Principal stratum strategy: Potential role in drug development

Abstract

A randomized trial allows estimation of the causal effect of an intervention compared to a control in the overall population and in subpopulations defined by baseline characteristics. Often, however, clinical questions also arise regarding the treatment effect in subpopulations of patients, which would experience clinical or disease related events post‐randomization. Events that occur after treatment initiation and potentially affect the interpretation or the existence of the measurements are called intercurrent events in the ICH E9(R1) guideline. If the intercurrent event is a consequence of treatment, randomization alone is no longer sufficient to meaningfully estimate the treatment effect. Analyses comparing the subgroups of patients without the intercurrent events for intervention and control will not estimate a causal effect. This is well known, but post‐hoc analyses of this kind are commonly performed in drug development. An alternative approach is the principal stratum strategy, which classifies subjects according to their potential occurrence of an intercurrent event on both study arms. We illustrate with examples that questions formulated through principal strata occur naturally in drug development and argue that approaching these questions with the ICH E9(R1) estimand framework has the potential to lead to more transparent assumptions as well as more adequate analyses and conclusions. In addition, we provide an overview of assumptions required for estimation of effects in principal strata. Most of these assumptions are unverifiable and should hence be based on solid scientific understanding. Sensitivity analyses are needed to assess robustness of conclusions.

Translating questions to estimands in randomized clinical trials with intercurrent events

“…Siponimod was shown to delay the onset of disability progression compared to placebo, and it was also shown to reduce the frequency of relapses. These primary results raised the question "whether a treatment effect (on the onset of disability progression) would be present in patients that would not experience relapses" [1,4]. Here, experiencing relapses is an intercurrent event.…”

“…The ASA/EFSPI oncology estimand working group [1] further suggested that "biomarkers or early readouts can be useful to investigate whether an investigational medicine works as intended on a biological level". Thus, a motivation for studying biomarker responses in RCTs seems to be elucidation of causal mechanisms (on a biological level), which can indicate whether the drug acts as intended through particular causal pathways.…”

“…To illustrate the importance of carefully defining a causal estimand, we revisit five recent examples [1] inspired by the ICH addendum [2]. These examples concern settings where the intercurrent event is non-absorbing and non-interveneable.…”

“…We have structured our arguments as follows. In Section 2, we briefly introduce the intercurrent event settings in the five clinical examples from Bornkamp et al [1]. In Section 3, we describe estimands that have been suggested for causal inference in clinical settings with intercurrent events.…”

“…In Section 3, we describe estimands that have been suggested for causal inference in clinical settings with intercurrent events. 1 In Section 4, we revisit the five clinical examples and map the subject matter questions -as described in plain English by the investigatorsto causal estimands. In Section 5, we review conditions that allow us to identify these estimands in a RCT, followed by a brief description on how to estimate them in Section 6.…”