Related Experiment Video
Updated: Jun 4, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Improving Overall Risk Ranking via Subgroup-Level Information Borrowing in Survival Risk Stratification
Tia S Thomas1, Jing Ning2, Ruosha Li1
1UTHealth Houston School of Public Health, 1200 Pressler St., Houston, TX, USA.
None:
Effective risk stratification is essential for providing tailored therapies, improving patient outcomes, and optimizing healthcare resources by identifying sub-populations with similar health risks. However, accurate risk ranking is challenging in the presence of heterogeneous subgroups. Under these instances, subgroup-level information can be leveraged to refine the overall risk ranking. We propose a novel approach that integrates within-subgroup risk ranking percentiles to enhance the overall cohort risk stratification. This method uses both a global model and subgroup-specific models along with optimized weights to improve discriminatory performance across the entire cohort. The proposed method is validated through extensive simulations and applied to a study of end-stage renal disease patients awaiting kidney transplantation.
Related Concept Videos
Comparing the Survival Analysis of Two or More Groups
Types of Biopharmaceutical Studies: Controlled and Non-Controlled Approaches
Non-controlled studies, commonly employed for initial exploration, lack a control group, rendering them susceptible to biases and external influences. In contrast, controlled...
Cancer Survival Analysis
Relative Risk
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...
Assumptions of Survival Analysis

