A Review of EMA Public Assessment Reports where Non-Proportional Hazards were Identified

• Published in: arXiv.org 2024-06
• Main Authors: Klinglmueller, Florian, Benda, Norbert, Friede, Tim, Fellinger, Tobias, Heinzl, Harald, Hooker, Andrew, Koenig, Franz, Mathes, Tim, Posch, Martin, Stampfer, Florian, Urach, Susanne
• Format: Article
• Language: English
• Subjects: Hazard assessment; Hazard identification; Marketing; Rank tests; Subgroups; Survival
• ISSN: 2331-8422

While well-established methods for time-to-event data are available when the proportional hazards assumption holds, there is no consensus on the best approach under non-proportional hazards. A wide range of parametric and non-parametric methods for testing and estimation in this scenario have been proposed. In this review we identified EMA marketing authorization procedures where non-proportional hazards were raised as a potential issue in the risk-benefit assessment and extract relevant information on trial design and results reported in the corresponding European Assessment Reports (EPARs) available in the database at paediatricdata.eu. We identified 16 Marketing authorization procedures, reporting results on a total of 18 trials. Most procedures covered the authorization of treatments from the oncology domain. For the majority of trials NPH issues were related to a suspected delayed treatment effect, or different treatment effects in known subgroups. Issues related to censoring, or treatment switching were also identified. For most of the trials the primary analysis was performed using conventional methods assuming proportional hazards, even if NPH was anticipated. Differential treatment effects were addressed using stratification and delayed treatment effect considered for sample size planning. Even though, not considered in the primary analysis, some procedures reported extensive sensitivity analyses and model diagnostics evaluating the proportional hazards assumption. For a few procedures methods addressing NPH (e.g.~weighted log-rank tests) were used in the primary analysis. We extracted estimates of the median survival, hazard ratios, and time of survival curve separation. In addition, we digitized the KM curves to reconstruct close to individual patient level data. Extracted outcomes served as the basis for a simulation study of methods for time to event analysis under NPH.