After a first phase where five subteams have written several publications (see publications) the working group now operates within seven task forces. Objectives and member rosters of these task forces are available below.
Lead: Stefan Englert (J&J)
Objective: Develop basic introductory material that can be used by all study team members to educate themselves on Oncology Estimands. Translate key messages from the working group activities to a non-statistical audience, targeting especially clinical functions.
Lead: Yufei Wang (GSK)
Objective: This task force performs periodical literature reviews of principal stratum applied to treatment switching, focusing on the analysis of overall survival. It aims to evaluate and improve existing methods, develop new principal stratification models for treatment switching, e.g. through simulation studies to compare operating characteristics, relaxation/stress test of key assumptions, prior selection for Bayesian analysis, and software for implementation.
Communication of results is intended to happen through publication(s) for peer-reviewed journals, presentations/round-table discussions/trainings at various forums (JSM, DIA, FDA workshop, ISCB, …).
Lead: Rachael Lawrance (Adelphi)
Objective: Clarify what questions are we answering with typical analyses conducted on HRQoL endpoints in regulatory clinical trials. We are going to consider longitudinal mixed models and time to event analyses initially; “mapping” potential common questions into the estimand framework. The task force is also going to dig into the question of “how to handle death” in HRQoL analyses. We are keen to build collaborative approaches with statisticians and others active in this topic area, such as SISAQoL and ISOQoL working groups.
Lead: Hans-Jochen Weber (Novartis)
Objective: Duration of response and also time to response are standard secondary endpoints in clinical studies in oncology. There are different approaches for analysis and often the clinical question to be addressed remains unclear. We contextualize the different approaches using the estimand framework and illustrate those with case studies. Finally we intend to present recommendations for analyses targeting relevant clinical questions.
Lead: Evgeny Degtyarev (Novartis)
Objective: Illustrate the value and promote the use of target trial framework and estimand framework for design of comparisons including real-world data. The frameworks allows to clarify the definition of the causal question of interest ensuring alignment between the research objective and analysis. Its application in submission documents would facilitate regulatory review in a transparent and structured way.
Lead: Jiawei Wei (Novartis)
Objective: We would like to bring the complex concept and methods about conditional and marginal treatment effect into a simplified and interpretable way. Potential topics including adjusted or unadjusted analysis; stratified vs unstratified hazard ratio; collapsibility and subgroup; p-values; etc. We will give clinically relevant opinions and recommendations based on our interpretation, and illustrate the idea using some case studies.
Lead: Yi Liu (Nektar)
Objective: Our goal is to understand various efficacy estimands of biomarker subgroups and its relationship to the overall population for binary and time-to-event endpoints. For continuous outcomes with difference of means as efficacy estimand, Least Square estimates from the full model containing treatment, subgroup, and its interaction term enable an unbiased estimation of efficacy for the overall population by linearly combining estimands of the two subgroups. Following the same process for binary or time-to-event efficacy estimands such as hazard ratio or odds ratio, although guaranteeing logical inference in appearance, does not lead to the correct efficacy estimand of the overall population. In fact, the correct HR (or OR) may be outside of the interval of subgroup HRs (or ORs) leading to illogical interpretations. The task force will investigate which efficacy measures are logic respecting on the population level and make recommendations on how to analyze real clinical trial data so that analysis results based on these efficacy measures will always be logical for either prognostic or predictive biomarkers.
|Siyoen||Kil||LSK Global Pharma Services||Asia|
Lead: Francois Mercier (Roche)
Objective: In oncology Phase 1a (dose-escalation) and Phase 1b (expansion cohort) studies, the designs are complex because the objectives are often multiple and ambitious. Defining estimands and the associated estimators in this setting can be difficult. In this WG, we intend to implement the ICH-E9 addendum and to reflect on the challenges it presents in early clinical development studies. Such challenges may include: (1) absence of control group (2) varying dose, but also dosing schedule across treatment arms (a.k.a. cohorts) (3) presence of anti-drug antibody (ADA) (4) prophylactic treatment or co-medication for toxicity mitigation (e.g. using steroids) (5) compassionate within-patient dose escalation. The taskforce will give clinically relevant opinions and recommendations based on our analysis and interpretation of the selected case studies. Contact to other task forces will be sought based on need.
Lead: Jonathan Siegel (Bayer)
Objective: Key issues of interest for this task force are: (1) Estimands for safety-focused studies (2) Safety estimands within the context of a conventional efficacy study (3) Implementing estimands principles in general safety reporting and analysis (including what to change and what to leave in place) (4) Implementing estimands principles in associated CRF and data standards. The mission of the group is up for discussion and I would appreciate your interest.
The envisioned output for the group would be white papers, one focused on study design and statistical methodological considerations in safety estimands, and one focused on more nuts-and-bolts implementation issues including recommendations for general safety reporting, visit schedule and withdrawal criteria issues, monitoring, CRF considerations, data considerations and changes in data standards etc. In addition, the TF plans to involve itself in WG discussions with and recommendations to regulatory authorities, conference presentations, outreach webinars and workshops, etc.
Lead: Kaspar Rufibach (Roche)
Objective: This task force has submitted a paper entitled Quantification of Follow-up Time in Oncology Clinical Trials with a Time-to-Event Endpoint: Asking the Right Questions, find the link on the publications page. All questions initially asked have been discussed in this paper and the task force is therefore currently inactive.