Proportional Correlation Between Systemic Inflammation Response Index and Gastric Cancer Recurrence Time

doi:10.21203/rs.3.rs-4905535/v1

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Proportional Correlation Between Systemic Inflammation Response Index and Gastric Cancer Recurrence Time

https://doi.org/10.21203/rs.3.rs-4905535/v1

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Disease recurrence is the primary cause of death in patients with gastric cancer who have undergone complete surgical resection. No prognostic factors for recurrence, other than the tumor, node, metastasis (TNM) stage, have been established. However, even within the same TNM stage, recurrence rates differ. Therefore, we developed a new prognostic confidence measure for gastric cancer recurrence and demonstrated its practical utility. In this retrospective study, we enrolled patients diagnosed with stage II/III gastric cancer who underwent complete surgical resection and adjuvant chemotherapy at the Chungnam National University Hospital, South Korea over the past 12 years. The associations among seven variables, including the systemic inflammation response index (SIRI), and gastric cancer recurrence was analyzed. A total of 296 patients were enrolled. Although other factors did not exhibit significance, the SIRI showed a positive correlation with gastric cancer recurrence risk, confirmed through Cox regression testing (hazard ratio, 1.231; 95% confidence interval, 1.04–1.45). Linear regression analysis revealed a significant association between higher SIRI values and shorter recurrence time (p = 0.044; β = −0.225). Other than the SIRI, effective prognostic factors related to gastric cancer recurrence were not verified. SIRI shows potential as an independent prognostic factor.

Biological sciences/Cancer/Gastrointestinal cancer/Gastric cancer

Biological sciences/Cancer/Cancer prevention

Stomach Neoplasms

Recurrence

Prognosis

Chemotherapy

Adjuvant

Although the incidence and mortality rates of gastric cancer are continuously decreasing owing to medical advances, it remains one of the cancers with the highest incidence and mortality rates worldwide, especially in East Asia, including South Korea^{[1, 2]}. The standard treatment for stage II and III gastric cancer is surgical gastrectomy and lymph node (D2) dissection^[3]. To reduce the possibility of recurrence, adjuvant chemotherapy is administered postoperatively^{[4, 5]}. The main cause of death in patients with gastric cancer who undergo complete surgical resection is cancer recurrence, occurring despite adjuvant chemotherapy^[6]. The recurrence rate postoperatively is as variable as 20–60%^{[7, 8]}. Therefore, predicting an individual patient's risk of recurrence is clinically important for precision medicine. Many previous studies reported on prognostic factors of gastric cancer recurrence; however, factors other than tumor node metastasis (TNM) stage remain unclear. Even when adjuvant chemotherapy is administered for the same TNM stage, some patients experience recurrence, indicating the influence of other factors in addition to the TNM stage. Gastric cancer has high intra-tumor heterogeneity, and even if patients diagnosed at the same stage are treated, there may be differences in the incidence of resistance to anticancer drugs and recurrence rates^{[9, 10]}. Therefore, we planned a study to identify factors other than TNM stage that could predict gastric cancer recurrence.

The primary aim of this study was to identify and evaluate multiple factors that could predict the recurrence of gastric cancer after surgical resection and adjuvant chemotherapy in patients with stage II/III gastric cancer. Therefore, we first selected several factors that were mentioned as predictors of gastric cancer recurrence in previous studies and attempted to identify new aspects from our hospital data that could be used clinically. Second, we attempted to create a prognosis prediction scoring system using the factors identified through this process.

Study population

This retrospective study was conducted at a tertiary medical center in South Korea. The study was conducted on patients diagnosed with gastric cancer TNM stage (the American Joint Committee on Cancer eighth edition) II or III at Chungnam National University Hospital between January 1, 2010, and December 31, 2022, and treated with adjuvant chemotherapy after total gastrectomy. All procedures complied with the ethical standards of the responsible committees on human experimentation (institutional and national) and the Declaration of Helsinki of 1964 and its later versions. The retrospective study protocol was approved by the Institutional Review Board of Chungnam National University Hospital (approval number: 2023-06-037), and the requirement for written consent was waived based on the retrospective design.

