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Guidance on interim analysis methods in clinical trials.

ABSTRACT: Interim analyses in clinical trials can take on a multitude of forms. They are often used to guide Data and Safety Monitoring Board (DSMB) recommendations to study teams regarding recruitment targets for large, later-phase clinical trials. As collaborative biostatisticians working and teaching in multiple fields of research and across a broad array of trial phases, we note the large heterogeneity and confusion surrounding interim analyses in clinical trials. Thus, in this paper, we aim to provide a general overview and guidance on interim analyses for a nonstatistical audience. We explain each of the following types of interim analyses: efficacy, futility, safety, and sample size re-estimation, and we provide the reader with reasoning, examples, and implications for each. We emphasize that while the types of interim analyses employed may differ depending on the nature of the study, we would always recommend prespecification of the interim analytic plan to the extent possible with risk mitigation and trial integrity remaining a priority. Finally, we posit that interim analyses should be used as tools to help the DSMB make informed decisions in the context of the overarching study. They should generally not be deemed binding, and they should not be reviewed in isolation.

SUBMITTER: Ciolino JD

PROVIDER: S-EPMC10260346 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature

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Guidance on interim analysis methods in clinical trials.

Ciolino Jody D JD Kaizer Alexander M AM Bonner Lauren Balmert LB

Journal of clinical and translational science 20230515 1

Interim analyses in clinical trials can take on a multitude of forms. They are often used to guide Data and Safety Monitoring Board (DSMB) recommendations to study teams regarding recruitment targets for large, later-phase clinical trials. As collaborative biostatisticians working and teaching in multiple fields of research and across a broad array of trial phases, we note the large heterogeneity and confusion surrounding interim analyses in clinical trials. Thus, in this paper, we aim to provid ...[more]

PMID: 37313374

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Project description:BackgroundExisting guidelines recommend statisticians remain blinded to treatment allocation prior to the final analysis and that any interim analyses should be conducted by a separate team from the one undertaking the final analysis. However, there remains substantial variation in practice between UK Clinical Trials Units (CTUs) when it comes to blinding statisticians. Therefore, the aim of this study was to develop guidance to advise CTUs on a risk-proportionate approach to blinding statisticians within clinical trials.MethodsThis study employed a mixed methods approach involving three stages: (I) a quantitative study using a cohort of 200 studies (from a major UK funder published between 2016 and 2020) to assess the impact of blinding statisticians on the proportion of trials reporting a statistically significant finding for the primary outcome(s); (II) a qualitative study using focus groups to determine the perspectives of key stakeholders on the practice of blinding trial statisticians; and (III) combining the results of stages I and II, along with a stakeholder meeting, to develop guidance for UK CTUs.ResultsAfter screening abstracts, 179 trials were included for review. The results of the primary analysis showed no evidence that involvement of an unblinded trial statistician was associated with the likelihood of statistically significant findings being reported, odds ratio (OR) 1.02 (95% confidence interval (CI) 0.49 to 2.13). Six focus groups were conducted, with 37 participants. The triangulation between stages I and II resulted in developing 40 provisional statements. These were rated independently by the stakeholder group prior to the meeting. Ten statements reached agreement with no agreement on 30 statements. At the meeting, various factors were identified that could influence the decision of blinding the statistician, including timing, study design, types of intervention and practicalities. Guidance including 21 recommendations/considerations was developed alongside a Risk Assessment Tool to provide CTUs with a framework for assessing the risks associated with blinding/not blinding statisticians and for identifying appropriate mitigation strategies.ConclusionsThis is the first study to develop a guidance document to enhance the understanding of blinding statisticians and to provide a framework for the decision-making process. The key finding was that the decision to blind statisticians should be based on the benefits and risks associated with a particular trial.

Project description:BackgroundGroup sequential designs are one of the most widely used methodologies for adaptive design in randomized clinical trials. In settings where early outcomes are available, they offer large gains in efficiency compared to a fixed design. However, such designs are underused and used predominantly in therapeutic areas where there is expertise and experience in implementation. One barrier to their greater use is the requirement to undertake simulation studies at the planning stage that require considerable knowledge, coding experience and additional costs. Based on some modest assumptions about the likely patterns of recruitment and the covariance structure of the outcomes, some simple analytic expressions are presented that negate the need to undertake simulations.MethodsA model for longitudinal outcomes with an assumed approximate multivariate normal distribution and three contrasting simple recruitment models are described, based on fixed, increasing and decreasing rates. For assumed uniform and exponential correlation models, analytic expressions for the variance of the treatment effect and the effects of the early outcomes on reducing this variance at the primary outcome time-point are presented. Expressions for the minimum and maximum values show how the correlations and timing of the early outcomes affect design efficiency.ResultsSimulations showed how patterns of information accrual varied between correlation and recruitment models, and consequentially to some general guidance for planning a trial. Using a previously reported group sequential trial as an exemplar, it is shown how the analytic expressions given here could have been used as a quick and flexible planning tool, avoiding the need for extensive simulation studies based on individual participant data.ConclusionsThe analytic expressions described can be routinely used at the planning stage of a putative trial, based on some modest assumptions about the likely number of outcomes and when they might occur and the expected recruitment patterns. Numerical simulations showed that these models behaved sensibly and allowed a range of design options to be explored in a way that would have been difficult and time-consuming if the previously described method of simulating individual trial participant data had been used.

