A scoping review of utilisation of the EQ-5D questionnaire to evaluate health-related quality of life following a diagnosis of head and neck cancer

Introduction

Approximately 12,200 patients are diagnosed with head and neck cancer (HNC) in the United Kingdom annually (1). The survival rate of HNC has increased and is currently reported to be 50–60% (1). Treatment of HNC is associated with significant morbidity (2), particularly due to the critical functional and social roles of the face and surrounding structures. The implications of HNC on health-related quality of life (HRQOL) are widely recognised (2,3). As survivorship is increasing, patients are living longer with the impacts of HNC and its treatment, and so a significant emphasis on HRQOL in HNC research in recent years has emerged (2-5).

HRQOL is a multidimensional concept that broadly evaluates positive and negative aspects of a patient’s life. It incorporates not only physical and emotional facets, but includes key domains such as cultural, spiritual and financial well-being (5). It is an important outcome set following diagnosis and treatment of HNC. Indeed, from a patient perspective, HRQOL may be a more important factor in treatment decision-making than survival (3,6).

A variety of patient-reported outcome (PRO) tools have been utilised to determine the effect of treatments on patients’ HRQOL and guide clinicians regarding the future management and provision of services. The National Health Service (NHS) published a Long Term Plan for Cancer in 2019 (7), which aims to support the development of a world-leading cancer service. An important factor in this planning is a Nationally recognised Cancer Quality of Life Metric (QOL Metric) (8). After extensive pilot work, in December 2020 this QOL Metric was deployed in breast, prostate and colorectal cancer patients in England. From July 2021, this QOL Metric has been used to evaluate other cancers, including a 10% sample of HNC. As the QOL Metric applies to all cancers, two well-established HRQOL instruments are being used; a cancer-specific EORTC quality of life questionnaire (EORTC-QLQ-C30) and a non-disease-specific quality of life questionnaire: EuroQol 5 Dimensions (EQ-5D). The focus of this review is how the EQ-5D has been used and how these data are reported in the HNC literature.

The EQ-5D is a validated HRQOL tool which was first developed between 1987 and 1990. The EQ-5D covers five dimensions of QOL; mobility, self-care, usual activities, pain/discomfort and anxiety/depression, and is available in over 200 languages. There are three versions of EQ-5D including EQ-5D-3L and EQ-5D-Y (both with three levels of QOL severity) and EQ-5D-5L (with five levels of QOL severity). An EQ-5D visual analogue scale (VAS) is also a key component, which allows patients to express a quantitative measure of their overall self-perceived health status.

The scores selected for each domain in both the EQ-5D 3L and 5L questionnaires can be converted to numerical values by first coding answers between 1 and 5 for each domain. The corresponding codes (e.g., 11111) can produce up to 243 unique health state vectors for the EQ-5D 3L questionnaire and 3,125 unique vectors for the EQ-5D 5L questionnaire. Procedures for calculating health utility values and reference population values for 28 countries are available through the EuroQol website. This methodology is critical for calculation of economic outcomes such as Quality Adjusted Life Years (QALYs).

The aim of this review is to explore how researchers are utilising EQ-5D including what data is reported, serial measurements over time, comparison to reference populations and calculation of health utility values and derivative health economic outcomes. Finally, studies comparing HRQOL outcomes from this questionnaire with other established HRQOL questionnaires (in particular, EORTC-QLQ-C30) will be assessed. This review will help frame the findings of the national QoL Metric in HNC and allow for the opportunity to reflect on how the data could best be utilised to inform HNC research and patient care. This review does not examine specific HRQOL findings in detail, as these are well-reported within the literature (9). We present this article in accordance with the PRISMA-ScR reporting checklist (available at https://fomm.amegroups.com/article/view/10.21037/fomm-21-91/rc) (10).

Methods

An electronic search was undertaken on the electronic databases (last updated 27/12/21): Medline via Ovid, Embase, PsycINFO and CINAHL, using a combination of MESH terms and keywords. For full details of the search strategy, see Appendix. Additionally, the HANDLE-on-QOL database was searched for studies under the categories “EQ-5D” and “Euroqol EQ-5D”. After initial deduplication of search results, title and abstract screening was undertaken in duplicate, with any uncertainty resolved by discussion among the full author team. The full texts for remaining papers, including supplementary information and appendices, where applicable, were then examined by two authors independently to determine the final list of included studies. Subsequently, two authors (EW and LT) independently undertook data extraction using a preformulated data extraction form. Any conflicts were discussed with a third author (JT) who arbitrated. Where data were incompletely reported or clarity was needed regarding a study, the corresponding author was contacted.