Exclusion criteria were as follows: no available surgical pathology results from our hospital, non-performance of complete surgical resection (R0 resection), diagnosis of pathologic TNM stage I or IV, no postoperative adjuvant chemotherapy administration, diagnosis of other cancers, and history of previous chemotherapy or radiation treatment.

Prognostic factors

To select predictive factors that showed an association with gastric cancer recurrence, in addition to the TNM stage, we selected factors that have been reported to be related to the prognosis of gastric cancer. In addition to the systemic inflammation response index (SIRI, neutrophil × monocyte/lymphocyte)^[11], an inflammatory marker obtained using a peripheral blood test, the following prognostic biomarkers, which are included in the majority of gastric cancer pathology findings at our hospital, were investigated: P53^{[12, 13]}, E-cadherin^[14–16], HER2^[17–19] using immunohistochemistry (IHC); Lauren classification^[20], a histological classification system; Epstein-Barr virus (EBV) using in situ hybridization^{[21, 22]}; and microsatellite instability (MSI) status using DNA polymerase chain reaction^[23–25].

Using IHC, P53 was classified as “overexpressed” if it showed > 10% nuclear-stained cancer cells, and as “wild type” if it was < 10%^{[26, 27]}. E-cadherin was described as “not decreased” when preserved and “decreased” when reduced or not detected. HER2 was classified as “negative” for 0/1 + and “positive” for 2+/3 + according to immunoreactivity^[28]. In case of the Lauren classification, it was classified as “intestinal/diffuse/mixed type” according to histopathological findings. EBV was classified as “negative/positive” depending on whether it was detected. The MSI status was classified as “high” for a high degree of MSI and “low” for a low degree or stable MSI. The SIRI was calculated using the results of the last peripheral blood test performed before gastric cancer resection surgery.

Statistical analysis

Statistical analyses were performed using SPSS (version 29.0; IBM, Inc., USA). Nominal variables were analyzed using the chi-square test for continuous variables. Cut-off values were obtained using the receiver operating characteristic curve, converted into nominal variables, and were analyzed using chi-square tests. To determine whether the SIRI increases the recurrence risk regardless of TNM stage, we analyzed the gastric cancer recurrence rate between the high- and low-SIRI groups at the same TNM stage (cut-off, 2.1) using chi-square test and Kaplan–Meier curve analysis. Cox regression and linear tests were performed using the product. Linear regression analysis was performed to determine the relationship between the SIRI and recurrence time. Statistical significance was set at a two-sided p-value < 0.05.

A total of 296 patients were finally analyzed in this study. Patient selection and exclusion are shown in Fig. 1. Recurrence occurred in 82 patients during follow-up. The baseline and clinicopathological characteristics of these patients are summarized in Table 1.

Table 1

Baseline and clinicopathological characteristics of patients
		N	%
Age (years)	≤65	160	54.1
	> 65	136	45.9
Sex	Male	202	68.2
	Female	94	31.8
Location	Cardia	21	7.1
	Body	135	45.6
	Antrum	134	45.3
	Whole	6	2
Differentiation	Well	3	1
	Moderate	155	52.7
	Poor	136	46.3
Depth of invasion	T1	24	8.1
	T2	50	16.9
	T3	115	38.9
	T4	107	36.1
LN metastasis	N0	53	17.9
	N1	72	24.3
	N2	83	28
	N3	88	29.7
TNM stage (8th )	Stage II	147	49.7
	Stage III	149	50.3
LN, lymph node

For each prognostic factor, the chi-square test was performed to classify the patients into groups that did not experience recurrence and those that experienced recurrence during the follow-up period. The SIRI and TNM stage were significantly related to gastric cancer recurrence, but other factors were not significantly associated (Table 2). The SIRI is a continuous variable, and the cut-off value calculated using the ROC curve for analysis was 2.1 (10³/µL) (Fig. 2)

