A likely responder approach for the analysis of randomized controlled trials

OBJECTIVE

To further the precision medicine goal of tailoring medical treatment to individual patient characteristics by providing a method of analysis of the effect of test treatment, T, compared to a reference treatment, R, in participants in a RCT who are likely responders to T.

METHODS

Likely responders to T are individuals whose expected response at baseline exceeds a prespecified minimum. A prognostic score, the expected response predicted as a function of baseline covariates, is obtained at trial completion. It is a balancing score that can be used to match likely responders randomized to T with those randomized to R; the result is comparable treatment groups that have a common covariance distribution. Treatments are compared based on observed outcomes in this enriched sample. The approach is illustrated in a RCT comparing two treatments for opioid use disorder.

RESULTS

A standard statistical analysis of the opioid use disorder RCT found no treatment difference in the total sample. However, a subset of likely responders to T were identified and in this group, T was statistically superior to R.

CONCLUSION

The causal treatment effect of T relative to R among likely responders may be more important than the effect in the whole target population. The prognostic score function provides quantitative information to support patient specific treatment decisions regarding T furthering the goal of precision medicine.

Estimands: bringing clarity and focus to research questions in clinical trials

Precise specification of the research question and associated treatment effect of interest is essential in clinical research, yet recent work shows that they are often incompletely specified. The ICH E9 (R1) Addendum on Estimands and Sensitivity Analysis in Clinical Trials introduces a framework that supports researchers in precisely and transparently specifying the treatment effect they aim to estimate in their clinical trial. In this paper, we present practical examples to demonstrate to all researchers involved in clinical trials how estimands can help them to specify the research question, lead to a better understanding of the treatment effect to be estimated and hence increase the probability of success of the trial.

Demystifying the estimand framework: a case study using patient-reported outcomes in oncology

Patient-reported outcome (PRO) measures describe how a patient feels or functions and are increasingly being used in benefit-risk assessments in the development of cancer drugs. However, PRO research objectives are often ill-defined in clinical cancer trials, which can lead to misleading conclusions about patient experiences. The estimand framework is a structured approach to aligning a clinical trial objective with the study design, including endpoints and analysis. The estimand framework uses a multidisciplinary approach and can improve design, analysis, and interpretation of PRO results. On the basis of the International Council for Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use E9(R1) addendum, we provide an overview of the estimand framework intended for a multistakeholder audience. We apply the estimand framework to a hypothetical trial for breast cancer, using physical function to develop specific PRO research objectives. This Policy Review is not an endorsement of a specific study design or outcome; rather, it is meant to show the application of principles of the estimand framework to research study design and add to ongoing discussion. Use of the estimand framework to review medical products and label PROs in oncology can improve communication between stakeholders and ultimately provide a clearer interpretation of patient experience in the development of oncological drugs.

The potential of the estimands framework for clinical pharmacology trials: Some discussion points

The recently finalised and published guideline ICH E9 (R1) introduced a new framework for the statistical analysis of clinical trials, namely that of "estimands". While the framework was originally developed for the analysis of late-phase trials, it could also provide a rigorous basis for the analysis of clinical pharmacology trials. We illustrate potential applications on two examples: a multiple dose pharmacology trial and the interpretation of confirmatory bioequivalence (BE) trials according to the current FDA and EMA BE guidelines.

A constructive critique of the draft ICH E9 Addendum

In this article, I review the key elements of the proposed International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use E9 Addendum, present a constructive critique, and provide recommendations of how it can be improved. To highlight ideas, I present a case study involving a confirmatory trial for a chronic pain medication.