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Comparative quantitative survey of patient experience in Barrett's oesophagus and other gastrointestinal disorders.

Objective
To assess health-related quality of life in patients with non-dysplastic Barrett's oesophagus (NDBO) and endoscopically treated dysplastic Barrett's oesophagus (DBO).


Design
This quantitative, self-administered questionnaire study was conducted across three National Health Service hospitals. Data were collected from three other cohorts; gastro-oesophageal reflux disease (GORD), colonic polyp surveillance and healthy individuals. Fisher's exact and Spearman's rank correlation tests were used for analysis. Propensity score matching adjusted for age, sex and comorbidities.


Results
687 participants were eligible for analysis (NDBO n=306, DBO n=49, GORD n=132, colonic polyps n=152 and healthy n=48). 53% of NDBO participants reported similarly high cancer worry, comparable to DBO (50%, p=0.933) and colonic polyp participants (51%, p=0.355). Less cancer worry was reported in GORD participants (43.4%, p=0.01 vs NDBO). NDBO participants reported anxiety in 15.8% and depression in 8.6% of cases, which was similar to the other disease cohorts. Moderate or severe heartburn or acid regurgitation was found in 11% and 10%, respectively, in the NDBO cohort, comparable to DBO participants (heartburn 2% p=0.172, acid regurgitation 4% p=0.31) but lower (better) than GORD participants (heartburn 31% p=<0.001, acid regurgitation 25% p=0.001). NDBO participants with moderate or severe GORD symptoms were associated with higher rates of anxiety (p=<0.001), depression (p=<0.001) and cancer worry (p=<0.001). NDBO patients appropriately perceiving their cancer risk as low had lower rates of cancer worry (p=<0.001).


Conclusion
This study provides insight into the problems Barrett's oesophagus patients may face. Future care pathways must be more patient focussed to address misconceptions of cancer risk, oesophageal cancer related worry and GORD symptom control.


SUPPLEMENTARY TEXT
Participant Groups and Recruitment 1.1.
All participants who completed this one-off questionnaire, were >18 years old with no upper age limit. Those recruited in person were instructed, where possible, to complete the survey at home at a time independent (>4 weeks) of a hospital appointment in order to minimise any acute impact on their responses.
 Non-dysplastic Barrett's oesophagus. All patients enrolled in surveillance who have a diagnosis of BO irrespective of current histology. A lack of intestinal metaplasia on most recent histology was not a criterion for exclusion providing future surveillance was planned.
Patients were identified from endoscopy booking databases or outpatient clinic and recruited, when possible, via postal invite at a time independent of their surveillance test.
 Barrett's oesophagus with dysplasia or early OAC. Patients who had previously undergone ET for DBO (low grade dysplasia, high grade dysplasia and indeterminate for dysplasia) or BO with early OAC now undergoing surveillance. These patients were identified and recruited from two tertiary treatment centres within the North West of England (Salford Royal Foundation Trust and Central Manchester Foundation Trust). Recruitment followed two strategies. Patients were identified via local endoscopy surveillance databases and invited to complete the questionnaire via post or during a routine hospital appointment (clinic or endoscopy) and recruited in person.
 Gastroesophageal reflux disease. Included participants without BO who have been diagnosed with any of the following in primary or secondary care; "gastroesophageal reflux with oesophagitis", "gastroesophageal reflux without oesophagitis", "gastroesophageal reflux disease", "GORD", "acid reflux", "heartburn" or "dyspepsia". These participants have a similar symptom paradigm to BO patients with significantly less cancer risk(1). This cohort was chosen to help determine whether detriments to HRQoL in BO patients are symptom related or perhaps due to other factors. Participants were recruited via postal invite or in person at the time of a hospital appointment (clinic or endoscopy).
 Colonic polyp surveillance. Participants undergoing endoscopic surveillance for colonic adenomas without a concurrent diagnosis of BO. These patients also have a chronic precancerous condition requiring endoscopic surveillance at similar time intervals to BO patients (2). Those undergoing surveillance solely due to a personal history of colorectal  Healthy. Healthy or general population norms are not available for all measures. Norms available for the most widely used measures such as the SF-36 may be considered outdated, lack regional datasets, use varying administration techniques and under-represent certain social classes or ages (3). To provide a regional healthy population control, participants without significant chronic disease were identified by coding systems and recruited via postal invite. Hospital staff members, medical and non-medical, who perceived themselves to be healthy without active or significant chronic disease were also eligible for inclusion.
This group was chosen as a control to provide insight into the impact of co-morbid disease.

