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Background Time-to-event outcomes from randomized controlled trials (RCTs) are often communicated without clearly conveying how treatment effects evolve over time. This can limit clinicians’ ability to interpret results and support patient decision making. Methods We conducted an online experiment with 250 German general practitioners in April 2024. Participants evaluated treatment effects presented in 4 common formats: hazard ratios, prolongation of life, restricted mean survival time (RMST), and absolute risk reduction. We assessed 1) understanding, defined as the ability to correctly compare effect sizes (small, medium, large), and 2) acceptability of each format. We also tested whether providing baseline risk information (control group outcomes) improved performance. Results Participants’ effectiveness ratings did not differ between small, medium, and large treatment effects in any format. RMST presentations were judged less effective but more acceptable than the other formats. Providing baseline risk information did not influence effectiveness ratings or acceptance. Limitations The use of a convenience sample may limit generalizability. Conclusions General practitioners struggled to interpret time-to-event treatment effects across all formats. Although RMST was preferred, no format supported accurate understanding of effect size. Implications Current approaches may not adequately support communication of time-to-event outcomes in clinical practice. More effective strategies are needed, likely combining absolute time-based measures with clear contextual information such as baseline risk. Registration: OSF 10.17605/OSF.IO/U69YM Highlights Time-to-event outcomes from randomized trials are difficult for clinicians to interpret. General practitioners were unable to distinguish between small, medium, and large treatment effects across formats. Restricted mean survival time was preferred but did not improve understanding of time-to-event effects. Current formats do not support communication of time-to-event outcomes in clinical decision making.
Giese et al. (Tue,) studied this question.