009–2013) of the EORTC QLQ-C30 in 1700–2400 individuals from the Dutch general population. However, these studies were not conducted in line with other international general population studies. To enable inter-country comparison, the aim of the present study was to generate and describe updated EORTC QLQ-C30 data for the Dutch general population, based on the 2017 EORTC international online survey that employed a uniform sampling strategy across participating countries [13, 14]. Results were stratified by age and sex, both having a distinct impact on HRQoL [21, 22]. These updated normative data will facilitate the interpretation of HRQoL data within the Netherlands, and their comparison with data obtained in other countries.

This study describes Dutch EORTC QLQ-C30 normative data stratified by age and sex. Mean functioning ranged between 82 and 92 points (with 100 points indicating perfect functioning), while symptom scores ranged between 4 and 24 points (with 0 indicating no symptom burden). Clinically meaningful trends were found for emotional functioning (where scores were better with increasing age), similar to other recent publications in this area [15‐18]. Most symptom scores remained stable over age categories. However, fatigue scores were better with increasing age (clinically meaningful difference). Men generally reported better functioning, and lower symptom burden for insomnia, pain, fatigue, and dyspnoea, but except for insomnia, these differences were not clinically meaningful.

Dutch general population data for the EORTC QLQ-C30 have been published previously by van de Poll-Franse et al. based on a 2009 survey of 1700 individuals [19]. Similar to our findings and the results of the larger European parent study from which our sample stems [13], van de Poll-Franse et al. described clinically meaningful worse physical functioning scores with increasing age; differences in scores between age groups for other functioning scales were not clinically meaningful. Like our findings, men scored significantly better than women did on most functioning scales but differences were not clinically meaningful [19]. Subsequently, Mols et al. [20] carried out five consecutive annual assessments (2009–2013) of the EORTC QLQ-C30 in 1743 (2009), 2050 (2010), 2040 (2011), 2194 (2012), and 2333 (2013) individuals from the Dutch general population. They reported that, in general, HRQoL was worse among the older age groups; these findings were clinically meaningful for physical and role functioning. Similar to our findings, they reported non-clinically meaningful higher summary scale scores in men than in women and in the younger compared to the older age groups. However, in contrast to our findings, Mols et al. found clinically meaningful age differences for pain and dyspnoea (both worse scores with increasing age), as well as clinically meaningful worse scores in women compared to men for fatigue, and pain.

Contrasting to van de Poll-Franse et al. [19] and Mols et al. [20], we found clinically meaningful better emotional functioning with increasing age. Previous international literature yields mixed findings, with some studies observing this trend [13, 16, 17, 30] and others not [31, 32]. Actual differences in emotional functioning may have occurred over time, for example by changes in society over the past decade that especially affected younger people. Further, both previous Dutch studies [19, 20] found a clinically meaningful worse fatigue scores with increasing age, while we found that fatigue scores were better in older respondents. Both previous Dutch studies reported clinically meaningful differences for other symptom scales, including pain, insomnia, and dyspnoea, while in our study we observed stable symptom scores. A possible explanation for the observed differences between studies could lie in the detrimental effect of health conditions on HRQoL [33]. In our study, 52% percent of individuals reported no chronic health conditions (weighted sample). This is higher than the 38% reported by van de Poll-Franse et al. [19], the 40% reported by Mols et al. [20], and the 41% of the actual proportion of individuals without chronic health conditions reported in a 2020 Dutch public health report [34]. In our study, in particular, participants in the older age categories may have been ‘healthier’ than the data from the Dutch public health report suggest, resulting in an overestimation of their HRQoL. A related Dutch report on national health statistics described relatively large differences in self-reported health experience between lower and more highly educated persons, with the latter reporting better health [35]. We included 42% of participants with a university degree or higher, whereas van de Poll-Franse et al. reported 37% and Mols et al. only 13%. According to Statistics Netherlands, that publishes annual data on the characteristics of the Dutch population, the percentage of individuals with a university degree was 16% in 2019 and has been increasing over the past decade across age groups [36].

Comparing our data to Statistics Netherlands 2017 suggests that the study data are representative in terms of most basic individual characteristics (age, sex, and marital status) [37]. Since 97.1% of the Dutch population had access to internet from their homes at the time we conducted our survey [38], it is unlikely that computer access played a role in the somewhat skewed educational background of our sample. A more plausible explanation is that highly educated individuals are more likely to participate in surveys than low-educated individuals, and it is therefore worthwhile to correct for education levels [39]; especially to avoid bias in the older age groups, as those who can use computers might be healthier because of their intellectual ability or access to health information [40]. Use of paper-and-pencil questionnaires and telephone-assisted surveys could aid in recruiting older individuals who would otherwise not be recruited into such studies. As opposed to age and sex, we could not correct for health status or education in our weighting approach, as that information was not available at an international standardised level, for instance from the United Nations statistics. In the original study by Liegl et al. [14], representativeness of sample characteristics was tested. Although the total sample was not representative based on educational level, as is the case with the present Dutch sample, it was found that observed group differences based on educational status were negligible, evidenced by very small effect sizes.

The mean functioning scores we report (between 82 and 92) are, together with scores from Austria (between 78 and 92 [16]), among the most favourable in Europe [13], where scores in Germany (between 74 and 85 [15]), Italy (between 74 and 88 [18]), and Spain (between 77 and 88 [17]) are slightly worse. In the international study sample and country-specific samples for Austria and Italy, HRQoL was generally better in respondents without health conditions [14, 16, 18]. Half of our population sample was free from health conditions (52%, weighted sample), comparable to the percentage reported in Austria (53%) [16]. In Germany (41%) [15], Italy (38%) [18], and Spain (39%) [17], and the parent sample (39%), notably smaller proportions of the population samples reported having no health conditions (weighted samples). Similar to our study, Lehmann et al. [16] reported that 35% of their sample completed university-level education while, in fact, only 15% of the Austrian population has that level of education. The core publication by Liegl et al. [14] investigated in depth the relationship between education and HRQoL. Post-compulsory compared to less than post-compulsory education was associated significantly with better HRQoL. However, differences were of low clinical relevance as indicated by the small effect sizes (all eta² ≤ 0.015).