Table 2

Chi-square analysis of predictive factors of recurrence
N (%)
		Total	No recurrence	Recurrence	χ2 (p)
HER2	Negative	187 (100)	143(77)	55 (23)	3.062 (0.08)
	Positive	83 (100)	55(66)	28 (34)	3.062 (0.08)
Lauren classification	Intestinal	152 (100)	108(71)	44 (29)	0.353 (0.838)
	Diffuse	111 (100)	82(74)	29 (26)
	Mixed	28 (100)	21(75)	7 (25)
P53	Wild type	69 (100)	55(80)	14(20)	1.541(0.214)
	Overexpression	149 (100)	107(72)	42(28)	1.541(0.214)
SIRI	Low	267 (100)	202(76)	65 (24)	15.345* (< 0.001)
	High	29 (100)	12(41)	17 (59)	15.345* (< 0.001)
EBV	Negative	92 (100)	74(80)	18 (20)	0.136 (0.712)
	Positive	8 (100)	6(75)	2 (25)	0.136 (0.712)
E-cadherin	Not decreased	125 (100)	90(72)	35 (28)	2.601 (0.107)
	Decreased	41 (100)	24(59)	17 (42)	2.601 (0.107)
MSI	MSS/MSI-L	50 (100)	43(86)	7 (14)	0.031 (0.860)
	MSI-H	6 (100)	5(83)	1 (17)	0.031 (0.860)
TNM stage	Stage II	147 (100)	130(88)	17 (12)	37.97* (< 0.001)
	Stage III	149 (100)	84(56)	65 (44)	37.97* (< 0.001)
*p < 0.05
EBV, Epstein-Barr virus; MSI, microsatellite instability; MSI-L, MSI-low degree; MSI-H, MSI-high degree; and SIRI, systemic inflammatory response index.

The chi-square test revealed significantly higher recurrence in both TNM stages II and III of the high-SIRI group (Table 3). Kaplan–Meier survival curve analysis showed that recurrence was more likely to occur in the high-SIRI group only in TNM stage III (Fig. 3), suggesting a greater correlation between recurrence and a high TNM stage.

Table 3

Chi-square analysis of recurrence according to the TNM stage
N (%)
		Total	No recurrence	Recurrence	χ2 (p)
TNM state II	Low SIRI	139 (100)	124 (90)	14 (10)	4.442* (0.035)
	High SIRI	9 (100)	6 (67)	3 (33)	4.442* (0.035)
TNM stage III	Low SIRI	129 (100)	78 (60)	51 (40)	6.535* (0.011)
	High SIRI	20 (100)	6 (30)	14 (70)	6.535* (0.011)
*p < 0.05
SIRI, systemic inflammatory response index

Univariate and multivariate Cox regression analyses revealed a positive correlation between the SIRI and gastric cancer recurrence (univariate analysis: p < 0.001; hazard ratio [HR], 1.32; 95% confidence interval [CI], 1.127–1.545; multivariate analysis: p = 0.016; HR, 1.231; 95% CI, 1.04–1.459).

Linear regression analysis revealed a significantly negative correlation between the SIRI and gastric cancer recurrence time (p = 0.044; β = −0.225), indicating that the higher the SIRI, the shorter the time it takes for gastric cancer to recur (Fig. 4).

Postoperative recurrence is a major cause of death in patients with gastric cancer. However, no established prognostic factors, other than TNM, have been identified. Therefore, it is important to identify prognostic factors for gastric cancer recurrence. While designing the study, several pathological factors were considered important, but only the SIRI was significantly associated with gastric cancer recurrence.

The relationship between inflammation and cancer has been extensively studied over the past 20 years. Immune cells have high plasticity and may show antitumor activity or, conversely, may have pro-tumorigenic activity^[29–32]. In particular, systemic inflammation caused by innate/adaptive immunity is complex and highly variable, causing controversy. However, several epidemiological studies have shown that chronic inflammation causes tumor development. One prospective study showed that the cancer incidence rate in patients with elevated circulating inflammatory markers (e.g., C-reactive protein) during routine checkup was more than twice that of the control group^[33]. According to a 2018 survey, 42% of adult cancers in North America are caused by correctable risk factors, all of which cause local or systemic inflammation^[34]. Large-scale clinical studies have also provided evidence that non-specific inflammation inhibition using non-steroidal anti-inflammatory drugs reduces the incidence and mortality of various cancers^{[35, 36]}.

