Predicting the unpredictable: a robust nomogram for predicting recurrence in patients with ampullary carcinoma.

ABSTRACT:

Objective

To screen the risk factors affecting the recurrence risk of patients with ampullary carcinoma (AC)after radical resection, and then to construct a model for risk prediction based on Lasso-Cox regression and visualize it.

Methods

Clinical data were collected from 162 patients that received pancreaticoduodenectomy treatment in Hebei Provincial Cancer Hospital from January 2011 to January 2022. Lasso regression was used in the training group to screen the risk factors for recurrence. The Lasso-Cox regression and Random Survival Forest (RSF) models were compared using Delong test to determine the optimum model based on the risk factors. Finally, the selected model was validated using clinical data from the validation group.

Results

The patients were split into t

SUBMITTER: Chen R 

PROVIDER: S-EPMC10870520 | biostudies-literature | 2024 Feb

REPOSITORIES: biostudies-literature