Work package 2: identifying and optimising medical causes of symptoms

Aims:

1. To determine the presence and relationship between fatigue, pain and FI in people with IBD and the desire for intervention for these symptoms (WP2b).
2. To develop, in collaboration with people with IBD and expert clinicians, a checklist and management algorithm for potentially medically reversible causes of fatigue, abdominal pain and faecal urgency/FI in IBD (WP2a).
3. To test the checklist and algorithm for people with IBD who want help for symptoms and to determine what proportion have potentially reversible medical causes and if symptoms improve if these are addressed (WP2c).

Note: To enhance the flow of this report, WP2b is reported before WP2a.

Work package 2b: postal/online questionnaire survey

Paper 8: Fatigue, pain and faecal incontinence in adult inflammatory bowel disease patients and the unmet need: a national cross-sectional survey14

Conference presentation: An abstract was presented at the European Crohn’s and Colitis Conference, Copenhagen in 2023. https://doi.org/10.1093/ecco-jcc/jjac190.0099

Some texts in this section have been reproduced with permission from Hart et al.14 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution CC BY-NC-ND 4.0) licence, which permits others to copy and redistribute the material in any medium or format, provided the original work is properly cited. Material may not be used for commercial purposes. See: https://creativecommons.org/licenses/by-nc-nd/4.0/deed.en. The text below includes minor additions and formatting changes to the original text.

Methods: A survey (online or postal), incorporating validated tools and demographic details, was sent to unselected UK clinic and UK IBD-BioResource patients. As the COVID-19 pandemic made clinic recruitment impossible, additional participants were recruited from social media sources. Using the validated Patient Reported Outcomes Measurement Information System (PROMIS) tools, the following were used to define the presence of symptoms: fatigue: PROMIS fatigue T-score of ≥ 60; pain: PROMIS pain intensity T-score of ≥ 60; PROMIS bowel incontinence: raw score of ≥ 50. Disease activity was reported via the relevant PRO-2 score, IBD-Control, anxiety [Generalised Anxiety Disorder-7 (GAD-7)], depression [Patient Health Questionnaire-9 items (PHQ-9)] and QoL [EuroQol-5 Dimension, five-level version (EQ-5D-5L)]. We invited participants until the RCT sample (below) was recruited.

Key findings: A total of 8486 responses were received (7716 online, 770 postal); 4176 reported CD, 4255 UC or other form of IBD. There were 3281 men and 4883 women with a median age of 51 years (range 18–92 years); 30% (2550) reported fatigue, 21% (1766) pain and 54% (4565) FI in the past week; 10.9% (925) reported all three symptoms in the past week (Table 2). Table 3 shows the correlation between symptoms. Participants scored severity and impact a mean between 3.3/10 and 4.8/10; 56% of all respondents (not just those with symptoms) ‘definitely’ wanted help for fatigue; 42% wanted help for pain; 53% wanted help for FI; 29% reported ‘definitely’ wanting help for all three symptoms (Table 4). Anxiety and depression are shown in Table 5.

Relation to other parts of the programme: This study confirmed that fatigue, pain and urgency/FI are common in IBD and, for the first time, reports the coexistence and unmet need for help with these symptoms. The survey respondents who met eligibility criteria for the RCT (below) were invited until the RCT was fully recruited.

Limitations: Because of the COVID-19 pandemic, we had to change our original intention of recruiting an unselected sample from clinic databases and the UK IBD-BioResource, as clinics were unable to recruit for a prolonged period; so, we added ethics-approved social media recruitment to enable us to recruit enough people to the RCT. This enabled us the achieve a large sample size, but we were therefore unable to report prevalence as some participants were self-selected. However, sensitivity analyses did not find major differences between selected and unselected participants.

Figure 7 shows a graphical abstract of the survey findings.

FIGURE 7 Graphical abstract for the IBD-BOOST survey. (Figure not reproduced here; see the original article.)

We also conducted a supplementary QoL analysis (not in the original proposal):

Paper 9: Impact of fatigue, pain, and bowel incontinence on the quality of life of people living with Inflammatory Bowel Disease: a UK cross-sectional survey15

Some materials within this section have been reproduced with permission from Roukas et al.15 These are Open Access articles distributed in accordance with the terms of the Creative Commons Attribution (CC BY 4.0) licence, which permits others to distribute, remix, adapt and build upon this work, for commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by/4.0/. The text below includes minor additions and formatting changes to the original text.