Unlike acute inflammation, which promotes antitumor immunity, chronic inflammation is non-resolving^[37]. Both acute inflammation and its resolution are complex programmed processes, which if not controlled, can lead to a chronic inflammatory state and immunosuppressive microenvironment through the recruitment of immunosuppressive cells and cytokines^{[38, 39]}. As the relationship between inflammation and cancer has been revealed, interest in the tumor microenvironment (TME), which comprises tumor cells and surrounding non-malignant cells, has increased. Much research is being conducted on the signaling pathways of immune cells and mediators, such as cytokines and chemokines, which make up the TME, and recent developments in cancer treatments have also focused on related areas^{[40, 41]}. The first attempt to classify cancer type in patients with colorectal cancer was based on the immune base rather than the TNM stage. Depending on the degree of cytotoxic T-cell infiltration around the tumor cells, it is classified as a hot, altered, or cold tumor. Cancers with high T-cell infiltration have an antitumor effect and a good prognosis^{[42, 43]}. Moreover, a higher expression of Programmed Cell Death Protein1/Programmed Cell Death Ligand1 (PD-1/PD-L1) in tumor-associated immune cells showed a greater antitumor effect^[44]. Accordingly, checkpoint inhibitors have been developed for various cancer types, and the PD-1 inhibitor nivolumab is also used clinically as a treatment for gastric cancer^[45].

Analyzing the local immunity/inflammation of the TME requires tissue and pathological analyses, which are time-consuming and expensive. Moreover, in many cases, a partial biopsy is performed, which does not analyze the entire tumor tissue, and in such cases, analysis errors may occur. A clear relationship between systemic and local inflammation has not yet been revealed; however, the immune system of the human body may be related to both local and systemic inflammation. Therefore, studies on systemic inflammatory markers are ongoing. Many studies have reported on various types of systemic inflammatory markers such as neutrophil-lymphocyte, platelet-lymphocyte, and lymphocyte-monocyte ratios and systemic immune-inflammation index in several cancer types^[46–50]. Among them, the SIRI is calculated from the number of neutrophils, monocytes, and lymphocytes in peripheral blood and is known to be associated with poor prognosis in various carcinoma types^[51]. A high SIRI indicates an increase in blood neutrophil and monocyte levels and a decrease in lymphocyte levels, which is related to tumor progression, infiltration, and metastasis^[52–54]. The SIRI includes neutrophils and monocytes, which are among the most studied innate immune cells related to cancer progression. Moreover, the SIRI was selected because it comprises three inflammatory markers, including lymphocytes, and is expected to complement the interactions between markers, including innate, and adaptive immunity.

This study had several limitations. First, we attempted to develop a recurrence prediction scoring system using prognostic factors for gastric cancer recurrence. However, we were unable to develop this model because fewer factors showed significant results than expected. To construct this model, further research should be conducted with a larger sample size to identify more factors that increase the risk of gastric cancer recurrence. Second, systemic inflammation might have been affected by various external factors such as infection and inflammatory diseases. To minimize the possible impact, the SIRI was obtained from the last blood test performed before gastric cancer resection surgery, and this was combined with other test results, including chest radiography, urinalysis, and vital signs to determine test results, such as infection and fever. Finally, most studies related to systematic inflammatory markers and cancer prognosis are limited to China; therefore, references related to various races are lacking. Moreover, the cut-off values were set differently for each study. Therefore, additional studies including more diverse races and larger numbers of patients are necessary.

Through this study, we confirmed that the SIRI could be independently used as a risk factor for gastric cancer recurrence, regardless of TNM stage. The fact that significant results were obtained after excluding TNM stage, the strongest risk predictor, provides grounds for recognizing the SIRI as an independent factor. Additionally, a proportional relationship between the SIRI and timing of gastric cancer recurrence was confirmed. To the best of our knowledge, this finding is a novel contribution that has not been reported in previous studies. Both the recurrence of gastric cancer and the period of disease-free survival greatly affect a patient's quality of life; thus, measuring the SIRI as a predictive factor can have clinical significance. The SIRI is simple and cost-effective to measure, meaning that it can be easily integrated into routine postoperative monitoring protocols for patients with stage II/III gastric cancer to provide early identification of individuals at higher risk of recurrence. Furthermore, the SIRI can be a tool to predict the prognosis of patients with gastric cancer undergoing adjuvant anticancer therapy after surgery. Such approaches would allow for personalized follow-up schedules and timely intervention strategies, potentially improving patient outcomes. Finally, the SIRI could be used to stratify patients in clinical trials, ensuring that those at a higher risk of recurrence receive more intensive monitoring and therapeutic approaches.