Studies were included if they evaluated HRQOL, self-perceived health status (by VAS) or calculated health utility values using any form of the EQ-5D questionnaire in HNC patients, or if a subgroup of HNC patients was clearly identified and reported within the study. Study designs eligible for inclusion were: randomised clinical trials, quasi-experimental studies, cohort, case-control, other longitudinal studies, cross-sectional studies or economic evaluations. Case series and case reports, as well as all review articles were excluded. We also excluded studies if they included a HNC subgroup but did not report HRQOL results for this group individually. Only papers published in English language were included.

Results

A total of 54 unique studies were included. We identified no studies published in languages other than English. There were 3 studies for which more than one report was found (5,11-15). In these instances, EQ-5D data were extracted from the study with the most readily available information, or the first published report where identical data was available. Of the 54 included studies, 20 were identified both on the Handle-on-QOL database and through other electronic searches, 24 were identified through electronic database searching only, and 7 were identified on the Handle-on-QOL database only. A further study was identified from reference list searching, and 2 more through personal communication with known experts in the field. A summary of search results, screening and selection of studies is outlined in Figure 1.

Figure 1 PRISMA diagram for identification/selection of studies. QoL, quality of life; HNC, head and neck cancer; EQ-5D, EuroQol 5 Dimensions.

Nine studies were randomised controlled trials, of which 5 compared different chemotherapy regimens. Eight studies employed a cohort design, with 1 further study using a case-control design. There were 7 longitudinal (uncontrolled) observational studies, and 3 economic evaluations. The most frequently employed study design was cross-sectional (26 studies). The most common countries for studies were: USA (n=11), UK (n=6), The Netherlands (n=6) and Canada (n=5). In addition, 8 studies were multinational. There was 1 study from Africa, based in Egypt, and no studies from the South American continent.

Sample sizes ranged from 25 to 54,492 in the included studies and were dependent on study design and the specific population included. The mean sample size across all studies was 1,321 (SD =7,674), while the median sample size was 172 (IQR, 84–329); indicating that most studies had a relatively small sample size, with some notable outliers. The characteristics of included studies are summarised in Table 1.

Similarly, study populations varied considerably. Most studies included patients treated with curative intent and disease free at the time of inclusion. However, 3 chemotherapy trials specified that patients should have recurrent, metastatic disease deemed untreatable by primary surgery/radiotherapy. Of note, the worst self-perceived health status (VAS scores) was seen in Maximiano, where 27% of patients receiving chemotherapy and 14% of radiotherapy patients were palliative (34). The next lowest VAS scores were seen in Plaschke, who included patients with incurable disease (35); then Singh (57) and Singh (58), whose inclusion criteria specified patients with recurrent/metastatic disease, of stage III or IV. In all 3 studies, chemotherapy was the primary treatment of choice. The EQ-5D index values were typically lowest in studies where patients were treated by primary radio/chemotherapy [e.g., Jones—mean utility value 0.565 in Cetuximab arm (20); Singh—mean utility value 0.57 (57)]. The worst health states occurred in the immediate post-treatment period, and then recovered to baseline values or higher in the following months where repeat measures were shown [e.g., Pottel—mean utility value 0.66 at baseline, 0.42 at 1 month post-treatment, recovering to 0.66 at and 5 months. Note, subsequent drop in utility value is due to mortality over the study observation period, not reduction in QOL (21)]. A number of additional factors were identified for increased risk of reduced QOL, such as sex, age >65, tumour stage, anatomical site and comorbidities, but these were not consistent across studies. Only 4 studies specifically measured EQ-5D at least 18 months post-diagnosis for the whole sample (20-23).

At domain-level, data were reported in 13 studies for EQ-5D 3L, with 6 studies reporting the EQ-5D-5L at domain-level (Tables 2,3). In addition, 22 studies reported EQ-5D VAS scores (Table 4). Most frequently, the EQ-5D was used to calculate health utility values (23 studies, Table 5). Reporting practice varied considerably among studies. Partial domain data were reported in 2 studies, while mean scores were reported in a further 2 studies. In 3 studies, domains were grouped to form dichotomous outcomes (problems vs. no problems). Only 8 studies included the EORTC QLQ-C30 index (Figure 2).

Figure 2 EORTC-QLQ questionnaire scores (EORTC-QLQ C30). *, estimated from figures, numerical data not available. The data are expressed as median (IQR) or mean [SD] or n (%). SD, standard deviation; IQR, interquartile range.

Studies excluded following full text appraisal are summarised in Table 6.

