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Related Experiment Video

Updated: Sep 2, 2025

Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
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Dynamic Predictive Models With Visualized Machine Learning for Assessing Chondrosarcoma Overall Survival.

Wenle Li1,2, Gui Wang3, Rilige Wu4

  • 1Department of Orthopedics, Xianyang Central Hospital, Xianyang, China.

Frontiers in Oncology
|August 8, 2022
PubMed
Summary

A new chondrosarcoma prediction model was developed using SEER data and Chinese institutes. This validated nomogram accurately predicts outcomes and offers clinical utility for bone cancer patients.

Keywords:
chondrosarcomamulticenternomogramprediction modelweb calculator

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Area of Science:

  • Oncology
  • Medical Informatics
  • Biostatistics

Background:

  • Chondrosarcoma, a rare malignant bone tumor, necessitates accurate risk stratification for effective treatment.
  • Existing predictive models for chondrosarcoma exhibit limited reliability, highlighting the need for improved prognostic tools.

Purpose of the Study:

  • To develop and validate a credible clinical prediction model for chondrosarcoma risk assessment.
  • To integrate data from the Surveillance, Epidemiology, and End Results (SEER) program and Chinese medical institutions for robust model development.

Main Methods:

  • Utilized joint training of three algorithms: Best Subset Regression, Univariate and Cox regression, and Least Absolute Shrinkage and Selector Operator.
  • Constructed a nomogram predictor incorporating eight key variables: age, sex, grade, T, N, M, surgery, and chemotherapy.
  • Performed internal and external validation to assess model performance.

Main Results:

  • The developed nomogram predictor demonstrated strong performance in discrimination and calibration, with an Area Under the Curve (AUC) ≥0.8 in receiver operating characteristic analyses.
  • The predictor exhibited significant clinical utility, providing a positive net benefit for patients at 3- and 5-year intervals in both North American and Chinese cohorts.
  • A publicly accessible web calculator (https://drwenle029.shinyapps.io/CHSSapp) was created based on the prediction model.

Conclusions:

  • The novel nomogram serves as a reliable tool for chondrosarcoma risk evaluation.
  • The validated predictor enhances clinical decision-making and patient management for chondrosarcoma.
  • The free web calculator promotes accessibility and widespread clinical application of the prediction model.