A modified M-stage classification based on the metastatic patterns of pancreatic neuroendocrine neoplasms: a population-based study

作者:Zhang, Xianbin*; Song, Jiaxin; Liu, Peng; Mazid, Mohammad Abdul; Lu, Lili; Shang, Yuru; Wei, Yushan; Gong, Peng; Ma, Li*
来源:BMC Endocrine Disorders, 2018, 18(1): 73.
DOI:10.1186/s12902-018-0301-z

摘要

BackgroundThe present study aims to improve the M-stage classification of pancreatic neuroendocrine neoplasms (pNENs).MethodsTwo thousand six hundred sixty six pNENs were extracted from the Surveillance, Epidemiology, and End Results database to explore the metastatic patterns of pNENs. Metastatic patterns were categorized as single, two, or multiple (three or more) distant organ metastasis. The mean overall survival and hazard rate of different metastatic patterns were calculated by Kaplan-Meier and Cox proportional hazards models, respectively. The discriminatory capability of the modified M-stage classification was evaluated by Harrell's concordance index.ResultsThe overall survival time significantly decreased with an increasing number of metastatic organs. In addition, pNENs with only liver metastasis had better prognosis when compared to other metastatic patterns. Thus, we modified the M-stage classification (mM-stage) as follows: mM(0)-stage, tumor without metastasis; mM(1)-stage, tumor only metastasized to liver; mM(2)-stage, tumor metastasized to other single distant organ (lung, bone, or brain) or two distant organs; mM(3)-stage, tumor metastasized to three or more distant organs. Harrell's concordance index showed that the modified M-stage classification had superior discriminatory capability than both the American Joint Committee on Cancer (AJCC) and the European Neuroendocrine Tumor Society (ENETS) M-stage classifications.ConclusionsThe modified M-stage classification is superior to both AJCC and ENETS M-stage classifications in the prognosis of pNENs. In the future, individualized treatment and follow-up programs should be explored for patients with distinct metastatic patterns.