Blood parameters score predicts long-term outcomes in stage Ⅱ-Ⅲ gastric cancer patients

摘要

BACKGROUND Increasing numbers of laboratory blood parameters(BPM)have been reported to greatly affect the long-term outcomes of gastric cancer(GC)patients.However,the existing prognostic models do not comprehensively analyze these predictors.AIM To construct a new prognostic tool,based on all the prognostic BPM,to achieve more accurate prognosis prediction for GC.METHODS We retrospectively assessed 850 consecutive patients who underwent curative resection for stage II-III GC from January 2010 to April 2013.The patients were classified into developing(n=567)and validation(n=283)cohorts using computer-generated random numbers.A scoring system,namely BPM score,was then constructed using least absolute shrinkage and selection operator(LASSO)Cox regression model in the developing cohort,and validated in the validation cohort.A nomogram consisting of BPM score and tumor-lymph node-metastasis(TNM)stage was further created.The discrimination and calibration of the nomogram were evaluated via Harrell’s C-statistic and the Hosmer-Lemeshow test.RESULTS Using the LASSO model,we established the BPM score based on five BPM:Albumin,lymphocyte-to-monocyte ratio,neutrophil-to-lymphocyte ratio,carcinoembryonic antigen,and carbohydrate antigen 19-9.The BPM scores were divided into high-and low-BPM groups based on a cut-off value of-0.93.High-BPM patients were significantly older and had more advanced,larger tumors.In the developing cohort,significant differences were found in 5-year overall survival(OS)and 5-year disease-specific survival between the high-BPM and low-BPM patients.Similar results were found in the validation group.Multivariable analysis showed that the BPM score was an independent predictor of OS.High-BPM patients had a poorer 5-year OS for each subgroup.Furthermore,a nomogram that combined the BPM score and TNM stage had significantly better prognostic value compared with TNM stage alone.CONCLUSION The BPM score provides more accurate prognosis prediction in stage Ⅱ-Ⅲ GC patients and is an effective complement to the TNM staging system.