Related Experiment Video
Updated: Aug 17, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Predicting survival of patients with spinal metastatic disease using PathFx 3.0 - A validation study of 668 patients
Christian Carrwik1, Panagiotis Tsagkozis2, Rikard Wedin2
1Department of Surgical Sciences, Uppsala University, Uppsala, Sweden.
Introduction:
PathFx is a computer-based prediction model for estimating survival of patients with bone metastasis. The model has been validated in several studies, but this is the first validation using exclusively patients with spinal metastases.
Research Question:
Is PathFx 3.0 a tool useful for predicting survival for patients with spinal metastatic disease?
Material And Methods:
668 patients (67% male, median age 67 years) presenting with spinal metastases at two university hospitals in Sweden 1991-2014 were included. Of those, the majority (82%, n = 551) underwent surgery. Data on all patients was analyzed with PathFx version 3.0, generating a probability of survival at 1, 3, 6, 12, 18 and 24 months. The predictions were compared to real survival data and the precision in estimation was evaluated with Receiver-Operating Characteristic curve (ROC) analysis where the Area Under Curve (AUC) was calculated. Brier score and decision curve analyses were also assessed.
Results:
The AUC for 1-, 3-, 6- and 12 months survival predictions were 0.64 (95% CI 0.5-0.71), 0.71 (95% CI 0.67-0.75), 0.70 (95% CI 0.66-0.77) and 0.74 (95% CI 0.70-0.78). For 18- and 24 months survival the AUC were 0.74 (95% CI 0.69-0.78) and 0.76 (95% CI 0.72-0.81). The Brier scores were all 0.23 or lower depending on the estimated survival time.
Discussion And Conclusion:
PathFx 3.0 is a reasonably reliable tool for predicting survival in patients with spinal metastatic disease. As the PathFx computer model can be updated to reflect advancements in oncology, we suggest this type of model, rather than rigid point-based scoring systems, to be used for estimating survival in patients with metastatic spinal disease in the future.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
07:15Machine Learning Algorithms for Early Detection of Bone Metastases in an Experimental Rat Model
Published on: August 16, 2020
Related Concept Videos
Cancer Survival Analysis
Kaplan-Meier Approach
Comparing the Survival Analysis of Two or More Groups