Development and validation of a nomogram for predicting specific mortality risk: A study of competing risk model...

Area of Science:

• Oncology
• Biostatistics
• Cancer Epidemiology

Background:

• Endometrial cancer poses a significant mortality risk.
• Accurate prediction of specific mortality is crucial for patient management.
• Existing prognostic models may require updates based on comprehensive data analysis.

Purpose of the Study:

• To construct a competing risk prediction model for endometrial cancer.
• To identify demographic and tumor-related risk factors for specific mortality.
• To develop a nomogram for predicting survival outcomes in endometrial cancer patients.

Main Methods:

• Utilized data from the SEER database (2010-2015) for endometrial cancer patients.
• Employed univariate and multivariate competing risk models to identify prognostic factors.
• Constructed and validated a predictive nomogram using C-index and ROC curves.

Main Results:

• Identified Age, Marriage, Grade, FIGO stage, tumor size, surgery, and metastasis as independent prognostic factors.
• The constructed nomogram demonstrated strong discriminative ability with high C-index values (0.883) in both internal and external validation.
• Achieved favorable 1-, 3-, and 5-year AUC values, indicating good predictive accuracy.

Conclusions:

• A robust competing risk model for endometrial cancer mortality prediction was successfully developed.
• The model exhibits high accuracy and reliability, validated through rigorous statistical methods.
• This tool can serve as a valuable reference for refining endometrial cancer prognostic assessment.