Clinicians'Interpretation and Preferences for Survival Data Visualisation: A Pre-Post Study Comparing Kaplan-Meier and Mean Residual Life Plots

Effective visualization of survival data is essential for clinician interpretation and patient communication. While Kaplan-Meier (KM) plots are widely used, Mean Residual Life (MRL) plots may offer a more intuitive display of prognosis over time. However, little is known about clinicians'knowledge and preferences regarding these alternatives. This pre-post pilot cross-sectional survey assessed 32 medical students and doctors who interpreted four survival plot types (KM, survival difference, MRL, and MRL difference) before and after a brief learning section. Interpretation accuracy, learning gain, and ranking preferences were analyzed. Overall accuracy improved from 50.0 percent pre-learning to 81.2 percent post-learning (p = 0.002), with the largest improvement for MRL plots (+37.5 percentage points). KM plots remained the most preferred for ease of clinical use (59 percent), while MRL plots were valued for patient communication (9 percent). Participants with lower self-rated survival knowledge showed the greatest learning gains. These findings suggest that with minimal instruction, clinicians can interpret MRL plots as effectively as KM plots. Incorporating MRL visualizations into clinical dashboards and medical education could improve understanding of survival outcomes and patient-centered communication.

• Publication year

  2025

• Venue

  Unknown venue

• Publication date

  2025-11-11

• Fields of study

  Medicine, Mathematics

• Identifiers
  arXiv 2511.08332
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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