This cross-sectional study compared SF-36v2TM scores [26] collected from participants in the recently established UK ME/CFS Biobank [27]. The Biobank cohort included people with ME/CFS, PWMS and HCs who had provided data and samples for future research. The data were collected between December 2013 and February 2015 from a population resident in the same geographic area. Participants in the UK ME/CFS Biobank with ME/CFS and MS needed a medically confirmed diagnosis, and people with ME/CFS were required to meet the CDC 1994 [11] or Canadian criteria [12].

PWMS were chosen as a suitable comparison group because (1) both ME and MS are classified as a neurological disease in the World Health Organization’s International Classification of Diseases, Tenth Revision (ICD-10; G93.3) [28]; and (2) MS (ICD-10; G35) also presents with fluctuating chronic fatigue and a number of other similar symptoms, including orthostatic intolerance and cognitive impairment [29].

Recruitment for the UK Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) Biobank

Between 2012 and 2015, the UK ME/CFS Biobank collected data and samples from participants in London and East Anglia; details of the UK ME/CFS Biobank protocol have been previously published [27]. Participants were recruited through National Health Service general practices and specialist services with support from the National Institute for Health Research (NIHR) clinical and research networks. Staff from the local NIHR Clinical Research Network (formerly the Primary Care Research Network) approached general practices in Norfolk and Suffolk to seek willingness to recruit participants. Once local ethical approval was in place, participating practices sent letters to registered patients with a diagnosis of ME/CFS, people with a diagnosis of MS, and potential HCs, inviting them to participate in the study. Three HCs were invited for each person with ME/CFS to be recruited. A higher response and recruitment rate was anticipated from people with the disease because people with ME/CFS are underrepresented in research studies and are therefore motivated to participate [34]. At the same time, specialty clinics in London, Norfolk and Suffolk approached their patients with ME/CFS and MS. Posters seeking HC volunteers were placed in general practice surgeries and institutes of higher education in the same regions. A full description of recruitment procedures can be found in the paper describing the establishment of the UK ME/CFS Biobank [27].

All participants conformed to the inclusion/exclusion criteria described in Table 1. The study protocol was identical for all participants, regardless of category of recruitment, although questions related to MS and ME/CFS were omitted for HCs.

Table 1 UK Myalgic Encephalomyelitis/Chronic Fatigue Syndrome (ME/CFS) Biobank: inclusion and exclusion criteria Full size table

A clinical researcher assessed all potential Biobank participants at the recruitment stage using a bespoke ‘Symptoms Assessment’ form to confirm eligibility to participate in the study. All participants donated blood (some of which was used for clinical tests to exclude alternative diagnoses), completed a clinical assessment, and filled out study questionnaires, including the SF-36v2TM and the ‘Participant Questionnaire’. Together, these tools enabled the characterisation of participants with ME/CFS and MS according to clinical phenotype and disease severity.

Sample Size for the Proposed Analysis

A subsample of 156 individuals (52 with ME/CFS, 52 with MS, and 52 HCs) was drawn from the Biobank cohort. The participants with ME/CFS were randomly drawn from the list of recruited participants and matched by sex and age group with individuals from the control groups. This sample size was considered sufficient to detect differences in SF-36v2TM mean/median scores ≥ 5 between people with ME/CFS and each of the two comparison subgroups, with a power of 90% and at a significance level of 0.05 using norm-based scores. We used a conservative 5-point difference in norm-based scores as the minimally important difference (MID), even though the recommended MID varies among the summary measures and each specific domain. For example, an MID of 2–3 points is considered reasonable for the Physical Component Summary (PCS) domain [26], based on clinical trials with patients with peripheral arterial disease. Using a similar approach in different trials, Ware et al. suggested different MIDs for the SF-36v2TM scales, ranging from 3.1 to 5.7, the higher MID being recommended for the General Health (GH) domain (5.7), Vitality (VT) domain (5.5) and the Mental Health (MH) domain (5.5). The MIDs recommended for the summary measures were 3.1 (PCS) and 3.8 (Mental Component Summary; MCS) [26].

Data Collection

The SF-36v2TM is a health survey that uses 36 questions to collect information about functional status and well-being from respondents. These questions evolved from medical outcome studies carried out in the 1980s and 1990s, and were developed with psychometric rigour to ensure that the information captured was reliable [26]. The answers to these unambiguous questions form eight different scales, known as domains. Reports from studies using this instrument evidenced an increase in reliability and validity of scores in a diverse range of populations and settings when compared with other outcome measure instruments [30]. The SF-36v2TM is recognised as a reliable tool that uses generic health measures that are not age-, disease- or treatment-specific; it has been used and validated across different populations [31]. The version used employs language familiar to people living in the UK [32]. A full report on the development of this research instrument, and a detailed description of its ability to access functional status and well-being, has been published elsewhere [26].

The SF-36v2TM considers physical and mental functions resulting in eight distinct domains, which are summarised into the PCS and the MCS [26]. The PCS comprises four domains and is used to profile functional health: Physical Function (PF) measures the ability to undertake everyday activities; Role Physical (RP) measures limitations in the ability to work; Bodily Pain (BP) measures the impact of pain on activity; and GH looks at the general health perceptions of the respondent. Low scores in the PCS indicate reduced functional status.

The four domains making up the MCS are measures of VT, with questions about energy and tiredness; Social Function (SF); MH, which asks about psychological well-being, anxiety and depression; and Role Emotional (RE), which considers role limitations due to emotional problems. Since the VT domain is included in the MCS, the physical symptoms of ME/CFS and MS, especially fatigue, are likely to reduce that score, which should be borne in mind when interpreting results.

In this study, the SF-36v2TM instrument was used to compare disability (measuring functional status and well-being) and served to assess HRQoL. In addition to the SF-36v2TM questionnaire, all Biobank participants also completed the Participant Questionnaire, which was developed by the UK ME/CFS Biobank team to capture information on socioeconomic, demographic, clinical and family history, and which was piloted prior to its use. Most of its questions about symptoms were taken from validated questionnaires [27, 33,34,35]. Examples of the questions on employment and income used in the Participant Questionnaire can be seen in Online Appendix 1.

The time lag between disease onset and the response to the questionnaires varied between participants. For the analyses carried out for this study, we used the resultant demographic (sex and age), clinical (functional status and well-being), and socioeconomic (education, accommodation, employment, and income) data. Income data refers to income at the time of recruitment and, when relevant, to 6 months before the disease showed symptoms.

Data Analysis

Answers to the SF-36v2TM questions were scored in health domains grouped into the PCS and the MCS using the SF Health Outcomes™ Scoring Software 4.5 [36]. Although actual scores for individual questions may vary within the general population, these average scores become 50 out of a possible 100 across all questions when they are norm-based with an SD (σ) of 10 [26]. Therefore, norm-based scores compare results with others who have completed the SF-36v2TM rather than against fixed criteria.

Data were analysed using Stata 14.0 software [37]. Bivariate analyses were used to compare people with ME against PWMS or HCs using the Chi-square test and Chi-square for trend to assess the association between categorical variables; the t test or Wilcoxon rank-sum test were used for continuous variables.

In addition to using the SF-36v2TM scores, we also looked at the effect of ME/CFS on some socioeconomic variables, which could also impact HRQoL. For these analyses, we used the variables ‘current income’, ‘employment’, ‘hours of work’ and ‘benefits’, using conditional logistic regression as recommended for paired design [38].