Related Experiment Video
Updated: Sep 28, 2025

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
[New, innovative prognosis calculator for patients with metastatic spinal tumors]
Tamás Mezei1,2, János Báskay3,4, Péter Pollner4,5
1Semmelweis Egyetem, Idegsebészeti Tanszék, Budapest.
Background And Purpose:
The aim of our research was to create a scoring system that predicts prognosis and recommends therapeutic options for patients with metastatic spine tumor. Increasing oncological treatment opportunities and prolonged survival have led to a growing need to address clinical symptoms caused by meta-stases of the primary tumor. Spinal metastases can cause a significant reduction in quality of life due to the caused neurological deficits. A scoring system that predicts prognosis with sufficient accuracy could help us to achieve personalised treatment options.
Methods:
Methods - We performed a retrospective clinical research of data from patients over 18 years of age who underwent surgery due to symptomatic spinal metastasis at the National Institute of Mental Disorders, Neurology and Neurosurgery between 2008 and 2018. Data from 454 patients were analysed. Survival analysis (Kaplan-Meier, log-rank, Cox model) was performed, network science-based correlation analysis was used to select the proper prognostic factors of our scoring system, such that its C value (predictive ability index) was maximized.
Results:
Multivariate Cox analysis resulted in the identification of 5 independent prognostic factors (primary tumour type, age, ambulatory status, internal organ metastases, serum protein level). Our system predicted with an average accuracy of 70.6% over the 10-year study period.
Conclusion:
Our large case series of surgical dataset of patients with symptomatic spinal metastasis was used to create a risk calculator system that can help in the choice of therapy. Our risk calculator is also available online at https://emk.semmelweis.hu/gerincmet.
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