Author Contributions

Conception or design of the work: Dr. Kyung Ryun In and Dr. Sun Hyung Kang; acquisition, analysis, or interpretation of data for the work: Dr. Kyung Ryun In, Dr. Sun Hyung Kang, Dr. Hyun Seok Lee, and Dr. Hee Seok Moon; drafting the work or revising it critically for important intellectual content: Dr. Kyung Ryun In, Dr. Sun Hyung Kang, Dr. Hyuk Soo Eun, Dr. Eaum Seok Lee, Dr. Seok Hyun Kim and Dr. Jae Kyu Sung; and final approval of the version to be published: Dr. Kyung Ryun In, Dr. Sun Hyung Kang, and Dr. Byung Seok Lee.

Data Availability Statement

The datasets generated and analyzed during the current study are not publicly available because of the privacy of the research participants but are available from the corresponding author upon reasonable request.

Statement of Ethics

All procedures complied with the ethical standards of the responsible committees on human experimentation (institutional and national) and the Declaration of Helsinki of 1964 and its later versions. The retrospective study protocol was approved by the Institutional Review Board of Chungnam National University Hospital (approval number: 2023-06-037), and the requirement for written consent was waived owing to the retrospective design of this study.

Conflict of Interest Statement

The authors declare no competing interests.

Funding Sources

The authors have no sources of funding to declare.

Morgan, E. et al. The current and future incidence and mortality of gastric cancer in 185 countries, 2020–40: a population-based modelling study. EClinicalmedicine 47, 101404 (2022).
Sung, H. et al. Global cancer statistics 2020: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J. Clin. 71, 209–249 (2021).
Songun, I., Putter, H., Kranenbarg, E. M., Sasako, M. & van de Velde, C. J. Surgical treatment of gastric cancer: 15-year follow-up results of the randomised nationwide Dutch D1D2 trial. Lancet Oncol. 11, 439–449 (2010).
Bang, Y. J. et al. Adjuvant capecitabine and oxaliplatin for gastric cancer after D2 gastrectomy (Classic): a phase 3 open-label, randomised controlled trial. Lancet 379, 315–321 (2012).
Sakuramoto, S. et al. Adjuvant chemotherapy for gastric cancer with S-1, an oral fluoropyrimidine. N. Engl. J. Med. 357, 1810–1820 (2007).
Deng, J. et al. Investigation of the recurrence patterns of gastric cancer following a curative resection. Surg. Today 41, 210–215 (2011).
D’angelica, M. et al. Patterns of initial recurrence in completely resected gastric adenocarcinoma. Ann. Surg. 240, 808–816 (2004).
Wu, C. W. et al. Incidence and factors associated with recurrence patterns after intended curative surgery for gastric cancer. World J. Surg. 27, 153–158 (2003).
McGranahan, N. & Swanton, C. Clonal heterogeneity and tumor evolution: past, present, and the future. Cell 168, 613–628 (2017).
Gullo, I., Carneiro, F., Oliveira, C. & Almeida, G. M. Heterogeneity in gastric cancer: from pure morphology to molecular classifications. Pathobiology 85, 50–63 (2018).
Zhou, Q. et al. Systemic inflammation response index as a prognostic marker in cancer patients: a systematic review and meta-analysis of 38 cohorts. Dose. Response 19, 15593258211064744 (2021).
Yildirim, M., Kaya, V., Demirpence, O., Gunduz, S. & Bozcuk, H. Prognostic significance of p53 in gastric cancer: a meta-analysis. Asian Pac. J. Cancer Prev. 16, 327–332 (2015).
Ando, K. et al. Discrimination of p53 immunohistochemistry-positive tumors by its staining pattern in gastric cancer. Cancer Med. 4, 75–83 (2015).
Loh, C. Y. et al. The E-cadherin and N-cadherin switch in epithelial-to-mesenchymal transition: signaling, therapeutic implications, and challenges. Cells 8, 1118 (2019).
Gabbert, H. E. et al. Prognostic value of E-cadherin expression in 413 gastric carcinomas. