Showing papers by "Suzie Cro published in 2023"

Estimands and their Estimators for Clinical Trials Impacted by the COVID-19 Pandemic: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions

Abstract: Abstract The COVID-19 pandemic continues to affect the conduct of clinical trials globally. Complications may arise from pandemic-related operational challenges such as site closures, travel limitations and interruptions to the supply chain for the investigational product, or from health-related challenges such as COVID-19 infections. Some of these complications lead to unforeseen intercurrent events in the sense that they affect either the interpretation or the existence of the measurements associated with the clinical question of interest. In this article, we demonstrate how the ICH E9(R1) Addendum on estimands and sensitivity analyses provides a rigorous basis to discuss potential pandemic-related trial disruptions and to embed these disruptions in the context of study objectives and design elements. We introduce several hypothetical estimand strategies and review various causal inference and missing data methods, as well as a statistical method that combines unbiased and possibly biased estimators for estimation. To illustrate, we describe the features of a stylized trial, and how it may have been impacted by the pandemic. This stylized trial will then be revisited by discussing the changes to the estimand and the estimator to account for pandemic disruptions. Finally, we outline considerations for designing future trials in the context of unforeseen disruptions.

Eliminating Ambiguous Treatment Effects Using Estimands

Abstract: Abstract Most reported treatment effects in medical research studies are ambiguously defined, which can lead to misinterpretation of study results. This is because most authors do not attempt to describe what the treatment effect represents, and instead require readers to deduce this based on the reported statistical methods. However, this approach is challenging, because many methods provide counterintuitive results. For example, some methods include data from all patients, yet the resulting treatment effect applies only to a subset of patients, whereas other methods will exclude certain patients while results will apply to everyone. Additionally, some analyses provide estimates pertaining to hypothetical settings in which patients never die or discontinue treatment. Herein we introduce estimands as a solution to the aforementioned problem. An estimand is a clear description of what the treatment effect represents, thus saving readers the necessity of trying to infer this from study methods and potentially getting it wrong. We provide examples of how estimands can remove ambiguity from reported treatment effects and describe their current use in practice. The crux of our argument is that readers should not have to infer what investigators are estimating; they should be told explicitly.

Barriers and facilitators to the recruitment of disabled people to clinical trials: a scoping review

Abstract: Underrepresentation of disabled groups in clinical trials results in an inadequate evidence base for their clinical care, which drives health inequalities. This study aims to review and map the potential barriers and facilitators to the recruitment of disabled people in clinical trials to identify knowledge gaps and areas for further extensive research. The review addresses the question: 'What are the barriers and facilitators to recruitment of disabled people to clinical trials?'.The Joanna Briggs Institute (JBI) Scoping review guidelines were followed to complete the current scoping review. MEDLINE and EMBASE databases were searched via Ovid. The literature search was guided by a combination of four key concepts from the research question: (1) disabled populations, (2) patient recruitment, (3) barriers and facilitators, and (4) clinical trials. Papers discussing barriers and facilitators of all types were included. Papers that did not have at least one disabled group as their population were excluded. Data on study characteristics and identified barriers and facilitators were extracted. Identified barriers and facilitators were then synthesised according to common themes.The review included 56 eligible papers. The evidence on barriers and facilitators was largely sourced from Short Communications from Researcher Perspectives (N = 22) and Primary Quantitative Research (N = 17). Carer perspectives were rarely represented in articles. The most common disability types for the population of interest in the literature were neurological and psychiatric disabilities. A total of five emergent themes were determined across the barriers and facilitators. These were as follows: risk vs benefit assessment, design and management of recruitment protocol, balancing internal and external validity considerations, consent and ethics, and systemic factors.Both barriers and facilitators were often highly specific to disability type and context. Assumptions should be minimised, and study design should prioritise principles of co-design and be informed by a data-driven assessment of needs for the study population. Person-centred approaches to consent that empower disabled people to exercise their right to choose should be adopted in inclusive practice. Implementing these recommendations stands to improve inclusive practices in clinical trial research, serving to produce a well-rounded and comprehensive evidence base.

Handling intercurrent events and missing data in non-inferiority trials using the estimand framework: A tuberculosis case study.

Abstract: INTRODUCTION The ICH E9 addendum outlining the estimand framework for clinical trials was published in 2019 but provides limited guidance around how to handle intercurrent events for non-inferiority studies. Once an estimand is defined, it is also unclear how to deal with missing values using principled analyses for non-inferiority studies. METHODS Using a tuberculosis clinical trial as a case study, we propose a primary estimand, and an additional estimand suitable for non-inferiority studies. For estimation, multiple imputation methods that align with the estimands for both primary and sensitivity analysis are proposed. We demonstrate estimation methods using the twofold fully conditional specification multiple imputation algorithm and then extend and use reference-based multiple imputation for a binary outcome to target the relevant estimands, proposing sensitivity analyses under each. We compare the results from using these multiple imputation methods with those from the original study. RESULTS Consistent with the ICH E9 addendum, estimands can be constructed for a non-inferiority trial which improves on the per-protocol/intention-to-treat-type analysis population previously advocated, involving respectively a hypothetical or treatment policy strategy to handle relevant intercurrent events. Results from using the 'twofold' multiple imputation approach to estimate the primary hypothetical estimand, and using reference-based methods for an additional treatment policy estimand, including sensitivity analyses to handle the missing data, were consistent with the original study's reported per-protocol and intention-to-treat analysis in failing to demonstrate non-inferiority. CONCLUSIONS Using carefully constructed estimands and appropriate primary and sensitivity estimators, using all the information available, results in a more principled and statistically rigorous approach to analysis. Doing so provides an accurate interpretation of the estimand.

