Open Access

Evaluating and validating the predictive ability of preoperative systemic inflammatory/immune cells in gastric cancer following R0 resection

  • Authors:
    • Wenbo Xue
    • Xuezhong Xu
    • Yulin Tan
    • Yan Qian
    • Hao Wang
    • Yibo Wang
    • Yixin Xu
    • Xiaojun Zhu
    • Peng Jiang
    • Wei Ding
  • View Affiliations

  • Published online on: September 13, 2019     https://doi.org/10.3892/ol.2019.10867
  • Pages: 5205-5214
  • Copyright: © Xue et al. This is an open access article distributed under the terms of Creative Commons Attribution License.

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Abstract

The present study aimed to compare the predictive abilities of preoperative systemic inflammatory/immune cell ratios in gastric cancer (GC) following curative R0 resection, and to screen the optimal parameter incorporated into nomograms to predict the postoperative overall survival (OS) and recurrence‑free survival (RFS). A total of 679 patients with GC were included in the study, divided into a primary cohort (300 cases), an internal validation cohort (278 cases), and an external validation cohort (101 cases). In the primary cohort, the prognostic abilities of all systemic inflammatory/immune cell accounts or ratios were compared by receiver operating characteristic (ROC) curve analysis. The area under the ROC curve (AUC) of the neutrophil‑monocyte‑lymphocyte ratio (NMLR) was largest for the prediction of OS (AUC=0.728) and RFS (AUC=0.695). The independent predictive factors for OS or RFS, including NMLR, degree of differentiation (DD), T‑stage and N‑stage were used to establish the 2 nomograms. The comprehensive predictive power of nomograms was compared with that of the tumor‑nodes‑metastasis (TNM) staging system and validated by bootstrap resampling. The concordance indexes (C‑indexes) of the nomograms for OS [C‑index, 0.851; 95% confidence interval (CI), 0.817‑0.883] and RFS (C‑index, 0.860; 95% CI, 0.831‑0.889), were increased compared with those for the DD, the NMLR and the TNM stage. The AUCs of the 2 nomograms (0.933 for OS and 0.944 for RFS) were largest among all predictive scoring systems. In the internal validation cohort, the C‑indexes of the nomograms for OS and RFS were 0.840 and 0.916, respectively. In the external validation cohort, the C‑indexes of the nomograms for OS and RFS nomograms were 0.827 and 0.891, respectively. The present study demonstrated that the NMLR was an independent prognostic factor for patients with GC. The proposed nomograms were demonstrated to have a good predictive ability with improved sensitivity and accuracy in survival and recurrence in patients with GC undergoing R0 resection.

Introduction

Gastric cancer (GC) is one of the most common malignant tumor types according to previous statistics (1). The morbidity of GC ranks fourth and the associated mortality ranks second worldwide. Eastern Asia has the highest incidence of GC in the world. Despite comprehensive post-operative anti-tumor therapy resulting in prolonged survival following GC resection, long-term survival following surgery remains poor (2). Precise predictive tools are critical for individualizing treatment protocols. At present, the tumor-nodes-metastasis (TNM) stage is the most frequently used prognostic factor. However, clinical experience has indicated that even within the same TNM stage, the survival of patients may differ (3). Therefore, the development of novel evaluation systems that may include more prognostic factors is urgently required.

The predictive roles of the preoperative systemic inflammatory/immune cells in GC have been highlighted by previous studies, including the neutrophil-to-lymphocyte ratio (NLR), the monocyte-to-lymphocyte ratio (MLR) and the platelet-to-lymphocyte ratio (PLR) (46). Recently, the neutrophil-monocyte-lymphocyte ratio (NMLR) has been suggested to have an improved predictive ability compared with other inflammatory/immune cell counts or ratios in patients with hepatocellular carcinoma after curative hepatectomy (7). The most suitable parameter of the inflammatory/immune system for predicting the outcome for patients with GC remains to be determined.

To improve and refine the predictive models of traditional staging systems for GC, several novel nomograms have been reported (8,9). These included prognostic nomograms for GC following gastrectomy incorporating systemic inflammatory/immune parameters. The present study performed a screening to identify the optimum systemic inflammatory/immune parameter and to develop reliable nomograms, in order to provide accurate estimations of the prognosis of patients with GC undergoing R0 resection.

