The predictive value of platelet to lymphocyte ratio and neutrophil to lymphocyte ratio in the diagnosis of early gastric cancer
10.3760/cma.j.cn311367-20210428-00250
- VernacularTitle:血小板与淋巴细胞比值和中性粒细胞与淋巴细胞比值对早期胃癌诊断的预测价值
- Author:
Lingling YAN
1
;
Jianfen WU
;
Binbin GU
;
Liping YE
Author Information
1. 浙江省台州医院消化内科，台州 317000
- Keywords:
Platelet to lymphocyte ratio;
Neutrophil to lymphocyte ratio;
Early gastric cancer;
Predictive model
- From:
Chinese Journal of Digestion
2022;42(3):163-170
- CountryChina
- Language:Chinese
-
Abstract:
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.
