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Metastasis

Metastasis

Metastasis is the spread of cancer cells from the original site to distant locations in the body. Cancer cells can spread via blood vessels (hematogenous) as well as lymph vessels in the body.
Epithelial-to-Mesenchymal Transition
The epithelial-to-mesenchymal transition or EMT is a developmental process commonly observed in wound healing, embryogenesis, and cancer metastasis. EMT is induced by transforming growth factor-beta (TGF-β) or receptor tyrosine kinase (RTK) ligands, which further...

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Lung Metastasis Probability in Ewing Sarcoma: A Nomogram Based on the SEER Database.

Jie Wang¹, Yonggang Fan¹, Lei Xia¹

¹Department of Orthopaedic Surgery, The First Affiliated Hospital of Zhengzhou University, Zhengzhou 450052, China.

Current Oncology (Toronto, Ont.)

|March 11, 2021

Summary

This study developed a nomogram to predict lung metastasis in Ewing sarcoma (ES) patients. The tool uses factors like age and tumor size to improve early diagnosis and treatment planning for ES.

Keywords:

Ewing sarcoma SEER database lung metastasis nomogram

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Area of Science:

Oncology
Medical Statistics
Skeletal System Neoplasms

Background:

Accurate prediction of lung metastasis in Ewing sarcoma (ES) at initial diagnosis is currently lacking.
Lung metastasis is a critical factor influencing prognosis in ES patients.

Purpose of the Study:

To construct and validate a nomogram for predicting the probability of lung metastasis in ES patients.
To provide a clinical tool for improved risk stratification and management of ES.

Main Methods:

Retrospective analysis of 1157 ES patients from the SEER database.
Identification of metastasis predictors using LASSO and multivariate logistic regression.
Validation of the nomogram's discrimination and calibration using ROC curves, calibration curves, and DCA.

Main Results:

Key predictors identified include age, tumor size, primary site, tumor extension, and other site metastasis.
The nomogram demonstrated good predictive discrimination with AUC values of 0.732 (training) and 0.741 (validation).
Calibration curves and Hosmer-Lemeshow tests confirmed good model fit, and DCA indicated clinical usefulness between 1% and 90% metastasis probability.

Conclusions:

The developed nomogram is a convenient and effective tool for clinicians.
It can improve the prediction of lung metastasis probability in ES patients at initial diagnosis.
This tool aids in better clinical decision-making for Ewing sarcoma management.