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Updated: Jan 24, 2026
04:57
Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
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Development and Validation of a Prognostic Nomogram for Extremity Soft Tissue Leiomyosarcoma
MingFeng Xue1, Gang Chen1, JiaPing Dai1
1Department of Orthopaedics, The Second Hospital of Jiaxing, The Second Affiliated Hospital of Jiaxing University, Jiaxing, China.
Frontiers in Oncology
|May 24, 2019
Summary
This study developed a nomogram to predict survival for extremity soft tissue leiomyosarcoma (LMS) patients. The tool accurately forecasts overall survival (OS) and cancer-specific survival (CSS) using key prognostic factors.
Area of Science:
- Oncology
- Surgical Oncology
- Biostatistics
Background:
- Extremity soft tissue leiomyosarcoma (LMS) is a rare malignancy with a generally poor prognosis.
- Accurate prognostic tools are crucial for guiding treatment and patient counseling in LMS.
Purpose of the Study:
- To develop and validate nomograms for predicting overall survival (OS) and cancer-specific survival (CSS) in patients with extremity soft tissue LMS.
- To identify independent predictors of survival for extremity soft tissue LMS.
Main Methods:
- Utilized the Surveillance, Epidemiology, and End Results (SEER) database, including 1,528 extremity soft tissue LMS cases (1983-2015).
- Employed Cox proportional hazards regression to identify independent prognostic factors.
- Constructed nomograms based on identified predictors and validated performance using concordance index (C-index) and calibration plots.
Main Results:
- Multivariate analysis identified age ≥60, high tumor grade, distant metastasis, tumor size ≥5 cm, and lack of surgery as significant predictors of decreased OS and CSS.
- Nomograms demonstrated excellent agreement between predicted and observed 5- and 10-year OS and CSS.
- Achieved high C-index values for internal (OS: 0.776, CSS: 0.835) and external (OS: 0.748, CSS: 0.814) validation.
Conclusions:
- The developed nomogram serves as a reliable and robust tool for predicting prognosis in extremity soft tissue LMS.
- This tool can aid clinicians in providing more accurate prognostic assessments for patients with this rare sarcoma.
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