Prognostic risk factors and nomogram construction for sebaceous carcinoma: A population-based analysis

Area of Science:

• Oncology
• Dermatology
• Biostatistics

Background:

• Sebaceous gland carcinoma (SGC) is a rare malignancy lacking effective prognostic tools.
• Accurate prediction of patient outcomes is crucial for effective management of SGC.

Purpose of the Study:

• To analyze clinical and pathological prognostic risk factors for SGC.
• To develop a nomogram for predicting overall survival (OS) rates in SGC patients.

Main Methods:

• Utilized data from 2844 SGC patients (2004-2015) from the SEER database.
• Employed univariate and multivariate COX regression to identify risk factors.
• Constructed and validated a nomogram using training and validation cohorts.

Main Results:

• The nomogram demonstrated good predictive power with a C-index of 0.725 in the training cohort and 0.710 in the validation cohort.
• AUC curves and calibration plots confirmed the nomogram's accuracy for 3-, 5-, and 10-year OS.
• Decision curve analysis indicated clinical utility for the developed nomogram.

Conclusions:

• A novel nomogram for SGC prognostic factors was successfully created.
• The nomogram provides accurate and comprehensive prediction of OS, aiding clinical decision-making.
• Early identification of high-risk SGC patients can facilitate personalized treatment and improve survival rates.