Evaluating and validating the predictive ability of preoperative systemic inflammatory/immune cells in gastric cancer following R0 resection
- Authors:
- Published online on: September 13, 2019 https://doi.org/10.3892/ol.2019.10867
- Pages: 5205-5214
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Copyright: © Xue et al. This is an open access article distributed under the terms of Creative Commons Attribution License.
Abstract
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) (4–6). 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.
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. |
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 (5,16–18). 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 (27–30), 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 (31–33). 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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