Patient Reported Outcomes in Single-arm Trials: Recommendations for the Design and Analysis

Music City Center 

Single arm trials (SAT) play an increasingly important role in cancer research. In certain situations, it serves as alternatives to randomized control trials as well. However, the absence of a randomized control group can limit the interpretation and conclusions, particularly when assessing the effect of a specific treatment on patient reported outcomes (PRO), such as quality of life (QOL) data. Currently, PRO objectives in SATs are often unclear or not mentioned at all. Moreover, different approaches to handle intercurrent events may yield different results and conclusions, even in a descriptive setting Specifically, addressing death should be carefully considered in advance, because patient reported outcomes after death are not defined. To address this, single-arm trials require pre-specified PRO objectives that can be translated into key clinical questions using the the ICH-E9 (R1) estimand framework including pre-specified strategies to handle intercurrent events. The chosen strategy should be defined prior to analysis in line with the pre-defined PRO objective. For example, when describing PROs over time, the while-alive strategy is generally preferred. The population-level summary for this approach includes the PRO score of participants alive and descriptive statistics about death such as the proportion of patients still alive at the time point of assessment.

Making statements on treatments in single arm studies is challenging as changes over time in PROs cannot be solely attributed to the treatment. Various factors such as natural changes over time (e.g., due to disease worsening), response shift and the effects of concomitant therapies and comorbidities may also contribute to observed changes. Use of appropriate external data may address some of the concerns, but it also poses additional challenges including defining relevant estimands, accounting for confounding and different study drop out. Moreover, a key challenge for the QOL data analysis is handling of missing data which potentially introduce bias in the results depending on how cause of missingness related patient's medical condition. We'll discuss some of the recent works done by SISAQOL-IMI project to address these challenges.

The work presented here is part of the European IMI-SISAQOL project. SISAQOL-IMI is an international project, led by the European Organization for Research and Treatment of Cancer and Boehringer Ingelheim. The aim of this four-year project is to establish international standards in the analysis of patient reported outcomes (PRO) and health-related quality of life data in cancer clinical trials.