Patients and methods

Ethics statement

The present retrospective cohort study was approved by the Ethics Review Committee of Wujin Hospital affiliated to Jiangsu University and was performed in accordance with the ethical guidelines of the Declaration of Helsinki from 1975. Due to the retrospective nature of this study, the need for written informed consent was waived.

Study population

Data were collected from Wujin Hospital and the Southern Branch of Wujin Hospital Affiliated to Jiangsu University. A total of 1,023 consecutive patients with GC confirmed by pathology undergoing radical gastrectomy were considered for the retrospective analysis The inclusion criteria were as follows: i) Detailed laboratory test data; ii) no pre-operative metastases confirmed by computed tomography (CT); iii) no pre-operative anti-tumor treatments; iv) complete lymph node dissection; v) complete records and follow-up data, and continuous regular follow-up. Finally, 679 patients were included into the present study and further divided into a primary cohort (January 2013 to December 2013; n=300), an internal validation cohort (January 2014 to October 2014; n=278), and an external validation cohort (May 2012 to May 2015; n=101). The patients in the primary cohort and internal validation cohort were from Wujin Hospital and the patients in the external validation cohort were from the Southern Branch of Wujin Hospital. Wujin Hospital and the Southern Branch of Wujin Hospital are 2 different centers, independent of each other, serving different populations. Wujin Hospital serves the people (~1,300,000) from the Tianning, Zhonglou and Xinbei districts, and Changzhou city. The Southern Branch of Wujin Hospital serves the people (~1,400,000) from the Wujin district and Changzhou city. The grouping method was consistent with a previous study (7).

Data collection

Clinical characteristics, including the status of the patients, operative features, results of laboratory tests, histologic and pathologic features of tumors, and prognostic data were collected. The TNM staging system (American Joint Committee on Cancer, 8th ed., 2018) was used to stage the tumors (10). Laboratory examinations included neutrophil, lymphocyte, monocyte and platelet count, and D-dimer and carcinoembryonic antigen (CEA). The NLR was defined as the absolute neutrophil count divided by the absolute lymphocyte count. The MLR was defined as the absolute monocyte count divided by the absolute lymphocyte count. The PLR was defined as the absolute platelet count divided by the absolute lymphocyte count. The NMLR was defined as the product of the neutrophil count and monocyte count divided by the absolute lymphocyte count. The platelet-neutrophil-lymphocyte ratio (PNLR) was defined as the product of the platelet count and neutrophil count divided by the absolute lymphocyte count. The platelet-monocyte-lymphocyte ratio (PMLR) was defined as the product of platelet count and monocyte count divided by the absolute lymphocyte count.

Follow-up

During the first year following surgery, patients were examined once a month. During the second year, follow-up was performed every 3 months. For the third year, patients were followed up twice a year, and then once annually thereafter. The parameters determined at each visit included thoracic and abdominal CT scan, blood routine, hepatic and renal function, D-dimer and CEA.

Statistical analysis

The receiver operating characteristics (ROC) curve was used to calculate the optimal cutoff values (by Youden index) of systemic inflammatory/immune cell counts or ratios and the areas under the ROC curve (AUC). For continuous variables, differences between groups were analyzed using one-way analysis of variance with least significant difference test. Categorical variables were analyzed using the χ2 test. Survival curves were drawn using the Kaplan-Meier method and compared using log-rank tests. Parameters in nomograms were selected by univariate and multivariate analyses, using a Cox proportional-hazards model. Statistical analyses were performed with SPSS 20.0 for Windows (IBM Corp.).

Two nomograms were established using the rms package in R v.3.5.1 (http://www.r-project.org/). Differences between the predictive model and experimental data were quantified according to the concordance index (C-index). Bootstraps with 1,000 resamples were used to estimate bias and present calibration plots. For all statistical tests, a two-sided P<0.05 was considered to indicate a statistically significant difference.