Discussion

With recent improvements in survival of HNC patients following treatment, HRQOL is increasingly recognised as an important metric, both for patient-centred treatment outcomes and economic utility (13). The EQ-5D is one of the most frequently employed generic QoL indices in medicine, likely due to its extensive validation in a variety of settings (including cancer) and the potential to calculate cost-utility values and QALYs. To our knowledge, this review is the first systematic examination of the use of this tool in HNC patients.

Given the versatility of the EQ-5D and multiple components/versions, it is unsurprising that its use was highly variable. However, a number of studies which specified that EQ-5D was used did not report the results of this index. We tried to contact authors for this information in these instances, or where data reporting was incomplete, but response rates were low. Several studies preferentially reported cancer-specific QOL tools such as MDASI, UW-QOL, EORTC-QLQ-C30 or EORTC-QL-H&N35 and only partially reported EQ-5D. However, these tools lack the facility to produce health index values and economic outcomes. Where multiple tools were used, EQ-5D appeared to be at least as effective at detecting global QOL and health states and discriminated between objective levels of disease severity. However, by design, the generic nature of the EQ-5D domains meant that some cancer-specific concerns and problems were not detected. It is therefore advisable to include both a cancer-specific QOL index combined with the EQ-5D to maximise the value of study data.

A number of studies only reported VAS scores or dichotomised responses into ‘problems’ and ‘no problem’ groups. While VAS gives an excellent indication of a patient’s self-perceived health status, inclusion of utility values or full domain-specific responses helps to identify discrepancies between self-perceived health status and arguably more objective functional/symptom burden. Similarly, a number of studies recorded full 5-domain data but then dichotomised this into ‘problems’ and ‘no problems’. This can be useful, particularly for simplifying the conduct and interpretation of statistical testing but means that the severity of problems cannot be extrapolated and limits comparisons between studies. It seems counterintuitive to use a tool featuring a likert-scale to indicate the burden of HNC, only to discard this feature in the analysis and presentation of results. Where such reduction of domains is necessary, we feel that inclusion of the full domain scores as supplementary data may be helpful to complement the primary analysis. Utility values, presented alone, also result in loss of granularity. Where full domain data is available (Table 2), we find that the burden following HNC treatment is symptom-related, with a large number of patients having only mild or no functional limitations, but persistent moderate-severe pain and anxiety. This information is important as it indicates where interventions to improve QOL should be targeted for maximum impact, and has implications for commissioning support services for HNC patients. Further, because a number of studies demonstrated a ceiling effect for utility values (i.e., median scores of 1 indicating optimal health). Domain-level data would help to distinguish subgroups with persistent symptom burden despite overall good health utility.

While some trends in QOL relating to clinicopathological, sociodemographic and other factors were identified in studies, interpretation requires contextualising against the reference population. For this reason, health utility values offer insights that may otherwise be missed. For example, as was discussed by Rogers (6), while a comparison between different age groups may appear to show no difference in utility values within study cohorts, the UK reference population shows higher utility values in younger patients. Therefore, comparisons only make sense when the disparity in HRQOL between HNC cohorts and an age-matched reference population is also evaluated, as real reductions in QOL may otherwise be underestimated or missed entirely.

The majority of studies were cross-sectional in nature, with timing of HRQOL assessment varying between: at diagnosis, immediately after treatment, and various post-treatment timepoints. This makes comparisons between such studies challenging, and due to the temporal changes observed in longitudinal studies that measure across different pre and post-treatment intervals (21,24), may limit the value of such studies to inform clinical practice. The UK-wide EUROQOL assessment assesses QOL at 18 months post-diagnosis, giving a reasonable indication of the long-term HRQOL burden following treatment for HNC, but we found few studies that selected this timepoint. Although the same limitations described for cross-sectional analyses apply, a consistent post-treatment interval as is used by the EUROQOL group does provide a useful framework for establishing longer-term patient outcomes and identifying potentially unmet needs, particularly if the assessment is repeated at regular intervals to assess the impact in any changes to service provision, diagnostic or treatment pathways.

Most of the included studies evaluated patients with a primary diagnosis of HNC who were treated with curative intent, excluding those with recurrent, metastatic of palliatively treated HNC. However, we found that these latter cohorts had the greatest HRQOL deficit and are likely under-represented in research. Although recruitment of such participants may pose additional challenges and analysis can be complicated by a high mortality rate, these especially vulnerable patient cohorts represent an important subset of the HNC population and should only be excluded where justifiable and necessary. Similarly, only Davies (42) specifically enumerated the number of patients whose health utility value was <0 (i.e. a health state deemed worse than death) (25), while several studies provided ranges that clearly included <0 utility values. This cohort, although fortunately a very small proportion of HNC patients could be important to evaluate in more detail, as they are likely not appropriate for curative treatment, and so effective palliation methods to improve HRQOL are an important objective for which there is a dearth of evidence specific to HNC (25).

