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A New Metastatic Lymph Node Classification-based Survival Predicting Model in Patients With Small Bowel Adenocarcinoma: A Derivation and Validation Study.

Abstract：

BACKGROUND:Current methods of lymph node (LN) staging are controversial in predicting the survival of SBA. We aimed to develop an alternative LN-classification-based nomogram to individualize SBA prognosis. METHODS:Based on the data from the Surveillance, Epidemiology, and End Results (SEER) database of patients diagnosed with SBA between 2004 and 2014, we identified the cut-off points for the number of LNs examined and the number found to be metastatic using the K-adaptive partitioning (KAPS) algorithm. Using metastatic LNs, a nomogram predicting the survival of SBA was derived, internally and externally validated, and measured by calibration curve, C-index, and decision curve analysis (DCA), and compared to the 8th TNM stage. RESULTS:A total of 1516 patients were included. The cut-off of 17 was the optimal examined LN number. For metastatic LN numbers, the cut-off points were 0, 2, and 8. The C-index for the nomogram was higher than the 8th TNM staging (internal: 0.734; 95% CI, 0.693 to 0.775 vs. 0.677; 95% CI, 0.652 to 0.702, P < 0.001; external: 0.715; 95% CI, 0.674 to 0.756 vs. 0.648; 95% CI, 0.602 to 0.693, P < 0.001). Also, the nomogram showed good calibration in internal and external validation and larger net benefit than TNM staging. CONCLUSION:We modified current N staging into a 4-level staging system based on the number of metastatic LNs: N0, no LN metastasis; N1, 1-2 metastatic LNs; N2, 3-8 metastatic LNs, and N3, >8 metastatic LNs and set the least examined LN number to 17. A nomogram based on this staging showed great clinical usability than TNM staging for predicting the survival of SBA patients.

journal_name

EBioMedicine

journal_title

EBioMedicine

authors

Wu S,Chen JN,Zhang QW,Tang CT,Zhang XT,Tang MY,Li XB,Ge ZZ

doi

10.1016/j.ebiom.2018.05.022

subject

Has Abstract

pub_date

2018-06-01 00:00:00

pages

134-141

issn

2352-3964

pii

S2352-3964(18)30186-5

journal_volume

32

pub_type

杂志文章

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