Results

Clinicopathological characteristics

The clinicopathological characteristics of the 679 cases in the primary and validation cohorts are summarized in Table I. The median follow-up time was 61, 51 and 49 months, the median age was 67, 66 and 67 years, and the median tumor size was 4.0, 4.0 and 3.5 cm in the primary, internal validation and external validation cohorts, respectively. Among all cases, the neutrophil, monocyte, lymphocyte and platelet counts ranged from 1.24–13.75×109/l, 0.03–1.61×109/l, 0.33–5.49×109/l and 68–768×109/l, respectively. The laboratory test results were comparable among the three cohorts, with the exception of the monocyte (P=0.001), albumin (P<0.001) and globulin levels (P=0.001), as presented in Table I.

Table I.

Characteristics of patients in the primary and validation cohorts.

Table I.

Characteristics of patients in the primary and validation cohorts.

CharacteristicsPrimary cohort (n=300)Internal validation cohort (n=278)External validation cohort (n=101)P-value
Age, year, median (range)67 (39–91)66 (38–85)67 (29–92)0.363
Sex (male/female)214/86198/8078/230.469
Neutrophil, 10×9/l, median (range)4.00 (1.30–13.48)3.81 (1.24–13.72)3.83 (1.40–13.75)0.517
Monocyte, 10×9/l, median (range)0.35 (0.03–1.23)0.39 (0.11–1.27)0.41 (0.07–1.61)<0.001
Lymphocyte, 10×9/l, median (range)1.48 (0.33–4.05)1.50 (0.51–3.87)1.45 (0.49–5.49)0.411
Platelet, 10×9/l, median (range)210 (82–585)205 (68–768)211 (83–492)0.372
Albumin, median (range)40 (22.3–50.3)39.7 (24.39–59.3)42.8 (26.6–55.6)<0.001
Globulin, median (range)26.6 (16.6–39.4)24.9 (14.0–39.0)24.5 (13.9–34.4)<0.001
D-dimer, median (range)0.33 (0.03–40.00)0.30 (0.06–6.65)0.44 (0.05–22.7)0.071
CEA, median (range)2.01 (0.11–527.53)2.35 (0.15–391.10)2.21 (0.42–193.8)0.591
Tumor size, cm (range)4.0 (0.3–14.0)4.0 (0.3–14.0)3.5 (0.6–11.0)0.172
Tumor differentiation (I–II/III–IV)52/24875/20315/860.005
TNM stage (I–II/III)164/134153/12550/510.589

[i] CEA, carcinoembryonic antigen.

Overall survival (OS) and recurrence-free survival (RFS) in the three cohorts

For the primary cohort, the 1-, 3- and 5-year OS rates were 92.7, 68.0 and 57.7%, and the 1-, 3- and 5-year RFS rates were 92.3, 58.3 and 39.7%, respectively. For the internal validation cohort, the 1- and 3-year OS rates were 95.7 and 66.9%; the 1- and 3-year RFS rates were 93.9 and 52.2%, respectively. For the external validation cohort, the 1- and 3-year OS rates were 91.1 and 64.4%, and the 1- and 3-year RFS rates were 90.1 and 48.5%, respectively.

Comparison of predictive accuracy of the systemic inflammatory/immune parameters in the primary cohort

The optimal cutoff values of systemic inflammatory/immune cell counts or ratios were estimated from the ROC curves when the Youden index was maximal, as presented in Fig. 1. For OS, the optimal cutoff levels for the neutrophil, lymphocyte, monocyte and platelet counts, NLR, MLR, PLR, NMLR, PNLR and PMLR were 4.09, 1.10, 0.38, 216.00, 2.50, 0.29, 140.77, 1.15, 580.23 and 63.61, respectively. For RFS, the optimal cutoff levels for the neutrophil, lymphocyte, monocyte and platelet counts, NLR, MLR, PLR, NMLR, PNLR and PMLR were 4.38, 1.28, 0.29, 216.00, 2.65, 0.29, 144.29, 1.17, 668.00 and 59.22, respectively. The final cut-off levels for the neutrophil, lymphocyte, monocyte and platelet counts, NLR, MLR, PLR, NMLR, PNLR and PMLR were calculated as the average of the OS and RFS values, and were set as 4.23, 1.19, 0.33, 216.00, 2.57, 0.29, 143.00, 1.16, 624.00 and 61.40, respectively.

