Utilizing innovative two curves in nomogram
Tianhan Zhou, Zhongkai Ni, Hao Fan, Hai Huang, Haimin Jin · Frontiers in Medicine · 2025
Objective: Nomograms are valuable tools in clinical research for predicting patient outcomes. Understanding threshold values within these models is crucial for assessing the model's effectiveness and practical application in clinical environments. Methods: We developed two novel interpretive curves to enhance the utility of nomograms. These curves were designed to provide clear visualization of how clinical prediction models perform across various thresholds. The curves are applied to two case studies to demonstrate their practical application and efficacy. Results: In both examples, the novel curves successfully highlighted critical threshold values and revealed changes in prediction accuracy across these thresholds. This enhanced the understanding of the nomogram's performance, providing clinicians with more informative decision-making tools. Conclusions: The introduction of these interpretive curves allows for a more nuanced understanding of nomogram-based predictions, offering insights into threshold effects that can inform clinical decisions.