Conference abstract: https://doi.org/10.1093/ecco-jcc/jjac190.0063

Aims: To assess the impact of fatigue, pain and bowel incontinence symptoms on health-related QoL in IBD.

Methods: In the IBD-BOOST survey, over 26,000 people with IBD across the UK were approached; 8486 participant-completed surveys were returned. Participants’ QoL was measured using the EQ-5D-5L questionnaire, and their QoL was calculated on a scale ranging from 1 (perfect health) to −0.594 (worst health). Item non-response was imputed. Stages of linear regression models assessed the associations of symptoms, with QoL controlling for IBD type, sociodemographic characteristics, comorbidities and, in further analysis, for IBD activity and IBD control.

Key findings: The EQ-5D-5L questionnaire was fully completed by 8093 (95.4%) participants [mean age 50 years [standard deviation (SD) 15]; 49% with CD]. The mean QoL was 0.76 (SD 0.23). From the three IBD-related symptoms, pain was associated with the largest QoL decrement (−0.159) followed by fatigue (−0.140) and bowel incontinence (−0.048). Co-occurrence of pain and fatigue further reduced QoL. Clear graded associations were observed between symptom severity and QoL decrements (p < 0.001). Depression and anxiety were also associated with significant QoL decrements (−0.102 and −0.110 for moderate-to-severe anxiety and moderately severe depression, respectively). Worse IBD Control score and higher IBD activity were associated with lower QoL.

Relation to other parts of the programme: We report strong associations between symptoms of pain, fatigue, FI, anxiety and depression and their severity with QoL in IBD. These estimates could inform further IBD management interventions.

Work packages 2a and 2c: checklist and algorithm development and testing

Some materials within this section have been reproduced with permission from Stagg et al.16 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY-NC 4.0) licence, which permits others to distribute, remix, adapt and build upon this work, for non-commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by-nc/4.0/. The text below includes minor additions and formatting changes to the original text.

Development of the checklist and algorithm: changes from the original proposal

We originally proposed using the nominal group technique in a single meeting to develop a checklist and algorithm. However, preliminary consultation with stakeholders, particularly 10 senior gastroenterologists, found that there was almost no initial consensus on what to include in this algorithm. Views polarised around a very minimal checklist and a much more detailed (and onerous and costly) set of questions and investigations, which PPI suggested might not be acceptable. Therefore, we decided that we needed a lot more work on the development stages and conducted several rounds of online consultations with expert gastroenterologists and IBD specialist nurses, in addition to patients with IBD, and a face-to-face meeting with a stakeholder group before finalising the content.

The aim was to produce a structured assessment and management algorithm that could be implemented by a specialist nurse in secondary care. More advanced or specialist options were deliberately not included, as the goal was to achieve a feasible algorithm for assessment and management that could be readily adopted in NHS services. Evidence from key previous systematic literature reviews was summarised to determine the main risk factors for fatigue, abdominal pain and urgency/FI in IBD. A list of candidate actions (i.e. clinical tests or interventions) was developed and refined over a series of individual and group face-to-face meetings and e-mail correspondence until agreement was reached. Simultaneously, the team were developing the online, self-management programme to address psychosocial aspects of fatigue, pain, and urgency/FI, and so, while considered very important, these psychosocial factors (such as addressing anxiety, stress and sleep quality) were not included in the Optimise algorithm.

Potential underlying conditions/causes were divided into (1) those which were known to affect symptoms but were considered non-modifiable (e.g. age or disease type); (2) psychosocial factors suitable to be included in the separate online intervention and so not included in Optimise and (3) ‘medically reversible’ causes that would ideally be addressed prior to a patient undertaking the separate online self-management programme.

Firstly, the symptom checklist aimed to identify ‘red flags’ that needed reasonably prompt medical attention before other issues were considered. Red flags aimed to identify if pain could be caused by strictures or adhesions leading to subacute obstruction or bowel perforation, as well as melaena, unexplained fevers and new rectal bleeding. Appendix 2, Table 9 presents consensus ‘red flags’ and the questions asked on the patient-completed symptom checklist to identify each ‘red flag’. Participants were contacted by a nurse about possible red flags on their checklist responses by telephone or e-mail, and follow-up questions were asked to distinguish between new-onset/acute or severe symptoms and more chronic ongoing issues.

