RESUMO
Objective:To explore the association of platelet to lymphocyte ratio (PLR) and neutrophil to lymphocyte ratio (NLR) with early gastric cancer (EGC), and to assess the predictive value of PLR and NLR in EGC diagnosis.Methods:From January 1, 2017 to December 31, 2020, 178 patients with EGC, 129 patients with chronic gastritis (CG), 122 patients with gastric intraepithelial neoplasia (GIN) admitted and treated at Taizhou Hospital of Zhejiang Province were enrolled. According to Rand random function and with the ratio of 7 to 3, the patients were divided into training group ( n=301, 125 cases of EGC, 90 cases of CG, 86 cases of GIN) and validation group ( n=128, 53 cases of EGC, 39 cases of CG, 36 cases of GIN). The age, gender, routine blood test, carcinoembryonic antigen (CEA) level, Helicobacter pylori ( H. pylori) infection status and other data of the patients were collected. The routine blood test and clinical characteristics of EGC, CG and GIN patients of the training group, and the routine blood test of EGC patients and CG+ GIN patients (hereinafter referred to as non-EGC group) of training group were compared to analyzed the independent risk factors of EGC. Receiver operator characteristic curve (ROC) was drawn. The optimal cut-off value, area under the curve (AUC), OR, 95% confidence interval (95% CI) of independent risk factors were analyzed for EGC diagnosis and prediction. A diagnostic prediction model was established, and the model was apply to the validation group for validation. Hosmer-Lemeshow test was used to test the fitting degree of the model. Compared the AUC of the model applied to training group with validation group to evaluate the discrimination of model. Kruskal-Wallis H test, Mann-Whitney U test or Wilcoxon rank sum test, chi square test, and univariate and multivariate logistic regression analysis were used for statistical analysis. Results:In the training group, the proportions of males and females in CG, GIN and EGC patients were 50.0% (45/90) and 50.0% (45/90), 61.6% (53/86) and 38.4% (33/86), 69.6% (87/125) and 30.4% (38/125), respectively, and the difference was statistically significant ( χ2=8.49, P=0.014). The proportion of males in EGC patients was higher than that in CG patients, and the difference was statistically significant ( χ2 =8.48, P=0.004). The H. pylori infection rate, age, PLR, NLR, lymphocyte count, neutrophil count, and CEA level of CG, GIN and EGC patients in the training group were 18.9% (17/90), 18.6% (16/86) and 43.2% (54/125); 54.0 years old (45.5 years old, 64.0 years old), 63.0 years old (58.0 years old, 66.3 years old) and 66.0 years old (58.5 years old, 71.0 years old); 113.70 (84.48, 136.09), 120.00 (97.94, 138.37) and 124.29 (101.97, 173.57), 1.55 (1.17, 2.23), 1.71 (1.44, 2.02) and 2.04 (1.57, 2.62), 2.00×10 9/L (1.50×10 9/L, 2.40×10 9/L), 1.75×10 9/L (1.50×10 9/L, 2.40×10 9/L) and 1.60×10 9/L (1.30×10 9/L, 2.05×10 9/L), 3.00×10 9/L (2.38×10 9/L, 3.90×10 9/L), 3.00×10 9/L (2.48×10 9/L, 3.40×10 9/L) and 3.30×10 9/L (2.60×10 9/L, 4.30×10 9/L), 1.70 g/L (1.10 g/L, 2.50 g/L), 2.05 g/L (1.48 g/L, 2.90 g/L) and 2.50 g/L (1.55 g/L, 3.40 g/L), respectively, and the differences were statistically significant ( χ2=21.26, H=41.00, 11.79, 21.13, 10.82, 8.54 and 14.42; all P<0.05). The H. pylori infection rate of EGC patients was higher than that of CG and GIN patients, the ages of EGC and GIN patients were older than that of CG patients, the NLR and PLR levels of EGC patients were higher than those of CG patients, the NLR level of EGC patients was higher than that of GIN patients, the level of lymphocyte count of EGC patients was lower than that of CG patients, and the levels of neutrophil count and CEA were higher than those of CG patients, and the differences were statistically significant( χ2=13.98 and 13.90, Z=-6.13, -4.15, -4.07, -3.25, -3.40, -3.18, -2.62 and -3.74; all P<0.017). The levels of PLR, NLR, neutrophil count and CEA of EGC patients were all higher than those of non-EGC patients(124.29 (101.97, 173.57) vs. 117.97 (101.57, 137.32); 