A safety estimand for late phase clinical trials where the analysis period varies over the subjects.

BACKGROUND/AIMS: Evaluating safety is as important as evaluating efficacy in a clinical trial, yet the tradition for safety analysis is rudimentary. This article explores more complex methodologies for safety evaluation, with the aim of improving the interpretability, as well as generalizability, of the results. METHODS: For studies where the analysis periods vary over the subjects, using the International Council for Harmonisation estimand framework, we construct a formal estimand that could be used in the setting of safety surveillance that answers the clinical question of 'What is the magnitude of the increase in risk of experiencing an adverse event if the treatment is taken, as prescribed, for a specific period of time?'. Estimation methodologies for this estimand are also discussed. RESULTS: The proposed estimand is similar to that found in the efficacy analyses of time to event data (e.g. in outcome studies), with the key difference of utilization of hypothetical intercurrent event strategy for the intercurrent event of treatment discontinuation. This is motivated by what we perceive to be a key difference for the safety objective compared to efficacy objectives, namely a desire for sensitivity (i.e. greater possibility of detecting a negative impact of the drug, if such exists) as opposed to the need to prove a positive effect of the drug in a conservative manner. CONCLUSION: It is valuable, and possible, to use the International Council for Harmonisation estimand framework not only for efficacy but also for safety evaluation, with the estimand driven by an interpretable, and relevant, clinical question.

Current developments of the estimand concept.

Since the introduction of the estimand in therapeutical studies, several adaptions have been developed. This short article highlights the important aspects of the estimand concept. A literature research was conducted to identify different extensions to this framework. Different modified strategies for intercurrent events are presented, as well as examples of methods to implement the estimand in clinical studies. The article reflects that the estimand is an ongoing research field with further exploration.

Application of hypothetical strategies in acute pain.

Since the publication of ICH E9 (R1), "Addendum to statistical principles for clinical trials: on choosing appropriate estimands and defining sensitivity analyses in clinical trials," there has been a lot of debate about the hypothetical strategy for handling intercurrent events. Arguments against the hypothetical strategy are twofold: (1) the clinical question has limited clinical/regulatory interest; (2) the estimation may need strong statistical assumptions. In this article, we provide an example of a hypothetical strategy handling use of rescue medications in the acute pain setting. We argue that the treatment effect of a drug that is attributable to the treatment alone is the clinical question of interest and is important to regulators. The hypothetical strategy is important when developing non-opioid treatment as it estimates the treatment effect due to treatment during the pre-specified evaluation period whereas the treatment policy strategy does not. Two widely acceptable and non-controversial clinical inputs are required to construct a reasonable estimator. More importantly, this estimator does not rely on additional strong statistical assumptions and is considered reasonable for regulatory decision making. In this article, we point out examples where estimators for a hypothetical strategy can be constructed without any strong additional statistical assumptions besides acceptable clinical inputs. We also showcase a new way to obtain estimation based on disease specific clinical knowledge instead of strong statistical assumptions. In the example presented, we clearly demonstrate the advantages of the hypothetical strategy compared to alternative strategies including the treatment policy strategy and a composite variable strategy.

Estimands in CNS trials - A review of strategies for addressing intercurrent events.

Background: The estimands framework represents a significant innovation for the design, conduct, analysis, and interpretation of clinical trials. An aim of the framework is to increase precision and transparency on the handling of intercurrent events (IEs), defined as events occurring after treatment initiation and affecting the endpoint. While the experience in constructing and reporting estimands in the published literature is limited, developers performing confirmatory studies are already making use of the new paradigm, allowing to survey the strategies proposed by applicants and endorsed by regulators. Methods: To identify strategies for handling IEs in confirmatory central nervous system (CNS) trials, we searched scientific advice letters issued by the European Medicines Agency (EMA) between 2017 and 2022. We developed a categorisation of the IEs and classified, according to the strategies defined in the framework, the strategies proposed by the Applicants and recommended by the agency. Strategies proposed and recommended were summarised by category of IEs, and the rationale for the choices was analysed qualitatively. Results: In total, 170 IEs were identified in 52 confirmatory trials. A clear preference for the treatment policy strategy for treatment discontinuation and for the hypothetical strategy for pandemic-related disruptions was identified. For other categories of IEs, there are more mixed patterns. Discussion: This study highlights the multidimensional nature of choosing a strategy for an IE. For different occurring IEs in confirmatory CNS trials different strategies are of regulatory interest, depending on the trial objective, underlying disease properties, rarity of disease, as well as frequency and timing of IEs and their relatedness to the disease.

Estimand for non-inferiority influenza vaccine immunogenicity trials.

According to recent regulatory guidance, clinical trial objectives should be translated into estimands, i.e., precise descriptions of that what is to be estimated. Hence, estimands are to be formulated for influenza vaccine immunogenicity (IVI) trials, notably for one of the most popular immunogenicity trials, the non-inferiority trial. In this paper an estimand for this trial design is proposed. An estimand should state how intercurrent events are handled. Intercurrent events are events that occur after the start of the trial and that affect the endpoint's measurement or interpretation or prevent its observation. In IVI trials the intercurrent events of interest are immunological intercurrent events (IIEs). Major IIEs are identified, i.e., protocol deviations occurring during the trial that affect immunogenicity endpoints, and the consequences for the trial data collection are discussed. In the statistical analysis endpoint values that are missing or excluded from the analysis due to IIEs are to be substituted by plausible values, by means of multiple imputing. Replacing values are based on predictors of the endpoint. A distinction is made between mandatory and non-mandatory predictors. Mandatory predictors are predictors necessary to prevent biased prediction. Non-mandatory predictors are predictors that limit the additional variance due to the imputing. The four steps of the multiple imputing are explained, and available software is listed.