Related Experiment Video
Updated: Apr 3, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Development of a User-Friendly Graphic Tool to Estimate Individualized Survival Curves for Advanced Cancer Patients
Abstract:
This prospective study aimed to develop an individualized prognostic tool for predicting the survival probability at any given point for a hospice patient with advanced cancer. A total of 286 patients with advanced cancer were included in the study. Median observational time was 18 days (range: 1 to 60 days). Cox proportional hazards regression analysis revealed that faster heart rate (hazard ratio [HR] = 1.01), jaundice (HR = 2.32), poorer performance status (HR = 2.01), and antifungal treatment (HR = 1.62) were independent predictors of shorter survival time. Patients with infections who received aminoglycoside treatments (HR = 0.45) were associated with longer survival times. Based on this model, we could construct a covariate-adjusted individualized survival curve for a given patient according to his or her clinical condition. This user-friendly tool for estimating the survival probability of patients with advanced cancer in hospice settings could facilitate clinical decision making and medical care planning.
Related Concept Videos
Cancer Survival Analysis
Survival Curves
The Kaplan-Meier estimator is the most common method for constructing survival curves. This...
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Actuarial Approach
Consider the example of a high-risk surgical procedure with significant early-stage mortality. A two-year clinical study is conducted,...

