已发表论文

淋巴结分期评分和淋巴结分期的充分性

 

Authors Chen H, Feng G

Received 6 September 2018

Accepted for publication 14 November 2018

Published 8 January 2019 Volume 2019:12 Pages 449—455

DOI https://doi.org/10.2147/OTT.S186642

Checked for plagiarism Yes

Review by Single-blind

Peer reviewers approved by Dr Andrew Yee

Peer reviewer comments 2

Editor who approved publication: Dr Leo Jen-Liang Su

Aims: The number of lymph nodes (LNs) excised in patients with pathologic N0 is limited, and it is very likely that there will be recessive node disease after surgery, so they are at risk of understaging. The purpose of the present study is to develop a nodal staging score (NSS) in a mathematical way to assess the likelihood that a pathologic N0 gastric cancer (GCa) patient has, indeed, no occult nodal disease after surgery.
Patients and methods: A total of 14,033 stage I–III GCa patients were identified from Surveillance, Epidemiology and End Results database for analysis. A beta-binomial model was fitted to calculate the probability of missing a nodal disease. This probability is then used to calculate the NSS.
Results: The probability of missing a nodal disease is decreased with increasing LNs examined across all pT stages. Seven and 24 LNs removed and examined was enough for an NSS of 90% in pT1 and pT2 patients, respectively, ensuring a high confidence of correct nodal negative classification. Twenty-three and 31 LNs examined in pT3 and pT4 patients could also maintain the NSS at 80%, respectively. NSS had a significant impact on patients’ survival across all pT stages (all s <0.0001).
Conclusion: The probability that GCa patients are free of true nodal disease could be provided by NSS-based prediction, which is conducive to postoperative decision and survival surveillance. In addition, NSS can define a subtle standard on how many LNs examined are enough for adequate staging dependent on pT stages. However, at least 16 LNs examined is the standard recommendation to date.
Keywords: gastric cancer, nodal-negative classification, adequate staging, prognosis




Figure 1 Using a beta-binomial model to calculate the probability of false-negative findings of...