If no red flags were present, or if red flags had been investigated or addressed, then a nurse reviewed a patient’s checklist responses to screen for possibly active IBD. Active IBD was diagnosed using a combination of faecal calprotectin (FCP) sample results and patient responses to the IBD-Control questionnaire,44 which was incorporated in the checklist. Possibly active IBD was defined as FCP ≥ 200 μg/g AND/OR an IBD control score ≤ 13, which is the author-recommended cut-off threshold to indicate likely active disease (a high score is better control).44 Nurses reviewing each patient’s checklist followed local clinical protocols for investigating or treating potentially active IBD.

The checklist included validated questionnaires for fatigue, pain, FI, anxiety, depression and QoL.

The algorithm

Once the completed symptom checklist and a FCP result (see below) were received, clinical staff consulted the clinical algorithm to assess and manage any potentially reversible medical causes of pain, fatigue and urgency/FI (Figure 8).

FIGURE 8 The Optimise algorithm. Reproduced with permission from Stagg et al.16 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY-NC 4.0) licence, which permits others to distribute, remix, adapt and build upon this work, for non-commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by-nc/4.0/. The figure includes minor additions and formatting changes to the original text. (Figure not reproduced here; see the original article.)

The full algorithm (see Appendix 2, Figure 22) was designed to be nurse-led and identified if actions (further clinical investigations or interventions) were indicated. A manual was created to ensure a standardised approach for navigating the algorithm. Nurses were provided with this manual and trained on its use as part of site initiation training before study commencement.

Note: the COVID-19 pandemic necessitated the reduction of the planned sample size to 200 and a change of design from a full study to a feasibility study.

Paper 10: Optimising fatigue, abdominal pain and faecal incontinence in people with inflammatory bowel disease. Feasibility study of a checklist and algorithm for initial nurse-led management: the IBD-BOOST Optimise study16

Aim: To assess feasibility of using the checklist and algorithm in people with IBD reporting fatigue, pain and/or urgency/FI. Table 6 shows the research questions for this WP.

Methods: We conducted a multisite, non-randomised intervention feasibility study testing the feasibility of the Optimise patient-reported symptom checklist and nurse-administered management algorithm to manage common medical causes of IBD-related fatigue, pain and urgency/FI. Potentially eligible Optimise participants were identified via our previous survey (above). The symptom checklist was self-administered, completed online or on paper. A FCP sample kit was completed and posted to a central laboratory by the participant.

An IBD nurse or another trained member of the clinical team at each hospital site reviewed the checklist and the FCP test result to screen for red flags, any indication of active disease and potentially reversible causes, following the steps in the algorithm. A telephone call or clinic visit could be used, if required, to clarify any unclear findings.

Participants were asked to complete a follow-up questionnaire by post or online only if an action (for red flags, potentially active disease or a prescribed test or intervention for fatigue, pain and/or urgency/FI) was indicated by the clinical algorithm and not declined by the participant.

Due to the COVID-19 pandemic, we could only recruit four clinical sites from the originally planned 20 sites, and the target sample size was reduced from 1000 to 200 participants. This pragmatic change meant that a formal sample size calculation was not possible.

Absolute frequencies and percentages were used to calculate and present feasibility outcomes. The proportion of study participants with (1) red flags, (2) active IBD disease and for whom algorithm-informed tests or interventions were advised/prescribed for (3) fatigue, (4) pain and (5) urgency/FI was calculated for primary clinical outcomes.

We conducted qualitative interviews with nurses implementing the algorithm.

Key findings: About 515 individuals from four hospital sites, reporting fatigue, pain or urgency/FI in the previous survey were invited to participate, of whom 201 (39%) consented. Figure 9 presents a flow of participant recruitment, assessment, management and follow-up throughout the study. Of the 201 consenting participants, 194 (96.52%) participants completed the Optimise symptom checklist, of whom 157 (81%) returned a postal FCP sample. Five (3%) participants reported ‘red flags’, and 31/157 (20%) participants had a FCP result ≥ 200 μg/g, of whom 12 (8%) were judged to have likely active inflammation when clinical symptoms and disease history were reviewed. The algorithm suggested at least one clinical test or intervention for fatigue, pain, or urgency/FI in 67 (43%) participants, of whom 25 (37%) declined. Among 87 participants for whom clinical actions were indicated, 57 (66%) completed follow-up outcomes 3 months after algorithm implementation. The study was not powered to detect a difference in clinical outcomes at 3 months. Missing items ranged from 0% to 41% for clinical, patient-reported outcome measures at baseline and follow-up.

