Background The possibility of lymph node metastasis (LNM) is critical to the assessment of the indication for endoscopic submucosal dissection. Thus, the aim of this study is to identify the risk factors for LNM and construct a risk-scoring model for patients with early gastric cancer to guide treatment. Methods A retrospective examination of reports and studies carried out January 2000 and December 2014 was conducted. A risk-scoring model for predicting LNM was developed based on the data thus collected. In addition, the model is subject to verification and validation by three institutions. Results Of the 1029 patients, 228 patients (22%) had LNM. Multivariate analysis showed that female, depressed type, undif- ferentiated type, submucosa, tumor size, and lymphovascular invasion were significantly associated with LNM. An 11-point risk- scoring model was used to predict LNM risk. An area under the receiver operating characteristic (AUROC) of the risk-scoring model was plotted using the development set and the AUROC of the model [0.76 (95% CI 0.73–0.80)] to predict LNM risk. After internal and external validation, the AUROC curve for predicting LNM was 0.77 (95% CI 0.68–0.86), 0.82 (95% CI 0.72–0.91), and 0.82 (95% CI 0.70–0.94), respectively. Conclusions A risk-scoring model for predicting LNM
Journal of Gastrointestinal Surgery – Springer Journals
Published: May 29, 2018
It’s your single place to instantly
discover and read the research
that matters to you.
Enjoy affordable access to
over 18 million articles from more than
15,000 peer-reviewed journals.
All for just $49/month
Query the DeepDyve database, plus search all of PubMed and Google Scholar seamlessly
Save any article or search result from DeepDyve, PubMed, and Google Scholar... all in one place.
Get unlimited, online access to over 18 million full-text articles from more than 15,000 scientific journals.
Read from thousands of the leading scholarly journals from SpringerNature, Wiley-Blackwell, Oxford University Press and more.
All the latest content is available, no embargo periods.
“Hi guys, I cannot tell you how much I love this resource. Incredible. I really believe you've hit the nail on the head with this site in regards to solving the research-purchase issue.”Daniel C.
“Whoa! It’s like Spotify but for academic articles.”@Phil_Robichaud
“I must say, @deepdyve is a fabulous solution to the independent researcher's problem of #access to #information.”@deepthiw
“My last article couldn't be possible without the platform @deepdyve that makes journal papers cheaper.”@JoseServera