Estimand framework: Are we asking the right questions? A case study in the solid tumor setting

Pharm Stat. 2021 Mar;20(2):324-334. doi: 10.1002/pst.2079. Epub 2020 Nov 5.

Abstract

The estimand framework requires a precise definition of the clinical question of interest (the estimand) as different ways of accounting for "intercurrent" events post randomization may result in different scientific questions. The initiation of subsequent therapy is common in oncology clinical trials and is considered an intercurrent event if the start of such therapy occurs prior to a recurrence or progression event. Three possible ways to account for this intercurrent event in the analysis are to censor at initiation, consider recurrence or progression events (including death) that occur before and after the initiation of subsequent therapy, or consider the start of subsequent therapy as an event in and of itself. The new estimand framework clarifies that these analyses address different questions ("does the drug delay recurrence if no patient had received subsequent therapy?" vs "does the drug delay recurrence with or without subsequent therapy?" vs "does the drug delay recurrence or start of subsequent therapy?"). The framework facilitates discussions during clinical trial planning and design to ensure alignment between the key question of interest, the analysis, and interpretation. This article is a result of a cross-industry collaboration to connect the International Council for Harmonisation E9 addendum concepts to applications. Data from previously reported randomized phase 3 studies in the renal cell carcinoma setting are used to consider common intercurrent events in solid tumor studies, and to illustrate different scientific questions and the consequences of the estimand choice for study design, data collection, analysis, and interpretation.

Keywords: EFSPI SIG estimands in oncology; ICH E9; estimand; intercurrent events; time-to-event data.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Data Interpretation, Statistical
  • Humans
  • Neoplasms* / drug therapy
  • Research Design*