Development and validation of a nomogram for primary duodenal carcinoma: a multicenter, population-based study

Area of Science:

• Oncology
• Medical Statistics

Background:

• Duodenal carcinoma is a rare but serious malignancy.
• Accurate prognostic models are crucial for patient management and treatment planning.

Purpose of the Study:

• To develop and validate a predictive nomogram for duodenal carcinoma.
• To identify independent prognostic factors influencing patient survival.

Main Methods:

• Utilized data from the Surveillance, Epidemiology, and End Results (SEER) database and a hospital cohort.
• Employed least absolute shrinkage and selection operator (LASSO) regression, Akaike information criterion (AIC), and Cox regression analyses.
• Constructed a nomogram based on identified prognostic factors.

Main Results:

• Identified five independent prognostic factors significantly associated with duodenal carcinoma patient outcomes.
• The nomogram demonstrated good predictive accuracy with C-indices of 0.671 (training) and 0.662 (validation).

Conclusions:

• The developed nomogram provides a visualized tool for assessing individual patient risk in duodenal carcinoma.
• This model can assist clinicians in making informed prognostic predictions and treatment decisions.