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A prognostic nomogram in patients with distant metastasis of pancreatic neuroendocrine tumors: a population-based study

    Jin-Song Cai

    Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, PR China

    ‡Authors contributed equally; co-first authors

    Search for more papers by this author

    ,
    Hai-Yan Chen

    Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, PR China

    ‡Authors contributed equally; co-first authors

    Search for more papers by this author

    ,
    Yuan-Fei Lu

    Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, PR China

    &
    Ri-Sheng Yu

    *Author for correspondence: Tel.: +86 571 87783924; Fax: +86 571 87784556;

    E-mail Address: risheng-yu@zju.edu.cn

    Department of Radiology, Second Affiliated Hospital, Zhejiang University School of Medicine, Hangzhou, PR China

    Published Online:https://doi.org/10.2217/fon-2019-0545

    Aim: Prognostic factors in patients with distant metastatic pancreatic neuroendocrine tumors (PNETs) remain uncertain. The purpose of our study is to establish a nomogram to predict survival outcomes in patients with metastatic PNETs. Methods: A total of 878 patients diagnosed with PNETs in the Surveillance, Epidemiology and End Results database between 2004 and 2016 were retrospectively identified. The Kaplan–Meier survival analysis with log-rank test was used to analyze survival outcomes. The nomogram was established after a univariate and multivariate Cox analysis. Results: The independent prognostic variables, including age, tumor grade and primary site surgery were applied to develop a nomogram. The original concordance index was 0.773 (95% CI: 0.751–0.795), and the bias-corrected concordance index was 0.769 (95% CI: 0.748–0.791). The internal calibration curves showed well consistency and veracity in predicting cancer-specific survival probabilities. Conclusion: A nomogram was constructed and verified to predict survival outcomes in patients with distant-stage PNETs.

    Papers of special note have been highlighted as: • of interest; •• of considerable interest

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