Title: Accessible statistical methods to determine treatments effects that matter to patients and prescribing physicians in randomised controlled trials
Funder: Department of Health and Social Care

Abstract: Research question Beyond nave per-protocol analyses: What accessible, practical, methods can be developed to obtain causal treatment effects that are relevant to patients in randomised controlled trials (RCTs) with intercurrent events? Background Accurate evaluation of treatments through RCTs is essential to provide robust, reliable evidence for effective treatments to use in the NHS and beyond. However, once we move beyond intention-to-treat, analysis of many trials is complicated by protocol deviations and related intercurrent events, such as non-adherence or rescue therapy use. Aims and objectivesThis research will develop accessible methodology for estimating causal treatment effects of relevance to patients in RCTs through the following objectives: Systematically review which causal treatment effects are estimated in RCTs and methods for their estimation. Develop novel, more accessible, statistical methods to calculate causal treatment effects of relevance to patients, including the effect of treatment if adhered to, or if rescue therapy was not available. Apply and evaluate the performance of the identified and developed methods. Create implementation guidance on methods.Methods and delivery timelines This research will consist of four interlocking work-packages conducted over three-years, structured as: Package-1: Literature review of published RCTs, months 1-6 Package-2: Develop controlled multiple imputation procedures to estimate treatment effects in the absence of intercurrent events in RCTs, including software, months 7-18 Package-3: Apply and compare methods using 4 chronic condition RCTs and by running simulations, months 19-30 RCTs I will re-examine are: Early introduction of allergenic foods against usual diet in infants on food-allergy development. Only 31.9% of the early introduction group adhered. Intention-to-treat and nave per-protocol analyses were contradictory. I will explore the treatment effect, if adhered to. A fixed-dose-combination (FDC) of agents versus usual-physician-care on heart risk factors. Intention-to-treat analysis identified significant reductions in risk factors for FDC, however agent adherence rates were 86%-FDC, 65%-usual care. I will investigate the treatment effect, if FDC adhered to versus usual-physician-care only. Home non-invasive ventilation plus oxygen (HOT-HMV) against oxygen alone on time-to-hospital admission/death after COPD exacerbation. A beneficial intention-to-treat effect of HOT-HMV was identified, however compliance and crossovers varied between treatment groups (91% versus 75%). I will consider the treatment effect if crossover is not experienced. A placebo-controlled trial of anti-IgE on eczema symptoms. Anti-IgE improved eczema symptoms in intention-to-treat analysis. But, this did not adjust for rescue therapies or adherence. I will investigate the treatment effect, if adhered to, and rescue therapy was not available.Package-4: Creation of accessible tutorials and implementation workshop, months 21-36Anticipated impact and disseminationBeyond answering outstanding clinically important questions in the above trials, this research will provide methodology and software to gain robust treatment effect estimates that are more relevant for patients in trials. This will enrich the information gained from trials, and aid better informed treatment choices by patients and treating physicians, thus improving patient health outcomes. An implementation workshop and tutorial papers will inform researchers of the most accessible and robust methodology. I will communicate trial results to the wider public to highlight the impact and importance of adherence.

Lay abstract: Background Poor treatment adherence is associated with suboptimal health outcomes and remains a major challenge across the field of medicine. This is particularly important in the treatment and management of chronic conditions, such as heart, respiratory, skin diseases and allergies. Improved information for patients on the health benefits of taking treatments as designed is required to help address this challenge. The best type of study to establish the benefit of a new treatment is a Randomised Controlled Trial (RCT). In RCTs a group of patients are enrolled and allocated to treatment groups at random. The patients are followed over time and their health outcomes are compared between the groups and any difference can be attributed to the treatment under study. However, if some individuals do not take the treatment as intended or experience other unplanned events, such as using rescue medication, this comparison will not indicate how well the trial treatment works if taken as designed. This can result in two problems; at trial level we may miss an effective treatment; in real world settings patients will not have information on how their adherence impacts effectiveness, which can be particularly important in chronic conditions. The calculation of treatment effects that are more relevant for patients, such as the treatment effect if adhered to, or if rescue medications were not used, has recently been brought to the forefront in new international drug trial guidelines. However, the guidance does not provide statistical methods for achieving this. Whilst some statistical methods have been proposed for calculating such patient centred effects, these are limited and not often used. Alternative, more accessible, methods are required to be developed and evaluated. Aims This research aims to develop accessible methodology to provide more meaningful information about the health benefits of treatments for patients and prescribing physicians. To achieve this, specific objectives are to: Systematically review the types of treatment effects calculated in RCTs that are of relevance to patients and the methods used to calculate these. Develop new, more accessible, statistical methods to estimate treatment effects of relevance to patients. Assess how the identified and developed methods perform and compare. Make methodology for estimating patient centred effects accessible through providing guidance for statisticians on implementation.Designs and methods I will: Conduct a systematic review of published RCTs. Develop methodology recently introduced to handle missing data to provide the effects of treatment, if taken as intended. Apply and evaluate the performance of the methods using data from 4 RCTs in chronic conditions, including heart, respiratory, skin diseases and allergies, and by running simulations. Develop accessible tutorials on methods.Patient and public involvement I have designed this research with input from the public (n=9, aged 20-60, mixed genders and ethnicities) at a 'peoples research caf' run by the NIHR Imperial Patient Experience Research Centre. Individuals were not surprised that patients do not always take treatments as intended in trials. But they were surprised that we do not usually take this into account when calculating how a new treatment performs. They felt this was important to do so. Patient representatives will be identified during the research and their opinion sought on the most useful information for patients. I will seek their opinion on how to disseminate results effectively. Dissemination Results will be disseminated at public events including Imperials Science Festival. I will disseminate methodological results to clinical researchers and statisticians at a planned implementation workshop, scientific conferences, local seminars and in statistical and clinical publications. During this research I will engage and work closely with academic colleagues nationally to inform the design and analysis of new and ongoing trials.

Research activity codes: 8.4 RESEARCH DESIGN AND METHODOLOGIES (HEALTH SERVICES)
Health categories: GENERIC HEALTH RELEVANCE