FIGURE 9 Flow chart of participants for Optimise. a, Possible for a participant to simultaneously experience red flags, demonstrate possibly active IBD, and require a consultation for fatigue, pain, of urgency. Reproduced with permission from Stagg et al.16 This is an Open Access article distributed in accordance with the terms of the Creative Commons Attribution (CC BY-NC 4.0) licence, which permits others to distribute, remix, adapt and build upon this work, for non-commercial use, provided the original work is properly cited. See: https://creativecommons.org/licenses/by-nc/4.0/. The figure includes minor additions and formatting changes to the original text. (Figure not reproduced here; see the original article.)

The three intervention nurse interviewees were very positive about the Optimise algorithm, felt that it was clearly a suitable role for nurses to implement in NHS clinical practice and that it was simple to implement with minimal training and central support. All three were fully supportive of this as an appropriate and useful nursing role.

There were very few suggestions for changes or improvement. The nurses repeatedly emphasised the perceived benefits to patients and that patients were very glad and reassured to have their symptoms checked out.

The interview findings are summarised in Appendix 2, Table 10, using verbatim quotes in italics. One nurse succinctly summarised what all three conveyed in the interviews: ‘Algorithm was incredibly helpful: simple, straightforward and easy to follow’ (Nurse 1).

Optimise patient participant free text feedback is summarised in Appendix 2. Most were positive about the experience.

Figure 10 presents a graphical abstract of the Optimise study.

FIGURE 10 Graphical abstract for Optimise. (Figure not reproduced here; see the original article.)

Relation to other parts of the programme: Implementing the Optimise checklist and algorithm appears feasible in UK clinical practice, with adjustments needed to minimise missing items. Not all patients accepted algorithm-indicated interventions, but a yield of 43% with symptoms having potentially reversible causes detected is clinically useful. Nurses endorsed the ease and utility of the implementation process, which now needs to be tested for clinical outcomes.

It was reassuring that very few participants had ‘red flags’, but those who did warranted clinical review which they had not currently sought. It is possible that people living with IBD need clearer guidance on which signs and symptoms warrant seeking clinical attention.

With 75% of participants with symptoms of fatigue, pain or urgency/FI being identified as having potentially active disease using a combination of IBD-Control score and FCP sample, our team felt that this was not a clinically credible number and reverted to using a FCP cut-off of ≥ 200 μg/g alone. IBD-Control score does not appear to be a useful discriminator of active disease in a group with these symptoms. This was also found in the RCT (below).

A user-friendly tool such as this could allow HCPs to readily monitor symptoms often difficult to control with existing IBD therapies. Health authorities and industry are increasingly prioritising patient-reported outcomes, such as pain, fatigue or FI, in clinical trials to determine treatment efficacy/success.

This study had also originally aimed to identify and prepare potential participants for the RCT (below). Participants who did not have potentially treatable pathophysiological contributors, or who had been ‘optimised’ (i.e. had their checklist reviewed and either no further tests or interventions were indicated, or these had been initiated where indicated) were invited to participate in the RCT. However, as stated above, because of adjustments necessitated by the COVID-19 pandemic, the originally envisaged flow of participants from the survey to the RCT via Optimise was no longer feasible, so very few RCT participants followed this route. With the reduced sample size for Optimise, it became apparent that we would never be able to deliver the RCT if we waited for sufficient patients to complete Optimise.

Limitations: It is possible that there was a self-selection bias in those patients who opted into the study. However, the very few presenting with red flags suggests that participants were not opting into the study because of urgent medical issues they wanted addressed. Likewise, the nurses interviewed were self-selected and may not be representative of IBD nurses generally.

As a feasibility study, with the reduction in sample size from 1000 to 200 as a result of the COVID-19 pandemic, this study was no longer powered to detect a difference in symptom scores or EQ-5D-5L utility scores and so null hypothesis significance testing was not performed. Thus, we do not assess nor infer whether algorithm-indicated actions had a clinically important effect.