These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.


Pubmed for Handhelds

PUBMED FOR HANDHELDS

Search MEDLINE/PubMed

  • Title: An Examination of Lymph Node Sampling as a Predictor of Survival in Resected Node-Negative Small Bowel Adenocarcinoma: a SEER Database Analysis.
    Author: Thiessen M, Lee-Ying RM, Monzon JG, Tang PA.
    Journal: J Gastrointest Cancer; 2020 Mar; 51(1):280-288. PubMed ID: 31111426.
    Abstract:
    BACKGROUND: Small bowel adenocarcinoma (SBA) is a rare disease. Current recommendations are largely extrapolated from the colorectal literature. For node-negative (N -ve) cases, optimally stratifying cases into high or low risk, may help define optimal management. The objective of this analysis was to determine the importance of lymph node sampling for prognostication and to define what number of lymph nodes sampled is adequate. METHODS: Cases of non-metastatic SBA with complete staging, pathologic, and demographic information were selected from the SEER database and SAS 9.4 software was used. Variables included age, gender, race, grade, TNM staging, and number of lymph nodes were examined. Comparisons were made between N -ve and N +ve cases. Survival analysis using N -ve cases was performed to characterize the impact of nodal sampling on survival and to determine which nodal cut-offs best predict survival. RESULTS: A total of 523 cases from 2004 to 2014 were included in this analysis. Statistically significant differences identified included the median number of nodes sampled between the N -ve and N +ve groups, and the distribution of T stage and grade. Survival analysis in the N -ve cases demonstrated that the strongest predictor of survival was sampling of 16 or more lymph nodes. CONCLUSION: In this analysis, lymph node sampling was shown to be the most important pathologic predictor of survival in cases of N -ve SBA. Replicating these findings in a secondary dataset and determining whether a clinical benefit of adjuvant chemotherapy exists for SBA patients with inadequate sampling are both important next steps.
    [Abstract] [Full Text] [Related] [New Search]