The quality of the association between each systemic inflammatory/immune parameter and the OS or RFS rates were compared using log-rank tests. As presented in Fig. 2, the neutrophil count (both P<0.001), monocyte count (both P<0.001), platelet count (both P<0.001), NLR (both P<0.001), MLR (both P<0.001), PLR (P=0.004 and P=0.003), NMLR (both P<0.001), PNLR (both P<0.001) and PMLR (both P<0.001) were associated with OS and RFS. The sensitivities and specificities of each parameter was compared using ROC curves, as presented in Fig. 3. Among all inflammatory/immune parameters, the NMLR consistently exhibited the highest AUC value for OS (AUC=0.728) and RFS (AUC=0.695). Patients with a low NMLR demonstrated significantly improved OS and RFS compared with those with a high NMLR, as presented in Fig. 4.

Prognostic factors according to univariate and multivariate analyses in the primary cohort

In the primary cohort, univariate analyses were used to identify the potential predictive factors. Subsequently, the significant predictive factors were subjected to multivariate analyses. It was demonstrated that the degree of differentiation (DD; P=0.003 and P=0.010), T stage (both P<0.001), N stage (both P<0.001), and NMLR (both P<0.001) were independent prognostic factors for OS and RFS, respectively (Table II).

Table II.

Univariate and multivariate analyses, using a Cox proportional-hazards model of OS and recurrence-free survival of gastric cancer in primary cohort.

Table II.

Univariate and multivariate analyses, using a Cox proportional-hazards model of OS and recurrence-free survival of gastric cancer in primary cohort.

OSRFS


Univariate analysisMultivariate analysisUnivariate analysisMultivariate analysis




Prognostic variablesHR (95% CI)P-valueHR (95% CI)P-valueHR (95% CI)P-valueHR (95% CI)P-value
Age0.9980.8331.0040.620
(0.979–1.017) (0.988–1.020)
Sex1.5320.0461.0820.345
(1.007–2.330) (0.919–1.274)
Tumor size1.161<0.0011.181<0.001
(1.089–1.239) (1.120–1.245)
DD<0.0010.003<0.001   0.010
T-stage<0.001<0.001<0.001<0.001
N-stage<0.001<0.001<0.001<0.001
NMLR0.291<0.0010.162<0.0010.365<0.0010.229<0.001
(0.205–0.413) (0.107–0.244) (0.272–0.490) (0.165–0.318)
D-dimer0.9840.6391.0210.356
(0.918–1.054) (0.977–1.066)
CEA1.0030.0251.0030.033
(1.000–1.005) (1.000–1.005)

[i] OS, overall survival; RFS, recurrence-free survival; HR, hazard ratio; CI, confidence interval; DD, degree of differentiation; NLR, neutrophil-to-lymphocyte ratio; MLR, monocyte-to-lymphocyte ratio; PLR, platelet-to-lymphocyte ratio; NMLR, neutrophil-monocyte-lymphocyte ratio; PNLR, platelet-neutrophil-lymphocyte ratio; PMLR, platelet-monocyte-lymphocyte ratio; CEA, carcinoembryonic antigen.

Establishment and evaluation of nomograms for OS and RFS

The nomograms for OS (Fig. 5A) and RFS (Fig. 5B) were established using independent prognostic factors identified in the multivariate analysis conducted in the primary cohort. The C-index of the nomograms for OS was 0.851 [95% confidence interval (CI), 0.817–0.883], which was increased compared with that of DD (0.636; 95% CI, 0.593–0.679), the NMLR (0.667; 95% CI, 0.628–0.706) and the TNM stage (0.731; 95% CI, 0.698–0.764). The C-index of the nomograms for RFS was 0.860 (95% CI, 0.831–0.889), which was increased compared with that of DD (0.629; 95% CI, 0.591–0.667), the NMLR (0.645; 95% CI, 0.612–0.678) and the TNM stage (0.740; 95% CI, 0.712–0.768). Concomitantly, the nomograms for OS and RFS exhibited the largest AUC value (0.933 for OS and 0.944 for RFS) compared with DD (0.674 for OS and 0.679 for RFS), NMLR (0.728 for OS and 0.695 for RFS) and TNM stage (0.817 for OS and 0.855 for RFS), as presented in Fig. 6. In the internal validation cohort, the C-indexes of the nomogram for OS and RFS were 0.840 (95% CI, 0.803–0.877) and 0.916 (95% CI, 0.895–0.937), respectively. In the external validation cohort, the C-indexes of the nomogram for OS and RFS were 0.827 (95% CI, 0.763–0.891) and 0.891 (95% CI, 0.852–0.930), respectively. The calibration plots generated in the present study exhibited a good coherence between the predictions and observations regarding 3-year survival and recurrence, as presented in Fig. 7.

