Objectives: We aimed to evaluate the global scientific output of gene research of myocardial infarction and explore their hotspots and frontiers from 2001 to 2015, using bibliometric methods. Methods: Articles about the gene research of myocardial infarction between 2001 and 2015 were retrieved from the Web of Science Core Collection (WoSCC). We used the bibliometric method and Citespace V to analyze publication years, journals, countries, institutions, research areas, authors, research hotspots, and trends. We plotted the reference co-citation network, and we used key words to analyze the research hotspots and trends. Results: We identified 1,853 publications on gene research of myocardial research from 2001 to 2015, and the annual publication number increased with time. Circulation published the highest number of articles. United States ranked highest in the countries with most publications, and the leading institute was Harvard University. Relevant publications were mainly in the field of Cardiovascular system cardiology. Keywords and references analysis indicated that gene expression, microRNA and young women were the research hotspots, whereas stem cell, chemokine, inflammation and cardiac repair were the frontiers. Conclusions: We depicted gene research of myocardial infarction overall by bibliometric analysis. Mesenchymal stem cells Therapy, MSCs-derived microRNA and genetic modified MSCs are the latest research frontiers. Related studies may pioneer the future direction of this filed in next few years. Further studies are needed.

Pancreatic neuroendocrine tumor (pancreatic NETs), is an important cause of cancer‐related death worldwide. No study has rigorously explored the impact of ethnicity on pancreatic NETs. We aimed to demonstrate the relationship between ethnicity and the survival of patients with pancreatic NETs. We used the SEER database to identify patients with pancreatic NETs from 2004 to 2013. Kaplan–Meier methods and Cox proportional hazard models were used to evaluate the impact of race on survival in pancreatic NETs patients. A total of 3850 patients were included: 3357 Non‐Blacks, 493 Blacks. We stratified races as “Black” and “White/Other.” Blacks were more likely to be diagnosed with later stages of tumors (P = 0.021). As for the treatment, the access to surgery seemed to be more limited in Blacks than non‐Black patients (P = 0.012). Compared with non‐Black patients, Black patients have worse overall survival (OS) (HR = 1.17, 95% CI: 1.00–1.37, P = 0.046) and pancreatic neuroendocrine tumors specific survival (PNSS) (HR = 1.22, 95% CI: 1.01–1.48, P = 0.044). Multivariate Cox analysis identified that disease extension at the time of diagnosis and surgical status contributed to the ethnical survival disparity. Black patients whose stages at diagnosis were localized had significantly worse OS (HR = 2.09, 95% CI: 1.18–3.71, P = 0.011) and PNSS (HR = 3.79, 95% CI: 1.62–8.82, P = 0.002). As for the patients who did not receive surgery, Blacks also have a worse OS (HR = 1.18, 95% CI: 1.00–1.41, P = 0.045). The Black patients had both worse OS and PNSS compared to non‐Black patients. The restricted utilization of surgery, and the advanced disease extension at the time of diagnosis are the possible contributors to poorer survival of Blacks with pancreatic NETs.

Background: Prognosis prediction is indispensable in clinical practice and machine learning has been proved to be helpful. We expected to predict survival of pancreatic neuroendocrine tumors (PNETs) with machine learning, and compared it with the American Joint Committee on Cancer (AJCC) staging system.