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中华妇幼临床医学杂志(电子版)

Chinese Journal of Obstetrics & Gynecology and Pediatrics(Electronic Edition) ›› 2020, Vol. 16 ›› Issue (05): 558 -566. doi: 10.3877/cma.j.issn.1673-5250.2020.05.009

Special Issue: ；

Original Article

Predictive values of neutrophil-to-lymphocyte ratio for neoadjuvant chemotherapy effects in patients with locally advanced cervical cancer

Xiaoxia Zheng1,†(), Dapeng Li2   

  1. 1. Department of Gynecology, Binzhou Central Hospital, Binzhou 251700, Shandong Province, China
    2. Shandong Institute of Cancer Prevention and Control, Jinan 250000, Shandong Province, China
  • Received:2020-04-10 Revised:2020-09-11 Published:2020-10-01
  • Corresponding author: Xiaoxia Zheng
  • Supported by:
    Key Research and Development Plan in Public Welfare Related Science and Technology of Shandong Province in 2018(2015-421)
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Objective

To explore predictive values of neutrophil-to-lymphocyte ratio (NLR) for neoadjuvant chemotherapy (NACT) effects in patients with locally advanced cervical cancer (LACC).

Methods

From January 2018 to June 2019, a total of 273 patients who received NACT in Binzhou Central Hospital and definitely diagnosed as LACC by pathological examination were selected as research subjects. After NACT, complete response (CR) and partial response (PR) were 74 and 147 cases respectively, while stable disease (SD) and disease progression (PD) were 48 and 9 cases respectively, and they were divided into effective group (n=221) and ineffective group (n=52), respectively. The age, clinical stage of International Federation of Gynecology and Obstetrics (FIGO), pathological grade, pathological type, serum squamous cell carcinoma antigen (SCCA), cancer antigen 125 (CA125), CA199, cytokeratin-19-fragment antigen (CY)21-1, carcino-embryonic antigen (CEA) and NLR were compared between two groups by independent-samples t test or chi-square test. Multivariate unconditional logistic regression analysis was used to analyze influencing factors of NACT effect and NLR in LACC patients. Receiver operating characteristic curve (ROC) was used to analyze the value of NLR in predicting NACT effect of LACC patients.There were no significant differences between two groups of ages and the largest diameter of tumors (P>0.05). This study was in line with World Medical Association Declaration of Helsinki revised in 2013.

Results

①The proportion of FIGO stage ⅠB2, pathological grade G1 and pathological type squamous-celled carcinoma in effective group were significantly higher than those in ineffective group, while serum SCCA, CA125, CA199, CY21-1, CEA and NLR were significantly lower than those in ineffective group, and all differences were significant (all P<0.05). Multivariate logistic regression analysis showed that serum SCCA, CA125, CA199, CY21-1, CEA levels, NLR and FIGO stage were all independent influencing factors to curative effects of NACT in LACC patients with LACC (OR=0.851, 0.931, 0.856, 0.614, 0.841, 0.521, 33.577; 95%CI: 0.767-0.945, 0.880-0.985, 0.780-0.938, 0.448-0.841, 0.749-0.944, 0.344-0.790, 5.509-204.660, P=0.002, 0.013, 0.001, 0.002, 0.003, 0.002, <0.001). ②ROC analysis showed that area under curve of ROC (ROC-AUC) of NLR in predicting curative effects of NACT in patients with LACC was 0.707 (95%CI: 0.649-0.760, P<0.001), and optimal critical value was 3.92%. ③NLR>3.92% of patients whose proportions of FIGO stage ⅡA, pathological grade of G2 and G3, and non-squamous cell carcinoma all were significantly higher than those NLR≤3.92% of patients, and differences were statistically significant (χ2=16.652, 19.721, 17.332, all P<0.001). Multivariate unconditional logistic regression analysis showed that FIGO stage, pathological grade and pathological type were all independent influencing factors of NLR in LACC patients (OR=4.908, 0.067, 12.293, 95%CI: 1.688-14.269, 0.005-0.871, 1.087-187.983, P=0.003, 0.039, 0.043).

Conclusions

NLR can effectively predict curative effects of NACT in patients with LACC, and its optimal critical value is 3.92%. NLR of patient with LACC is related to its clinical stage of FIGO, pathological grade and pathological type. Since this is just a single-center retrospective study with a relatively small sample size, NLR for clinical evaluation curative effects of NACT in patients with LACC still needs to further studied and confirmed by large-sample, multi-center, randomized controlled trials.

