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eISSN: 1643-3750

Prognostic Nomograms to Predict Survival of Patients with Resectable Gallbladder Cancer: A Surveillance, Epidemiology, and End Results (SEER)-Based Analysis

Yan Lin, Hua Chen, Fan Pan

Department of Gastroenterology, Fuzhou Second Hospital Affiliated to Xiamen University, Fuzhou, Fujian, China (mainland)

Med Sci Monit 2021; 27:e929106

DOI: 10.12659/MSM.929106

Available online: 2021-02-03

Published: 2021-03-30


#929106

BACKGROUND: Gallbladder adenocarcinoma (GBAC) is globally acknowledged as one of the most common malignancies among all gastrointestinal cancers. Despite prognosis of GBAC patients remains poor, patients with early-stage disease can be observed with long-term survival.
MATERIAL AND METHODS: In this study, 2556 patients with pathological GBAC between 2010 and 2015 were derived from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic nomograms containing all independent prognostic factors for predicting overall survival (OS) and cancer-specific survival (CSS) were constructed to achieve superior prognostic discriminatory ability.
RESULTS: Based on the AJCC 7th TNM staging system, we found the TNM substaging was not accurate enough to predict the survival and stratify the risk. Based on the results of univariate and multivariate analyses, a more precise prognostic nomogram was constructed containing all significant independent prognostic factors (age, grade, TNM stage, bone metastasis, and chemotherapy) for OS, while age, grade, TNM stage, bone metastasis and radiotherapy significant independent prognostic factors for CSS. The C-index of the constructed nomogram for predicting OS and CSS was 0.740 and 0.737 higher than that of TNM staging alone (0.667 for OS and 0.689 for CSS), respectively. In addition, the calibration curves and decision curve analysis further showed its robust power in survival prediction.
CONCLUSIONS: The constructed nomograms showed better discrimination abilities to predict OS and CSS rates at 1, 3, and 5 years. In the future, these constructed models for this disease will assist in risk stratification to guide GBAC treatment.

Keywords: Decision Support Techniques, Gallbladder Neoplasms, nomograms, SEER Program, Survival



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