Discussion

In the development of GC, sustained inflammatory and immune responses are hypothesized to serve a role, and they are considered to be the most important risk factors for prognosis (11,12). GC is associated with Helicobacter pylori infection, which stimulates Toll-like receptors, induces infection-associated inflammation and generates an inflammatory microenvironment by activating innate immunity. Immune cells, particularly regulatory T cells, have been considered to be involved in inflammatory and immune response during the development of GC (13). These responses result in neutrophilia, lymphopenia and thrombocytosis. A high absolute neutrophil, monocyte and platelet count, and a low absolute count of lymphocytes have been demonstrated to be associated with poor prognosis of patients with GC (14,15). The tumor immune microenvironment of GC is complex and changeable, and it involves various inflammatory cells, immune cells and tumor cells. The majority of single inflammatory or immune cell type counts are not sufficient to predict the prognosis of patients with GC after R0 resection. Numerous studies have revealed that systemic inflammation/immune cell ratios may be recognized as significant independent risk factors for the prognosis of GC (5,1618). However, to date, only a few studies have compared the predictive value of all inflammatory/immune parameters (7,19). The present study demonstrated that the NMLR exhibited the highest accuracy and predictive power; among all inflammatory/immune parameters assessed, it was the only parameter that was independently associated with OS and RFS.

The roles of inflammatory and immune cells in tumorigenesis may explain their predictive capacities regarding prognosis. Increasing evidence suggests that inflammatory environments accelerate the progression of metastasis by neutrophil-mediated mechanisms (20). For example, neutrophils contribute to the initiation of natural killer cell and monocyte recruitment by various mechanisms (21). Neutrophils and monocytes may contribute to tumor progression by releasing prostaglandin E2 to amplify inflammation and create the tumor microenvironment (22). Conversely, lymphocytes may kill tumor cells through cytotoxic effects from the release of chemokines and cytokines, including interleukin-16, C-C motif chemokine ligand 21 and vascular endothelial growth factor A, which attract monocytes, dendritic cells and endothelial cells to the tumor core and invasive margin (23,24). Therefore, the NMLR may reflect the complex interaction between neutrophils, monocytes and lymphocytes in the tumor microenvironment.

The present study analyzed the predictive ability of NMLR. To the best of our knowledge, the present study was the first to demonstrate that the NMLR, which reflects the homeostasis between host inflammatory and immune status, exhibited a greater prognostic value in GC compared with any other inflammatory/immune parameters; it was also the first to demonstrate that 2 specific OS and RFS nomograms, which included NMLR as one of their factors, exhibited high predictive values compared with measuring NMLR and the TNM stage separately. Among all factors involved in the 2 nomograms, the T stage, N stage and DD have been previously suggested to be associated with the prognosis of GC after gastrectomy (25,26). Although certain risk factors, including CEA, sex, age and D-dimer, are associated with the prognosis of patients with GC (2730), these factors were not applicable in the present study.

The nomogram described in the present study has several specific characteristics that distinguish it from previous nomograms. Firstly, the clinical and pathological factors included in the nomograms of the present study are much simpler to determine by routine clinical analysis. Furthermore, the nomogram did not just include the severity of GC, but the immune status of the patient was also considered. Finally, internal and external validation confirmed this accuracy.

