BACKGROUND: Neoadjuvant chemotherapy (NAC) plays an important role in the therapeutic strategy of locally advanced gastric cancer (LAGC). However, the response of LAGC after NAC varies among different patients. The objective response after NAC has proven to be an excellent indicator for benefiting from NAC, yet effective predictors of objective response are still lacking. The present study aimed to identify potential predictors of objective response in LAGC patients treated with NAC. METHODS: Clinicopathological data from 267 patients with LAGC who received NAC and met the inclusion criteria between July 2009 and December 2018 were retrospectively reviewed. Patients were randomly divided into the training and test sets at a 2:1 ratio. Univariate analysis was used to investigate whether any factors were correlated with objective response in the training set. Multivariate logistic regression analysis was applied to find independent predictors. A risk score model was then constructed based on the independent predictors, and its performance in predicting objective response was validated in the test set. RESULTS: Univariate analysis found that gender, age, short axis diameter of the largest regional lymph node (LNmax), serum total protein content, CEA detection value, tumor location, tumor differentiation, signet ring cell carcinoma component and Borrmann type were potential predictors for objective response. In multivariate logistic regression analysis, gender, LNmax and signet ring cell carcinoma component were independent predictors for objective response. Based on independent predictors, we developed a prediction model for objective response. CONCLUSIONS: We found gender, LNmax and signet ring cell carcinoma component were independent predictors for objective response. The prediction model is a good tool to predict the objective response for LAGC patients treated with NAC, which can be applied to guide clinical practice. AJTR
BACKGROUND: Neoadjuvant chemotherapy (NAC) plays an important role in the therapeutic strategy of locally advanced gastric cancer (LAGC). However, the response of LAGC after NAC varies among different patients. The objective response after NAC has proven to be an excellent indicator for benefiting from NAC, yet effective predictors of objective response are still lacking. The present study aimed to identify potential predictors of objective response in LAGC patients treated with NAC. METHODS: Clinicopathological data from 267 patients with LAGC who received NAC and met the inclusion criteria between July 2009 and December 2018 were retrospectively reviewed. Patients were randomly divided into the training and test sets at a 2:1 ratio. Univariate analysis was used to investigate whether any factors were correlated with objective response in the training set. Multivariate logistic regression analysis was applied to find independent predictors. A risk score model was then constructed based on the independent predictors, and its performance in predicting objective response was validated in the test set. RESULTS: Univariate analysis found that gender, age, short axis diameter of the largest regional lymph node (LNmax), serum total protein content, CEA detection value, tumor location, tumor differentiation, signet ring cell carcinoma component and Borrmann type were potential predictors for objective response. In multivariate logistic regression analysis, gender, LNmax and signet ring cell carcinoma component were independent predictors for objective response. Based on independent predictors, we developed a prediction model for objective response. CONCLUSIONS: We found gender, LNmax and signet ring cell carcinoma component were independent predictors for objective response. The prediction model is a good tool to predict the objective response for LAGC patients treated with NAC, which can be applied to guide clinical practice. AJTR
Authors: L A Anderson; A Tavilla; H Brenner; S Luttmann; C Navarro; A T Gavin; B Holleczek; B T Johnston; M B Cook; F Bannon; M Sant Journal: Eur J Cancer Date: 2015-09-26 Impact factor: 9.162
Authors: David Cunningham; William H Allum; Sally P Stenning; Jeremy N Thompson; Cornelis J H Van de Velde; Marianne Nicolson; J Howard Scarffe; Fiona J Lofts; Stephen J Falk; Timothy J Iveson; David B Smith; Ruth E Langley; Monica Verma; Simon Weeden; Yu Jo Chua Journal: N Engl J Med Date: 2006-07-06 Impact factor: 91.245