Yao JC, Hassan M, Phan A, et al. One hundred years after “carcinoid”: epidemiology of and prognostic factors for neuroendocrine tumors in 35,825 cases in the United States. J Clin Oncol. 2008;26:3063–72.
Masui T, Ito T, Komoto I, et al. Recent epidemiology of patients with gastro-entero-pancreatic neuroendocrine neoplasms (GEP-NEN) in Japan: a population-based study. BMC Cancer. 2020;20:1104.
Article PubMed PubMed Central Google Scholar
Ito T, Igarashi H, Nakamura K, et al. Epidemiological trends of pancreatic and gastrointestinal neuroendocrine tumors in Japan: a nationwide survey analysis. J Gastroenterol. 2015;50:58–64.
Dasari A, Shen C, Halperin D, et al. Trends in the incidence, prevalence, and survival outcomes in patients with neuroendocrine tumors in the United States. JAMA Oncol. 2017;3:1335–42.
Article PubMed PubMed Central Google Scholar
Gill A, Klimstra D, Lam A, et al. WHO classification of tumours: Digestive system tumours. 5th ed. Lyon: International Agency for Research on Cancer; 2019.
Fujimori N, Miki M, Lee L, et al. Natural history and clinical outcomes of pancreatic neuroendocrine neoplasms based on the WHO 2017 classification; a single-center experience of 30 years. Pancreatology. 2020;20:709–15.
Ito T, Masui T, Komoto I, et al. JNETS clinical practice guidelines for gastroenteropancreatic neuroendocrine neoplasms: diagnosis, treatment, and follow-up: a synopsis. J Gastroenterol. 2021;56:1033–44.
Article CAS PubMed PubMed Central Google Scholar
Miki M, Oono T, Fujimori N, et al. CLEC3A, MMP7, and LCN2 as novel markers for predicting recurrence in resected G1 and G2 pancreatic neuroendocrine tumors. Cancer Med. 2019;8:3748–60.
Article CAS PubMed PubMed Central Google Scholar
Gao H, Liu L, Wang W, et al. Novel recurrence risk stratification of resected pancreatic neuroendocrine tumor. Cancer Lett. 2018;412:188–93.
Article CAS PubMed Google Scholar
Ye L, Ye H, Zhou Q, et al. A retrospective cohort study of pancreatic neuroendocrine tumors at single institution over 15 years: New proposal for low- and high-grade groups, validation of a nomogram for prognosis, and novel follow-up strategy for liver metastases. Int J Surg. 2016;29:108–17.
Landoni L, Marchegiani G, Pollini T, et al. The evolution of surgical strategies for pancreatic neuroendocrine tumors (Pan-NENs): time-trend and outcome analysis from 587 consecutive resections at a high-volume institution. Ann Surg. 2019;269:725–32.
Yamamoto Y, Okamura Y, Uemura S, et al. Vascularity and tumor size are significant predictors for recurrence after resection of a pancreatic neuroendocrine tumor. Ann Surg Oncol. 2017;24:2363–70.
Hashim YM, Trinkaus KM, Linehan DC, et al. Regional lymphadenectomy is indicated in the surgical treatment of pancreatic neuroendocrine tumors (PNETs). Ann Surg. 2014;259:197–203.
Li Y, Fan G, Yu F, et al. Meta-analysis of prognostic factors for recurrence of resected well-differentiated pancreatic neuroendocrine tumors. Neuroendocrinology. 2021;111:1231–7.
Article CAS PubMed Google Scholar
Tsutsumi K, Ohtsuka T, Fujino M, et al. Analysis of risk factors for recurrence after curative resection of well-differentiated pancreatic neuroendocrine tumors based on the new grading classification. J Hepatobiliary Pancreat Sci. 2014;21:418–25.
Kaneko H, Umakoshi H, Ogata M, et al. Machine learning based models for prediction of subtype diagnosis of primary aldosteronism using blood test. Sci Rep. 2021;11:9140.
Article CAS PubMed PubMed Central Google Scholar
Kaneko H, Umakoshi H, Ogata M, et al. Machine learning-based models for predicting clinical outcomes after surgery in unilateral primary aldosteronism. Sci Rep. 2022;12:5781.
Article CAS PubMed PubMed Central Google Scholar
Zhou RQ, Ji HC, Liu Q, et al. Leveraging machine learning techniques for predicting pancreatic neuroendocrine tumor grades using biochemical and tumor markers. World J Clin Cases. 2019;7:1611–22.