There are several limitations which should be taken into consideration when interpreting the conclusions of the present study. Firstly, the present study was limited by its retrospective nature. Furthermore, as certain cases were followed up for <5 years, the 5-year survival rate and 5-year recurrence-free survival rate were not sufficiently accurate. In addition, the effects of adjuvant treatment, including chemotherapy or radiation treatment, were not evaluated. As an additional limitation, nutritive indexes were not considered in the present study. Previous studies demonstrated that certain nutritive indexes, including Controlling Nutritional Status, prognostic nutritional index and pre-operative body weight, were closely associated with the prognosis of GC (3133). Finally, comorbidities, including hypertension and diabetes, were not reflected in the nomograms. It may be assumed that comorbidities may affect the prognosis to a certain extent.

In conclusion, 2 nomograms were described in the present study, which demonstrated predictive value for survival and recurrence in patients with GC after R0 resection with improved sensitivity and accuracy. This evaluation system may provide valuable insight into identifying patients with a high risk of poor prognosis following surgery. Close follow-up and comprehensive anti-tumor therapy are more suitable for these people. However, a large-sample prospective study is required to determine whether these nomograms are sufficiently accurate, and whether any further risk factors should be considered for inclusion in the assessment.

Acknowledgments

Not applicable.

Funding

The present study received a grant (grant no. WS201515) from the Science and Technology Bureau of Changzhou Municipal Wujin District.

Availability of data and materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Authors' contributions

YT, HW, YW and PJ were responsible for data curation and YQ performed the statistical analysis. XX was responsible for acquiring the funding. WD, XX and XZ developed the methodology of the present study and WD, WX and YX performed the software analysis. WD and XX supervised the study. WD and WX wrote the original draft of the manuscript, and WD performed the review and editing of the manuscript.

Ethics approval and consent to participate

The present study was approved by the Ethics Committee of Wujin Hospital Affiliated to Jiangsu University. Due to the retrospective nature of this study, the need for written informed consent was waived.

Patient consent for publication

Due to the retrospective nature of this study, informed consent was waived.

Competing interests

The authors declare that they have no competing interests.

Glossary

Abbreviations

Abbreviations:

GC

gastric cancer

OS

overall survival

RFS

recurrence-free survival

TNM

tumor-nodes-metastasis

DD

degree of differentiation

NLR

neutrophil-to-lymphocyte ratio

MLR

monocyte-to-lymphocyte ratio

PLR

platelet-to-lymphocyte ratio

CT

computed tomography

CEA

carcinoembryonic antigen

NMLR

neutrophil-monocyte-lymphocyte ratio

PNLR

platelet-neutrophil-lymphocyte

PMLR

platelet-monocyte-lymphocyte

ROC

receiver operating characteristics

AUC

area under the ROC curve

HR

hazard ratio

CI

confidence interval

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November-2019
Volume 18 Issue 5

Print ISSN: 1792-1074
Online ISSN:1792-1082

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Copy and paste a formatted citation
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Spandidos Publications style
Xue W, Xu X, Tan Y, Qian Y, Wang H, Wang Y, Xu Y, Zhu X, Jiang P, Ding W, Ding W, et al: Evaluating and validating the predictive ability of preoperative systemic inflammatory/immune cells in gastric cancer following R0 resection. Oncol Lett 18: 5205-5214, 2019
APA
Xue, W., Xu, X., Tan, Y., Qian, Y., Wang, H., Wang, Y. ... Ding, W. (2019). Evaluating and validating the predictive ability of preoperative systemic inflammatory/immune cells in gastric cancer following R0 resection. Oncology Letters, 18, 5205-5214. https://doi.org/10.3892/ol.2019.10867
MLA
Xue, W., Xu, X., Tan, Y., Qian, Y., Wang, H., Wang, Y., Xu, Y., Zhu, X., Jiang, P., Ding, W."Evaluating and validating the predictive ability of preoperative systemic inflammatory/immune cells in gastric cancer following R0 resection". Oncology Letters 18.5 (2019): 5205-5214.
Chicago
Xue, W., Xu, X., Tan, Y., Qian, Y., Wang, H., Wang, Y., Xu, Y., Zhu, X., Jiang, P., Ding, W."Evaluating and validating the predictive ability of preoperative systemic inflammatory/immune cells in gastric cancer following R0 resection". Oncology Letters 18, no. 5 (2019): 5205-5214. https://doi.org/10.3892/ol.2019.10867