Systematic review of current prognostication systems for pancreatic neuroendocrine neoplasms

Background: Pancreatic neuroendocrine neoplasms are a heterogenous group of rare tumors whose natural history remains poorly defined. Accurate prognostication of pancreatic neuroendocrine neoplasms is essential for guiding clinical decisions. This paper aims to summarize all the commonly utilized and recently proposed prognostication systems for pancreatic neuroendocrine neoplasms published in the literature to date. Methods: A systematic review of Pubmed, Scopus, and Embase databases, of the period from January 1, 2000-November 29, 2016, was conducted to identify all published articles reporting on prognostication systems of pancreatic neuroendocrine neoplasms. Results: A total of 23 articles were included in our review, and a total of 25 classification systems were identified. There were 2 modifications of the World Health Organization 2004 criteria, 4 modifications of the World Health Organization 2010 criteria, 2 modifications of the American Joint Committee on Cancer 2010 staging system, 3 modifications of the European Neuroendocrine Tumor Society 2006 tumor, node, metastasis staging system, 7 novel categorial classification systems, and 2 novel proposed continuous classifications. The most commonly included variables included age, size of tumor, presence of distant and lymph node metastases, Ki-67 index, and mitotic count. Conclusion: Numerous prognostication systems have been proposed for pancreatic neuroendocrine neoplasms, of which the most commonly used systems presently include the World Health Organization 2010 criteria and the two tumor, node, metastasis staging systems by the European Neuroendocrine Tumor Society and the American Joint Commission on Cancer. However, prognostication systems for pancreatic neuroendocrine neoplasms continue to evolve with time as more prognostication factors are identified. More validation and comparative studies are needed to identify the most effective prognostication system. (C) 2018 Elsevier Inc. All rights reserved.