SF-36 Norm based scoring
Raw scores of SF-36 are initially converted to 0-100 scores, with higher scores indicating better HRQoL. Comparing population samples using the original 0-100 scoring metric has led to misinterpretation of peaks and troughs due to differences in the ceilings and floors of the scales. In particular general health (GH), energy and vitality (VT) and mental health (MH) measure wide score ranges and set the ceiling relatively high by measuring very favourable levels of those domains (8). In comparison physical functioning (PF) and role limitations physical (RP) measure a narrower range based on a lower ceiling, therefore the most favourable levels (a score of 100) represents an absence of limitations rather than well-being. Therefore, significant differences can occur between the domain 0-100 scores irrespective of the population in question leading to misinterpretation (9).
General population norms offer an answer to this by providing meaningful comparisons across scales and a more robust interpretation of disease impact. For example, the general population norm for PF is 80-90 compared to VT which is around 60. Conversion of 0-100 scores into T scores (normbased scores) with a mean of 50 and standard deviation of 10 also allows easier interpretation without cross referencing to norm tables. The further a score is from the mean the greater the likelihood it is above or below the average for that domain. Generally speaking for interpretation of groups, a deviation from the mean (50) of 3 points (0.3 standard deviations) is deemed clinically significant(9).
Mental component summary (MCS) and physical component summary (PCS) scores are weighted to reflect correlations with all 8 health domains. They are calculated using factor score co-efficient from prior normative data (10,11). Once again, population based co-efficient can be used although prior research has shown very similar outcomes when comparing US and UK co-efficient in both cross sectional and longitudinal surveys (12).
However, the use of previously published norms also has a number of potential issues. Firstly, the most widely used norms, particularly in the UK, have been conducted in the 1990's (3,13,14) and 2000's (15,16). These norms will therefore not reflect subsequent changes in national socioeconomic inequalities, health and life expectancy for example (17). Secondly, when conducting a regional study ideally a regional norm should be used. Prior studies have shown significant differences in regional HRQoL data, although the reasons for this have not always been clear (3,18). Unfortunately, adequately numbered regional norms remain sparse. Thirdly, HRQoL output is influenced by age, gender and socioeconomic status (19). Therefore, one must also consider whether a particular norm adequately measures these variabilities. For example, the Oxford Healthy Life Survey, one of the most widely used UK norms had an upper age cut off of 64 years (13). Fourthly, the mode of questionnaire administration also differs amongst norms and may influence the data captured. For example, interview captured data compared to self-completed methods may introduce social desirability bias(20-22). Perkins and Sanson-Fisher found higher mean scores via interview administration, in particular in mental dimensions scores (23). This may be because participants are less likely to disclose sensitive information during an interview. Fifthly, some have postulated but not proven that the order in which the SF-36 is placed with simultaneous questionnaires may impact the scores (24). Finally, and arguably the greatest limiting factor is the availability of norm data. Many publications provide inadequate information to facilitate further use such as missing standard

SF-36 Data Management
All individual respondent 0-100 dimension scores in this study were converted to an age and sex matched z scores for each domain using a previously published UK norm(3) (UK omnibus sample).
This national sample was chosen due to the availability, completeness of data and inclusion of older age ranges. Z scores for all domains were then converted to t scores to give a mean of 50 and standard deviation of 10.
 e.g. Physical Functioning z score = (PF -UK norm mean)/standard deviation of UK norm.
 e.g. Physical Functioning t score = 50 + (PFz x 10) Subsequently the MCS and PCS scores were calculated using previously published UK mental and physical factor co-efficient data (12). To achieve this, aggregate MCS and PCS scores are calculated first. Part of this equation can be seen below;  Aggregate MCS= (PFz x factor coefficient) + (MHz x factor coefficient) + ……….
The aggregate MCS and PCS scores were then converted to t scores in the same manner as before.
Please note, as per SF-36 author guidelines, in order reach a summary score 7 out of 8 domains must be available with MH present for MCS and PF present for PCS score to be valid(9).
The cancer worry scale (CWS) is a 6-item score originally designed to measure cancer specific worry and impact of worry on daily functioning among women at risk of breast and ovarian cancer (25).
Subsequently it has been successfully used in assessing fear of developing cancer or cancer recurrence in breast, ovarian and bowel cancer settings (26)(27)(28). This worry score was chosen because it encompasses both the frequency and severity of worry which are considered the most significant factors when assessing this trait (29,30).The wording of the items can also be easily modified to assess other cancer groups (31). In this study participants were asked in relation to the cancer specific to their diagnosis whereas healthy participants were questioned in relation to cancer in general. The score uses a 4-point Likert scale between "Never" (1 point) and "almost always" (4 points). Total scores therefore range between 6 and 24 with higher scores indicating worse cancer specific worry. Recent re-validation was undertaken by Custers and colleagues who investigated the use of the CWS as a screening tool and provided useful score cut offs via ROC analysis against the  (FCR). Based on the highest proposed RCRI cut off to detect "severe" levels of FCR as the gold standard the optimal CWS cut off was 11 vs 12 (sensitivity 88%, specificity 81%, NPV 97%, PPV 46%). When using a slightly less stringent RCRI cut off to detect "high" levels of FCR the optimal CWS cut off was 9 vs 10 (sensitivity 88%, specificity 73%, PPV 70%, NPV 90%) (32). For the purposes of this study the following cut offs were adopted; <10 as negative, 10-11 as borderline and ≥12 as positive. This score was accompanied by an assessment of both numerical and perceived risk of developing cancer using a 7-point Likert scale.

scale)
The hospital anxiety and depression score (HADS) is the most extensively used and validated screening tool for anxiety and depression (33)(34)(35). It has been used in a variety of healthcare settings including cancer patients (36). The HADS consists of 14 items, 7 relating to anxiety and 7 relating to depression symptoms. Items are ranked on a 4-point Likert scale between 0 and 3 with higher scores relating to more severe anxiety or depression. The sum of these items produces a HADS anxiety (HADS A) and HADS depression (HADS D) total score. The author proposed cut off points for these scores are; 0-7 suggests the absence of anxiety and depressive symptoms, 8-10 indicates the presence of symptoms to a moderate degree with doubtful cases, ≥11 indicates significant symptoms which correspond to confirmed cases (33). These thresholds were found to be robust on further scrutiny and have therefore been adopted in this study (37).

Scale)
The Gastrointestinal symptom rating scale (GSRS) consists of 15 items producing 5 gastrointestinal domains (abdominal pain, reflux, indigestion, diarrhoea and constipation). This extensively used symptom specific score measures frequency, intensity, duration and impact on daily life. It can identify clinically important change and discriminates well between each domain, most markedly in reflux and indigestion (38,39). This study adopted a 4-point Likert scale with higher scores indicating worse symptoms (0= None, no symptoms or very rarely, 2= mild, occasional or mild symptoms, 2= moderate, frequent symptoms that impact on some social activities, 3= severe, continuous symptoms that impact most social activities). There are no defined score cut offs.