Key words: Uterine cervical neoplasms, Neutrophil to lymphocyte ratio, Locally advanced cervical cancer, Neoadjuvant chemotherapy, Neoplasm staging, Pathological conditions, signs and symptoms, Female
表1 LACC患者NACT疗效影响因素的单因素分析结果
组别 例数 年龄(岁，±s) FIGO临床分期[例数(%)] 病理分级[例数(%)] 病理类型[例数(%)]
ⅠB2期 ⅡA期 G1 G2 G3 鳞癌 非鳞癌
有效组 221 56.0±11.2 174(78.7) 47(21.3) 141(63.8) 61(27.6) 19(8.6) 210(95.0) 11(5.0)
无效组 52 58.0±10.7 23(44.2) 29(55.8) 20(38.5) 23(44.2) 9(17.3) 35(67.3) 17(32.7)
检验值   t＝1.147 χ2＝24.944 χ2＝8.202 χ2＝4.920
P值   0.252 <0.001 0.017 0.027
组别 例数 肿瘤最大直径(cm，±s) SCCA(ng/L，±s) CA125(U/mL，±s) CA199(U/mL，±s) CY21-1(ng/L，±s) (ng/L，±s) NLR(%，±s)
反应组 221 5.6±0.7 14.0±3.8 49.8±8.3 39.2±4.8 7.2±1.4 12.8±3.8 3.1±0.9
无反应组 52 5.7±0.9 16.9±4.3 55.0±9.0 42.4±5.0 8.1±1.5 15.4±4.0 3.9±1.2
检验值   t＝0.881 t＝4.835 t＝4.025 t＝4.277 t＝4.079 t＝4.462 t＝5.816
P值   0.379 <0.001 <0.001 <0.001 <0.001 <0.001 <0.001
表2 LACC患者NACT疗效影响因素的多因素非条件logistic回归分析变量含义及赋值情况
自变量/因变量 变量名 赋值
NACT疗效 y1 y1＝0表示无效，y1＝1表示有效
血清SCCA水平(ng/L) x1 连续变量
血清CA125水平(U/mL) x2 连续变量
血清CA199水平(U/mL) x3 连续变量
血清CY21-1水平(ng/L) x4 连续变量
血清CEA水平(ng/L) x5 连续变量
NLR(%) x6 连续变量
FIGO临床分期 x7 x7＝1表示ⅠB2期，x7＝2表示ⅡA期
病理分级 x8 x8＝1表示病理分级为G1，x8＝2表示病理分级为G2，x8＝3表示病理分级为G3
病理类型 x9 x9＝1表示鳞癌，x9＝2表示非鳞癌
肿瘤最大直径(cm) x10 连续变量
表3 LACC患者NACT疗效影响因素的多因素非条件logistic回归分析结果
影响因素 B SE Wald值 P值 OR值 OR值95%CI
血清SCCA水平 -0.161 0.053 9.212 0.002 0.851 0.767～0.945
血清CA125水平 -0.071 0.029 6.117 0.013 0.931 0.880～0.985
血清CA199水平 -0.156 0.047 11.040 0.001 0.856 0.780～0.938
血清CY21-1水平 -0.488 0.161 9.240 0.002 0.614 0.448～0.841
血清CEA水平 -0.173 0.059 8.607 0.003 0.841 0.749～0.944
NLR -0.652 0.212 9.458 0.002 0.521 0.344～0.790
FIGO临床分期为ⅠB2期 3.514 0.922 14.518 <0.001 33.577 5.509～204.660
病理分级为G1 -1.967 1.359 2.094 0.148 0.140 0.010～2.088
病理分级为G2 -0.989 1.091 0.822 0.365 0.372 0.044～3.155
病理类型为鳞癌 0.029 1.185 0.001 0.980 0.971 0.095～9.906
肿瘤最大直径 -0.058 0.214 0.074 0.785 0.943 0.621～1.434
图1 NLR预测LACC患者NACT疗效的ROC
表4 LACC患者NLR影响因素的单因素分析结果
不同NLR患者 例数 年龄(岁，±s) FIGO临床分期[例数(%)] 病理分级[例数(%)] 病理类型[例数(%)] 肿瘤最大直径(cm，±s)
ⅠB2期 ⅡA期 G1 G2 G3 鳞癌 非鳞癌
NLR>3.92% 68 58.3±10.2 31(45.6) 37(54.4) 25(36.8) 32(47.0) 11(16.2) 52(76.5) 16(23.5) 4.7±1.1
NLR≤3.92% 205 55.7±9.5 166(81.0) 39(19.0) 136(66.3) 52(25.4) 17(8.3) 193(94.1) 12(5.9) 4.4±1.0
检验值   t＝1.953 χ2＝16.652 χ2＝19.721 χ2＝17.332 t＝1.950
P值   0.052 <0.001 <0.001 <0.001 0.052
表5 LACC患者NLR影响因素的多因素非条件logistic回归分析变量含义及赋值情况
自变量/因变量 变量名 赋值
NLR y1 y1＝0表示NLR>3.92%，y1＝1表示NLR≤3.92%
FIGO临床分期 x1 x1＝1表示ⅠB2期，x1＝2表示ⅡA期
病理分级 x2 x2＝1表示病理分级为G1；x2＝2表示病理分级为G2；x2＝3表示病理分级为G3
病理类型 x3 x3＝1表示鳞癌，x3＝2表示非鳞癌
肿瘤最大直径(cm) x4 连续变量
表6 LACC患者NLR影响因素的多因素非条件logistic回归分析结果
影响因素 B SE Wald值 P值 OR值 OR值95%CI
FIGO临床分期为ⅠB2期 1.591 0.544 8.538 0.003 4.908 1.688～14.269
病理分级为G1 -2.476 1.402 3.120 0.077 0.084 0.005～1.312
病理分级为G2 -2.706 1.310 4.265 0.039 0.067 0.005～0.871
病理类型为鳞癌 2.660 1.315 4.093 0.043 12.293 1.087～187.983
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