Prognostic value of preoperative inflammatory indicators for hepatocellular carcinoma
10.3760/cma.j.cn115610-20210125-00041
- VernacularTitle:肝细胞癌术前炎症指标的预后价值
- Author:
Meilong WU
;
Shizhong YANG
;
Xiaobin FENG
;
Fei YU
;
Jiahong DONG
- From:
Chinese Journal of Digestive Surgery
2021;20(2):213-219
- CountryChina
- Language:Chinese
-
Abstract:
Objective:To investigate the prognostic value of preoperative inflammatory indicators for hepatocellular carcinoma (HCC).Methods:The retrospective cohort study was conducted. The clinicopathological data of 73 patients with primary HCC who underwent radical partial hepatectomy in the Beijing Tsinghua Changgung Hospital of Tsinghua University from December 2014 to July 2019 were collected. There were 57 males and 16 females, aged from 33 to 81 years, with a median age of 58 years. Results of blood examination indicators at the first time in hospital were determined for patients. Observation indicators: (1) the best cut-off values of?? preoperative inflammatory indicators calculated by the maximally selected rank statistics; (2) follow-up; (3) influencing factors for prognosis of HCC patients; (4) comparison of clinicopathological parameters of HCC patients; (5) comparison of predictive value for overall survival. Follow-up was conducted using outpatient examination and telephone interview to determine postoperative survival of patients up to September 2019. Measurement data with normal distribution were represented as Mean±SD, and comparison between groups was analyzed using the t test. Measurement data with skewed distribution were represented as M (range). The best cut-off values ??for continuous variables were obtained using the maximally selected rank statistics based on survival at endpoint of follow-up. Count data were represented as absolute numbers, and comparison between groups was analyzed using the chi-square test or Fisher exact probability. Kaplan-Meier method was used to calculate survival rates, and Log-rank test was used for survival analysis. Univariate analysis was performed using the Log-rank test. Multivariate analysis was performed using the COX proportional hazard model. The time-dependent receiver operating characteristic curve (ROC) was used to compare the predictive value of independent prognostic factors. Results:(1) The best cut-off values of?? preoperative inflammatory indicators calculated by the maximally selected rank statistics: the best cut-off values of neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and prognostic nutrition index (PNI) were 3.46, 131.05, and 45.65. (2) Follow-up: 73 patients were followed up for 31 months (range, 2-57 months). Twenty patients died during the follow-up. (3) Influencing factors for prognosis of HCC patients: results of univariate analysis showed that NLR, PNI, tumor diameter, and tumor differentiation degree were related factors affecting prognosis of patients ( χ2=10.213, 4.434, 5.174, 4.306, P<0.05). Results of multivariate analysis showed that NLR and tumor differentiation degree were independent factors affecting prognosis of patients ( hazzard ratio=4.429, 13.278, 95% confidence interval as 1.662-11.779, 1.056-10.169, P<0.05). (4) Comparison of clinicopathological parameters of HCC patients: of 73 patients, 64 cases had NLR<3.46 and 9 cases had NLR≥3.46. Cases with tumor length >5 cm or ≤5 cm, neutrophils, lymphocytes were 23, 41, (2.9±1.2)×10 9/L, (1.7±0.6)×10 9/L for 64 patients with NLR<3.46, versus 8, 1, (5.8±2.9)×10 9/L, (1.0±0.3)×10 9/L for 9 patients with NLR≥3.46; there were significant differences in above indicators between the two groups ( χ2=7.017, t=2.982, -3.168, P<0.05). (5) Comparison of predictive value for overall survival: time-dependent ROC curves of NLR and tumor differentiation degree for 1-, 2-, 3-, 4-year survival rates had the area under curve of 0.735,0.611, 0.596, 0.574 and 0.554, 0.583, 0.572, 0.556, respectively. NLR had better predictive value for overall survival of patients than tumor differentiation degree. Conclusion:Preoperative NLR is an independent factor affecting prognosis patients, and its predictive efficacy is better than tumor differentiation degree.