2.04(1.57, 2.62) vs.1.66(1.25, 2.17); 3.30×10 9/L (2.60×10 9/L, 4.30×10 9/L) vs.3.00×10 9/L(2.40×10 9/L, 3.60×10 9/L); 2.50 g/L (1.55 g/L, 3.40 g/L) vs. 1.90 g/L(1.23 g/L, 2.70 g/L)), and the lymphocyte count level was lower than that of non-EGC patients (1.60×10 9/L(1.30×10 9/L, 2.05×10 9/L) vs. 1.80×10 9/L(1.50×10 9/L, 2.20×10 9/L)), and the differences were statistically significant ( Z=-3.23, -4.45, -2.91, -3.30 and -2.35; all P<0.05). The results of ROC analysis showed that the optimal cut-off value of PLR, NLR, CEA, neutrophil count and lymphocyte count was 138.18, 1.76, 2.70 g/L, 3.40×10 9/L, 1.80×10 9/L, respectively. The results of univariate analysis indicated that the gender, age, H. pylori infection, neutrophil count, PLR, NLR, lymphocyte count and CEA were all related to EGC ( χ2=5.98, 27.73, 21.26, 8.26, 10.26, 22.80, 4.81 and 25.91; all P<0.05). The results of multivariate analysis demonstrated that age≥70 years old( OR=9.267, 95% CI 3.239 to 26.514), H. pylori infection ( OR=3.353, 95% CI 1.862 to 6.037), NLR >1.76 ( OR=2.084, 95% CI 1.190 to 3.648), PLR>138.18 ( OR=2.452, 95% CI 1.325 to 4.539), CEA >2.70 g/L ( OR=2.637, 95% CI 1.490 to 4.667) were independent risk factors for EGC (all P<0.05). The Hosmer-Lemeshow test showed that there was no statistically significant difference between the predicted value of the model and the actual observed value ( P>0.05), which indicated that the fitting degree of the model was good. In the training group, the AUC of the diagnostic prediction model was 0.787 (95% CI 0.737 to 0.832, P<0.001). The model was applied to the validation group for validation, and the result showed that the AUC of the model was 0.664 (95% CI 0.576 to 0.745, P<0.001), which indicated that the discrimination of the model was good. Conclusions:PLR and NLR are independent risk factors of EGC, and may help to identify EGC. In this study the established diagnostic model has good discrimination and fitting degree, which can provide important reference information for early clinical diagnosis of EGC, which may facilitate early treatment and improve prognosis of patients.
RESUMO
Objective To evaluate the effect of nutrition support on nutritional status and clinical outcome of patients at nutritional risk in internal medical departments.Methods 148 patients at nutritional risk as identified by Nutritional Risk Screening 2002 were numbered according to the order of admission and divided into standard care group (control group,odd numbers,n =75) and individualised nutrition support group (intervention group,even numbers,n =73).Intervention consisted of encouraging food intake,designing food plan,and assuring implementation of food prescription.Energy and protein intake,body weight,length of hospital stay,hospitalization expenses and complications were compared between the two groups.Results In the interventions group,protein intake was significantly higher than that in the control group [(45.1 ± 2.2) g/d vs.(54.8±2.5) g/d,P=0.004],and energyintake higher than that in the control group [(4 180.0± 227.4) kJ/d vs.(4 589.6 ± 150.5) kJ/d,P =0.135] but without statistical significance.Intervention led to an intake of ≥75％ of requirements in 46.6％ patients in the intervention group,significantly higher than the proportion in the control group (30.7％) (P =0.047).The change of body weight was significantly smaller in the intervention group than in the control group [(-0.4 ± 0.2) kg vs.(-1.1 ± 0.2) kg,P =0.025].The length of hospital stay,hospitalization expenses,and incidence of complications showed no significant differences between the control group and the intervention group [(13.5 ±0.9) d vs.(12.4 ±0.6) d,P=0.310;(17834±1824) yuanvs.(16099±1243) yuan,P=0.435;12.8％ vs.8.1％,P=0.184].Conclusions Patients at nutritional risk in internal medical departments could benefit from nutrition support in terms of protein intake and body weight maintenance.A large-scale randomized controlled trial is necessary to confirm the effect of nutrition support on clinical outcomes of patients at nutritional risk.