AI Article Synopsis
- The study developed a predictive model to assess prognosis in patients with duodenal carcinoma using data from two sources, including a national database and a specific hospital.
- A nomogram was built using advanced statistical techniques like regression analyses to identify key factors affecting patient outcomes.
- The model showed a moderate prediction accuracy with C-index values around 0.67, allowing visualization of risk associated with each prognostic factor.
Article Abstract
This study aimed to develop a predictive model for patients with duodenal carcinoma. Duodenal carcinoma patients from the Surveillance, Epidemiology, and End Results database (2010-2015) and the First Affiliated Hospital of Nanchang University (2010-2021) were enrolled. A nomogram was constructed according to least absolute shrinkage and selection operator regression analysis, the Akaike information criterion approach and Cox regression analysis. Five independent prognostic factors were significantly associated with the prognosis of the duodenal carcinoma patients. A nomogram was constructed with a C-index in the training and validation cohorts of 0.671 (95% CI: 0.578-0.716) and 0.662 (95% CI: 0.529-0.773), respectively. The established nomogram model provided visualization of the risk of each prognostic factor.
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| http://dx.doi.org/10.2217/fon-2021-0622 | DOI Listing |
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