Perhaps surprisingly, in 12 of the 23 studies that reported health utility values, the mean plus one standard deviation includes 1 (i.e., perfect health), indicating a ceiling effect. While this is a positive finding, showing that health after HNC can return to a state equivalent to matched reference populations without HNC, it may be reflective of tendency to sample/recruit participants with less advanced disease more suitable to local surgical excision without extensive reconstruction or adjuvant treatments. In these instances, the importance of domain-specific analyses is highlighted, as further improvements can only come from the subsets of patients with problems and should be tailored towards those with the more extreme functional/symptom deficits to maximise impact. This finding may also reflect the low specificity of the EQ-5D for HNC, and it may be that the VAS offers better sensitivity for detecting the impact of these problems on patients’ QOL.

Despite being one of the most widely used HRQOL indices in cancer, few papers reported the EORTC-QLQ-C30. This index is included in the current EUROQOL national HRQOL assessment and complements the EQ-5D by including the more cancer-specific issues and concerns patients may experience, regardless of whether these appear to impact overall health or global QOL. This large-scale assessment will also enable more thorough validation of the EQ-5D and EORTC-C30 in HNC populations and specific subgroups, such as those treated palliatively, or HPV-related oropharyngeal cancers, whose demographic features differ from the majority of HPV negative HNC patients. Further implementation of these indices should be undertaken alongside HNC-specific assessments to ensure that outcomes are an accurate reflection of specific patient subsets’ needs and concerns.

This review is limited to tabular and narrative evidence synthesis, due to the high variability of studies and characteristics found. If more interventional studies are undertaken in well-defined HNC cohorts, with EQ-5D assessments undertaken at consistent intervals, it may be possible to compare these studies by meta-analysis. We also only included studies published in English language, although it should be noted that no potentially relevant studies were identified that were not available in English.

Recommendations for future research

We suggest that future research should aim to evaluate the EQ-5D alongside cancer and HNC-specific QOL indices [or alternatives to QOL indices such as the Patient Concerns Inventory (13,77)] in specific HNC cohorts, controlling for demographic, clinicopathological and treatment factors. Further validation of these disease-specific indices in different languages and cultures is important to enable better global engagement with HRQOL research in HNC patients. We observed that patient populations from Africa and South America were underrepresented in this review.

There is clear evidence that HRQOL is an important outcome for HNC research, and we see little justification to avoid including this as at least a secondary outcome in any interventional study within the field. Future researchers should plan for this either within the main patient cohort or as a sub-study.

Analysis of extreme outcomes should be considered where these exist, even if numbers are low—both indices indicating near perfect or very poor HRQOL may enable a transition toward more individualised patient-centred care and may identify important protective or deleterious factors that may influence choice of treatment, or indeed help inform clinicians and patients whether treatment is the correct option.

We found that use and reporting of the EQ-5D QOL questionnaire varied widely between studies, making comparisons between different HNC cohorts difficult. Standardised reporting criteria for EQ-5D should be developed. We recommend as a minimum that both VAS and utility values are presented, as these reflect complementary but distinct outcomes. Inclusion of full domain-level data may be appended as supplementary information, alongside more detailed analysis of extreme results, particularly if these are unexpected. The authors of this review appreciate that it may not always be feasible for these values to be presented within main study publications and would consider supplementary published material containing this data to be a valuable asset for future research.

Acknowledgments

We would like to thank Professor Simon Rogers, Professor Anastasios Kanatas and Mr. Derek Lowe for their input and feedback during the review process.

Funding: None.

Footnote

Provenance and Peer Review: This article was commissioned by Guest Editors (Simon N Rogers, Anastasios Kanatas) for the series “Health-Related-Quality of Life in Head and Neck Oncology” published in Frontiers of Oral and Maxillofacial Medicine. The article has undergone external peer review.

Reporting Checklist: The authors have completed the PRISMA-ScR reporting checklist. Available at https://fomm.amegroups.com/article/view/10.21037/fomm-21-91/rc

Peer Review File: Available at https://fomm.amegroups.com/article/view/10.21037/fomm-21-91/prf

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://fomm.amegroups.com/article/view/10.21037/fomm-21-91/coif). The series “Health-Related-Quality of Life in Head and Neck Oncology” was commissioned by the editorial office without any funding or sponsorship. The authors have no other conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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