Project description:BackgroundWith recent growth in the conduct of pragmatic clinical trials, the reliance on frontline staff to contribute to trial-related activities has grown as well. Active partnerships with staff members are often critical to pragmatic trial implementation, but rarely do research teams track and evaluate the specific "implementation strategies" used to support staff's involvement in trial procedures (e.g., participant recruitment). Accordingly, we adapted implementation science methodologies and conducted an interim analysis of the strategies deployed with social service staff involved in one multi-site pragmatic clinical trial.MethodsWe used a naturalistic, observational study design to characterize strategies our research team deployed with staff during monthly, virtual meetings. Data were drawn from meeting notes and recordings from the trial's 4-month Preparation phase and 8-month Implementation phase. Strategies were mapped to the Expert Recommendations for Implementing Change taxonomy and categorized into nine implementation clusters. Survey data were also collected from staff to identify the most useful strategies the research team should deploy when onboarding new staff members in the trial's second year.ResultsA total of 287 strategies were deployed. Strategies in the develop stakeholder interrelationships cluster predominated in both the Preparation (35%) and Implementation (31%) phases, followed by strategies in the use iterative and evaluative approaches cluster, though these were more prevalent during trial Preparation (24%) as compared to trial Implementation (18%). When surveyed on strategy usefulness, strategies in the provide interactive assistance, use financial approaches, and support staff clusters were most useful, per staff responses.ConclusionsWhile strategies to develop stakeholder interrelationships were used most frequently during trial Preparation and Implementation, program staff perceived strategies that provided technical assistance, supported clinicians, and used financial approaches to be most useful and should be deployed when onboarding new staff members. Research teams are encouraged to adapt and apply implementation strategy tracking methods when partnering with social service staff and deploy practical strategies that support pragmatic trial success given staff needs and preferences.Trial registrationNCT05357261. May 2, 2022.

Project description:BackgroundIt is important to design clinical trials to include all those who may benefit from the intervention being tested. Several frameworks have been developed to help researchers think about the barriers to inclusion of particular under-served groups when designing a trial, but there is a lack of practical guidance on how to implement these frameworks. This paper describes the ACCESS project, the findings from each phase of the project and the guidance we developed (STEP UP) on how to design more inclusive trials.MethodsDevelopment of the STEP UP guidance had five phases: (1) Scoping literature review, (2) 'roundtable' discussion meetings, (3) redesign of trials, (4) interviews and (5) guidance document development, with input from public contributors and the ACCESS team.ResultsOver 40 experts contributed to the ACCESS project-patients and the public, clinicians, NHS research staff, trialists and other academics. The scoping review identified several strategies being used to improve inclusion, mostly around recruitment settings, but there was little evaluation of these strategies. The 'roundtable' discussions identified additional strategies being used across the UK and Ireland to improve inclusion, which were grouped into: Communication, Community engagement, Recruitment sites, Patient information, Flexibility, Recruitment settings, Consent process, Monitoring, Training for researchers and Incentives. These strategies were used to redesign three existing trials by applying one of the three INCLUDE frameworks (ethnicity, socioeconomic disadvantage, impaired capacity to consent) to one trial each, to produce the key recommendations for the guidance. Issues around implementation were explored in stakeholder interviews and key facilitators were identified: funders requesting information on inclusion, having the time and funding to implement strategies, dedicated staff, flexibility in trial protocols, and considering inclusion of under-served groups at the design stages. The STEP UP guidance is freely available at http://step-up-clinical-trials.co.uk .ConclusionResearchers should consider inclusivity to shape initial trial design decisions. Trial teams and funders need to ensure that trials are given both the resources and time needed to implement the STEP UP guidance and increase the opportunities to recruit a diverse population.

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Guidance on interim analysis methods in clinical trials.

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Guidance on interim analysis methods in clinical trials.

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