The Value of ABO Blood Group and Complete Blood Count for the Prognosis Analysis of Gastric Cancer Patients

OBJECTIVE: To investigate the value of ABO blood group and complete blood count results in predicting the survival rate of patients with gastric cancer. PATIENTS AND METHODS: A retrospective study was conducted to collect 488 gastric cancer patients diagnosed in the Tumor Hospital Affiliated to Xinjiang Medical University from January 2010 to December 2011. Relevant clinical data were collected by the medical record system, and the patients were followed up by the medical record follow-up system of the hospital. The follow-up was ended until the death of the patients, and the survival time of all patients was obtained. Survival curve and Cox regression analysis model were used to study the role of various indicators in the prognosis of gastric cancer patients. RESULTS: Neutrophil lymphocyte ratio (NLR), neutrophil monocyte ratio (NMR), lymphocyte monocyte ratio (LMR) and platelet distribution width (PDW) in blood routine test could predict the death outcome of gastric cancer patients, with the predicted thresholds of 1.95, 13.49, 5.22 and 11.25, respectively. Survival curve analysis showed that female patients, type O blood patients, LMR >5.22 patients, NMR >13.49 patients and NLR ≤1.95 patients had longer survival. Multivariate Cox regression analysis model showed that gender and NLR were independent prognosis risk factors for gastric cancer, with HR values of 2.964 (95% CI of 2.258–3.891) and 1.103 (95% CI of 1.028–1.183), respectively. PLT and PDW were independent prognosis protective factors for gastric cancer, with HR values of 0.998 (95% CI of 0.997–1.000) and 0.891 (95% CI of 0.797–0.996), respectively. Compared with type O blood patients, patients with type A blood, type B blood and type AB blood had 3.472 times (95% CI 2.562–4.706), 3.368 times (95% CI 2.454–4.624) and 4.407 times (95% CI 2.871–6.766) increased risk of death. CONCLUSION: The results of NLR, PLT, PDW and ABO blood group can help to predict the survival of gastric cancer patients.