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

  • Lin, Yan1
  • Chen, Hua2
  • Pan, Fan3
  • 1 Department of Gastroenterology, Fuzhou Second Hospital Affiliated to Xiamen University, Fuzhou, Fujian, China (mainland). , (China)
  • 2 Department of General Surgery, Ningde Medical District, 900th Hospital of the Joint Logistics Team, People's Liberation Army (PLA), Ningde, Fujian, China (mainland). , (China)
  • 3 Department of Hepatobiliary Surgery, 900th Hospital of the Joint Logistics Team, People's Liberation Army (PLA), Fuzhou, Fujian, China (mainland). , (China)
Published Article
Medical Science Monitor
"International Scientific Information, Inc."
Publication Date
Mar 30, 2021
DOI: 10.12659/MSM.929106
PMID: 33784268


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.

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