Long-Bin Xiao1, Jian-Xing Yu, Wen-Hui Wu, Feng-Feng Xu, Shi-Bin Yang. 1. Department of Gastrointestinal-pancreatic Surgery, the First Affiliated Hospital, Sun Yat-Sen University, Guangzhou 510080, Guangdong Province, China. longbinxiao@yahoo.cn
Abstract
AIM: To compare and evaluate the appropriate prognostic indicators of lymph node basic staging in gastric cancer patients who underwent radical resection. METHODS: A total of 1042 gastric cancer patients who underwent radical resection and D2 lymphadenectomy were staged using the 6th and 7th edition International Union Against Cancer (UICC) N staging methods and the metastatic lymph node ratio (MLNR) staging. Homogeneity, discriminatory ability, and gradient monotonicity of the various staging methods were compared using linear trend χ(2), likelihood ratio χ(2) statistics, and Akaike information criterion (AIC) calculations. The area under the curve (AUC) was calculated to compare the predictive ability of the aforementioned three staging methods. RESULTS: Optimal cut-points of the MLNR were calculated as MLNR0 (0), MLNR1 (0.01-0.30), MLNR2 (0.31-0.50), and MLNR3 (0.51-1.00). In univariate, multivariate, and stratified analyses, MLNR staging was superior to the 6th and 7th edition UICC N staging methods. MLNR staging had a higher AUC, higher linear trend and likelihood ratio χ(2) scores and lower AIC values than the other two staging methods. CONCLUSION: MLNR staging predicts survival after gastric cancer more precisely than the 6th and 7th edition UICC N classifications and should be considered as an alternative to current pathological N staging.
AIM: To compare and evaluate the appropriate prognostic indicators of lymph node basic staging in gastric cancerpatients who underwent radical resection. METHODS: A total of 1042 gastric cancerpatients who underwent radical resection and D2 lymphadenectomy were staged using the 6th and 7th edition International Union Against Cancer (UICC) N staging methods and the metastatic lymph node ratio (MLNR) staging. Homogeneity, discriminatory ability, and gradient monotonicity of the various staging methods were compared using linear trend χ(2), likelihood ratio χ(2) statistics, and Akaike information criterion (AIC) calculations. The area under the curve (AUC) was calculated to compare the predictive ability of the aforementioned three staging methods. RESULTS: Optimal cut-points of the MLNR were calculated as MLNR0 (0), MLNR1 (0.01-0.30), MLNR2 (0.31-0.50), and MLNR3 (0.51-1.00). In univariate, multivariate, and stratified analyses, MLNR staging was superior to the 6th and 7th edition UICC N staging methods. MLNR staging had a higher AUC, higher linear trend and likelihood ratio χ(2) scores and lower AIC values than the other two staging methods. CONCLUSION: MLNR staging predicts survival after gastric cancer more precisely than the 6th and 7th edition UICC N classifications and should be considered as an alternative to current pathological N staging.
Authors: Yuhree Kim; Malcolm H Squires; George A Poultsides; Ryan C Fields; Sharon M Weber; Konstantinos I Votanopoulos; David A Kooby; David J Worhunsky; Linda X Jin; William G Hawkins; Alexandra W Acher; Clifford S Cho; Neil Saunders; Edward A Levine; Carl R Schmidt; Shishir K Maithel; Timothy M Pawlik Journal: Surgery Date: 2017-05-31 Impact factor: 3.982
Authors: Moran Amit; Samantha Tam; Mongkol Boonsripitayanon; Maria E Cabanillas; Naifa L Busaidy; Elizabeth Gardner Grubbs; Stephen Y Lai; Neil D Gross; Erich M Sturgis; Mark E Zafereo Journal: JAMA Otolaryngol Head Neck Surg Date: 2018-02-01 Impact factor: 6.223
Authors: S G Patel; M Amit; T C Yen; C T Liao; P Chaturvedi; J P Agarwal; L P Kowalski; A Ebrahimi; J R Clark; C R Cernea; S J Brandao; M Kreppel; J Zöller; D Fliss; E Fridman; G Bachar; T Shpitzer; V A Bolzoni; P R Patel; S Jonnalagadda; K T Robbins; J P Shah; Z Gil Journal: Br J Cancer Date: 2013-09-24 Impact factor: 7.640