Article PubMed PubMed Central Google Scholar
Luo Y, Chen X, Chen J, et al. Preoperative prediction of pancreatic neuroendocrine neoplasms grading based on enhanced computed tomography imaging: validation of deep learning with a convolutional neural network. Neuroendocrinology. 2020;110:338–50.
Article CAS PubMed Google Scholar
Song Y, Gao S, Tan W, et al. Multiple machine learnings revealed similar predictive accuracy for prognosis of PNETs from the surveillance, epidemiology, and end result database. J Cancer. 2018;9:3971–8.
Article PubMed PubMed Central Google Scholar
Harris PA, Taylor R, Minor BL, et al. The REDCap consortium: building an international community of software platform partners. J Biomed Inform. 2019;95: 103208.
Article PubMed PubMed Central Google Scholar
Harris PA, Taylor R, Thielke R, et al. Research electronic data capture (REDCap)—a metadata-driven methodology and workflow process for providing translational research informatics support. J Biomed Inform. 2009;42:377–81.
Murakami M, Fujimori N, Matsumoto K, et al. A clinical analysis on functioning pancreatic neuroendocrine tumors (focusing on VIPomas): a single-center experience. Endocr J. 2022. https://doi.org/10.1507/endocrj.EJ22-0111.
van Buuren S, Groothuis-Oudshoorn K. Mice: multivariate imputation by chained equations in R. J Stat Softw. 2011;45:1–67.
Harrell FE Jr, Califf RM, Pryor DB, et al. Evaluating the yield of medical tests. JAMA. 1982;247:2543–6.
Kamarudin AN, Cox T, Kolamunnage-Dona R. Time-dependent ROC curve analysis in medical research: current methods and applications. BMC Med Res Methodol. 2017;17:53.
Article PubMed PubMed Central Google Scholar
Kronek LP, Reddy A. Logical analysis of survival data: Prognostic survival models by detecting high-degree interactions in right-censored data. Bioinformatics. 2008;24:i248–53.
Chen J, Yang Y, Liu Y, et al. Prognosis analysis of patients with pancreatic neuroendocrine tumors after surgical resection and the application of enucleation. World J Surg Oncol. 2021;19:11.
Article PubMed PubMed Central Google Scholar
Zheng-Pywell R, Fang A, AlKashash A, et al. Prognostic impact of tumor size on pancreatic neuroendocrine tumor recurrence may have racial variance. Pancreas. 2021;50:347–52.
Article PubMed PubMed Central Google Scholar
Zhang XF, Wu Z, Cloyd J, et al. Margin status and long-term prognosis of primary pancreatic neuroendocrine tumor after curative resection: results from the US neuroendocrine tumor study group. Surgery. 2019;165:548–56.
Kwon W, Jang JY, Song KB, et al. Risk factors for recurrence in pancreatic neuroendocrine tumor and size as a surrogate in determining the treatment strategy: a Korean nationwide study. Neuroendocrinology. 2021;111:794–804.
Article CAS PubMed Google Scholar
Dong DH, Zhang XF, Lopez-Aguiar AG, et al. Resection of pancreatic neuroendocrine tumors: defining patterns and time course of recurrence. HPB (Oxford). 2020;22:215–23.
Marchegiani G, Landoni L, Andrianello S, et al. Patterns of recurrence after resection for pancreatic neuroendocrine tumors: who, when, and where? Neuroendocrinology. 2019;108:161–71.
Article CAS PubMed Google Scholar
Jilesen AP, van Eijck CH, in’t Hof KH, et al. Postoperative complications, in-hospital mortality and 5-year survival after surgical resection for patients with a pancreatic neuroendocrine tumor: a systematic review. World J Surg. 2016;40:729–48.
Sadot E, Reidy-Lagunes DL, Tang LH, et al. Observation versus resection for small asymptomatic pancreatic neuroendocrine tumors: a matched case-control study. Ann Surg Oncol. 2016;23:1361–70.
Breiman L. Random forests. Mach Learn. 2001;45:5–32.
Ishwaran H, Kogalur UB, Blackstone EH, et al. Random survival forests. Ann Appl Stat. 2008. https://doi.org/10.1214/08-AOAS169.
Sakin A, Tambas M, Secmeler S, et al. Factors affecting survival in neuroendocrine tumors: a 15-year single center experience. Asian Pac J Cancer Prev. 2018;19:3597–603.
Article CAS PubMed PubMed Central Google Scholar
Lee L, Igarashi H, Fujimori N, et al. Long-term outcomes and prognostic factors in 78 Japanese patients with advanced pancreatic neuroendocrine neoplasms: a single-center retrospective study. Jpn J Clin Oncol. 2015;45:1131–8.
留言 (0)