Analysis of Clinical Characteristics and Survival in Patients With Functional Neuroendocrine Tumors of Gastrointestinal Origin.

OBJECTIVES: Functional neuroendocrine tumors (FNETs) are characterized by excess secretion of disease-specific hormones. In this study, we attempted to define survival trends in patients with some of these uncommon tumors. METHODS: Using the Surveillance, Epidemiology, and End Results database, 529 patients with FNETs (gastrinoma, insulinoma, glucagonoma, VIPoma, and somatostatinoma) were identified. We analyzed patient and tumor characteristics, overall survival, and cancer-specific survival. RESULTS: Functional neuroendocrine tumors were found to be more predominant in White patients older than 50 years. Most common FNETs were gastrinoma (56.3%) and insulinoma (23.8%). Most FNETs were found in the pancreas, with the second most common location being the small bowel. Surgery was the primary modality of treatment, used in 55.8% of the cases. Median overall survival was 9.8 years (95% confidence interval [CI], 7.9-11.8) with a median cancer-specific survival of 18.5 years (95% CI, 12.8-24.2). In multivariate analysis, age >50 years (hazard ratio [HR], 2.7; 95% CI, 2.02-3.64), no surgical resection (HR, 1.88; 95% CI, 1.43-2.46), metastasis (HR, 3.0; 95% CI, 2.0-4.5), and poor differentiation were associated with poor survival. Site and histology did not have a significant impact on survival (P = 0.82 and 0.57 respectively). CONCLUSIONS: Our study highlights the most important prognostic factors for gastrointestinal FNETs.

>CME/CNE ARTICLE: Severity Grading in Multiple Sclerosis: A Proposal.

Currently used classification schemes for multiple sclerosis (MS) have not taken into account disease severity, instead focusing on disease phenotype (ie, relapsing vs. progressive). In this article, we argue that disease severity adds a crucial dimension to the clinical picture and may help guide treatment decisions. We outline a practical, easy-to-implement, and comprehensive scheme for severity grading in MS put forward by our mentor, Professor Joseph Herbert. We believe that severity grading may help to better prognosticate individual disease course, formulate and test rational treatment algorithms, and enhance research efforts in MS.