Study A: PEACE methodological framework

Is it possible to develop a methodology that integrates/transfers the principle of Clinical Equipoise into a clinical trial recruitment process?

A new methodology was developed to determine levels of clinical equipoise for patients in a clinical trial, allowing identification of patients eligible for randomisation (Chapter 4). The Patient Eligibility Assessment through Clinical Equipoise (PEACE) framework can be implemented in real time during a trial. It uses modern technology to distribute clinical data for expert assessments on line and state-of-the-art statistical tools to pool and compare collective data. This approach allows one to integrate the core principles of clinical research, such as clinical equipoise and randomisation, in a clinical trial recruitment process.

The PEACE framework adds to the methodological portfolio of trial designs that are available to researchers undertaking challenging surgical trials, particularly those comparing contrasting procedures, where patient recruitment is expected to be difficult. Often the comparison is between higher risk operative interventions and safer, but arguably less effective, conservative measures. There are examples of trials when a traditional fixed eligibility criteria approach simply fails; up until now no methodological alternative has been available in these settings. Examples of such failures include the endoscopic anti-reflux procedures (EARPs) trial (Eckardt, Pinnow et al. 2009), where 134 patients were interviewed,

but only 13 (10%) were successfully recruited. In addition, there were virtually no patient referrals from 50 collaborating private practices and 23 hospitals. The authors blamed the scepticism of the referring physicians and strict selection criteria for this failure. The situation was even worse for MIMOSA, the mixed urinary incontinence (MUI) medical or surgical approach trial (Brubaker, Moalli et al. 2009), where 1198 subjects were screened and approached for study enrolment, but only 27 consented to randomisation. The Early Randomized Surgical Epilepsy Trial (ERSET) (Engel, McDermott et al. 2012) was also stopped prematurely due to much slower than expected patient accrual.

There are two main reasons why the PEACE framework has the potential to improve recruitment in such challenging surgical trials. First, it allows for simpler initial entrance criteria, so more patients would be considered for a trial than with conventional fixed entry criteria (Chapter 4.4). Secondly, every potential trial participant is assessed by an expert panel. This is in line with patient expectations from a clinical consultation; that is, to get the best possible advice on the appropriate treatment (Chapter 1.4). Expert panel assessment with the option of personal involvement in such an assessment will also likely encourage more sceptical clinicians to take part or refer patients.

As outlined in Chapter 1.4, the theoretical basis of the PEACE framework is a recognition that randomised clinical trials are ethical and necessary in

the presence of clinical equipoise. When clinical equipoise exists, it should be difficult to decide on the best treatment or procedure for a patient in most cases. It is accepted as good clinical practice to discuss such cases with several experts before a final decision is made. The PEACE framework aims to identify cases where experts agree about a better outcome for one or another treatment for a patient; in these cases it follows that randomisation becomes unethical and the patient cannot be recruited into the study. It is significant that for some cases recognised as eligible by the fixed eligibility criteria used in the UK HeFT, experts agreed that one or another treatment option was likely to produce a better outcome. It can be argued that these instances indicate that the framework would give patients reassurance that their cases are individually assessed in order to provide the best treatment choice. Conversely, when no consensus about likely treatment outcome has been demonstrated, a clinician would have more confidence that random treatment allocation would not disadvantage their patient even when they may have an individual preference. Similarly, patients offered randomisation would be reassured that opinion across a panel of experts was such that there was no agreement on the best

treatment in their particular case. The panel assessment results were easy to interpret and simple enough to be explained to both patients and clinicians (Chapter 4.3). Both groups were positive about introducing the new concept in future trials.

that it can be adjusted to the needs and specifics of a given trial. Most importantly, for consensus about an intervention choice to be considered, the following factors need to be discussed before implementation and decided by the trial team: a) the questions posed to experts (Chapter 4.3); b) the clinical information to be submitted; c) the decision rules for case eligibility or otherwise. Once agreed, the rules need to be accepted by all Principal Investigators and trial centres involved in a study prior to the commencement. I think that the work by Johnson et al. (1991), as used in this study (Chapter 4.2), is a good starting point. It is strongly advisable to test the chosen rules in a pilot study, using hypothetical cases and a putative panel of experts if necessary (Chapter 4.1).

The expert panel choice is crucial and needs to involve well known and respected specialists in a given area, although votes in all cases must be anonymous. Experts need to be clear how patient trial eligibility is decided and understand that a treatment choice in each case depends on them, in order to increase the level of expert involvement. Experience from the Collective Uncertainty Project (Chapter 4.3) suggests that at least four experts need to express their opinion in order to make a case valid for eligibility assessment; however it is clear that a higher number of experts make an analysis more powerful. From the UK HeFT experience, a panel of somewhere between 10 and 20 experts should provide a sustainable number of votes per case over what is often a considerable period of time required for trial recruitment. Expert votes need to be monitored

by the research team and may be questioned, for example concerning the use of overwhelmingly strong votes (e.g. 100% in favour of one or other treatment) or possible bias. It is important for a treating clinician to be able to express their opinion as part of the panel, so that they are directly involved in the clinical decision for their patient and able to compare their vote with the other panellists. PEACE is designed to be ‘time light’ for the expert clinicians involved; this is achieved, however, through extra work and effort required from the research team.

7.1.1 Concerns and areas for future research/development.

Although tested in the context of a real-life RCT, the PEACE framework was not actually used in the trial recruitment process. Rather, it provided valuable data to guide further developments, so that it can be used in future trials. The web based tool for expert opinion elicitation was constructed from several freely available software blocks (Chapter 3.1). This

demonstrated that it is feasible, even on a limited budget. It worked well, but had occasional glitches due to factors out of the control of the research team, such as software or system updates. It is imperative and a legal

necessity due to data protection issues that the software and patient data should be secure, stable and under the full control of the study research team. If the system developed for UK HeFT were to be used elsewhere, the clinical data input and assessment could be simplified, for example through

compatibility with hospital digital imaging systems, such as picture archiving and communication systems (PACS), and the development of dedicated applications compatible with portable digital devices, such as Tablet PCs.

Currently, statistical modelling is implemented in a high level statistical software package (R Developmental Core Team 2013), but for widespread use by clinicians and clinical trialists a more user friendly point-and-click Graphical User Interface (GUI) would be preferable. It would require a considerable amount of initial (one-off) additional work by programmers to develop such a system.