Starting a conversation about estimands with public partners involved in clinical trials: a co-developed tool

Abstract: Clinical trials aim to draw conclusions about the effects of treatments, but a trial can address many different potential questions. For example, does the treatment work well for patients who take it as prescribed? Or does it work regardless of whether patients take it exactly as prescribed? Since different questions can lead to different conclusions on treatment benefit, it is important to clearly understand what treatment effect a trial aims to investigate-this is called the 'estimand'. Using estimands helps to ensure trials are designed and analysed to answer the questions of interest to different stakeholders, including patients and public. However, there is uncertainty about whether patients and public would like to be involved in defining estimands and how to do so. Public partners are patients and/or members of the public who are part of, or advise, the research team. We aimed to (i) co-develop a tool with public partners that helps explain what an estimand is and (ii) explore public partner's perspectives on the importance of discussing estimands during trial design.An online consultation meeting was held with 5 public partners of mixed age, gender and ethnicities, from various regions of the UK. Public partner opinions were collected and a practical tool describing estimands, drafted before the meeting by the research team, was developed. Afterwards, the tool was refined, and additional feedback sought via email.Public partners want to be involved in estimand discussions. They found an introductory tool, to be presented and described to them by a researcher, helpful for starting a discussion about estimands in a trial design context. They recommended storytelling, analogies and visual aids within the tool. Four topics related to public partners' involvement in defining estimands were identified: (i) the importance of addressing questions that are relevant to patients and public in trials, (ii) involving public partners early on, (iii) a need for education and communication for all stakeholders and (iv) public partners and researchers working together.We co-developed a tool for researchers and public partners to use to facilitate the involvement of public partners in estimand discussions.

Practical approaches to Bayesian sample size determination in non‐inferiority trials with binary outcomes

Abstract: Bayesian analysis of a non‐inferiority trial is advantageous in allowing direct probability statements to be made about the relative treatment difference rather than relying on an arbitrary and often poorly justified non‐inferiority margin. When the primary analysis will be Bayesian, a Bayesian approach to sample size determination will often be appropriate for consistency with the analysis. We demonstrate three Bayesian approaches to choosing sample size for non‐inferiority trials with binary outcomes and review their advantages and disadvantages. First, we present a predictive power approach for determining sample size using the probability that the trial will produce a convincing result in the final analysis. Next, we determine sample size by considering the expected posterior probability of non‐inferiority in the trial. Finally, we demonstrate a precision‐based approach. We apply these methods to a non‐inferiority trial in antiretroviral therapy for treatment of HIV‐infected children. A predictive power approach would be most accessible in practical settings, because it is analogous to the standard frequentist approach. Sample sizes are larger than with frequentist calculations unless an informative analysis prior is specified, because appropriate allowance is made for uncertainty in the assumed design parameters, ignored in frequentist calculations. An expected posterior probability approach will lead to a smaller sample size and is appropriate when the focus is on estimating posterior probability rather than on testing. A precision‐based approach would be useful when sample size is restricted by limits on recruitment or costs, but it would be difficult to decide on sample size using this approach alone.

Randomised controlled trial of adjunctive triamcinolone acetonide in eyes undergoing vitreoretinal surgery following open globe trauma: The ASCOT study

Abstract: Background/aims To investigate the clinical effectiveness of adjunctive triamcinolone acetonide (TA) given at the time of vitreoretinal surgery following open globe trauma (OGT). Methods A phase 3, multicentre, double-masked randomised controlled trial of patients undergoing vitrectomy following OGT comparing adjunctive TA (intravitreal and subtenons) against standard care (2014–2020). The primary outcome was the proportion of patients with at least 10 Early Treatment Diabetic Retinopathy Study (ETDRS) letter improvement in corrected visual acuity (VA) at 6 months. Secondary outcomes included: change in ETDRS, retinal detachment (RD) secondary to PVR, retinal reattachment, macular reattachment, tractional RD, number of operations, hypotony, elevated intraocular pressure and quality of life. Results 280 patients were randomised over 75 months, of which 259 completed the study. 46.9% (n=61/130) of patients in the treatment group had a 10-letter improvement in VA compared with 43.4% (n=56/129) of the control group (difference 3.5% (95% CI −8.6% to 15.6%), OR=1.03 (95% CI 0.61 to 1.75), p=0.908)). Secondary outcome measures also failed to show any treatment benefit. For two of the secondary outcome measures, stable complete retinal and macular reattachment, outcomes were worse in the treatment group compared with controls, respectively, 51.6% (n=65/126) vs 64.2% (n=79/123), OR=0.59 (95% CI 0.36 to 0.99), and 54.0% (n=68/126) vs 66.7% (n=82/123), OR=0.59 (95% CI 0.35 to 0.98), for TA vs control. Conclusion The use of combined intraocular and sub-Tenons capsule TA is not recommended as an adjunct to vitrectomy surgery following OGT. Trial registration number NCT02873026.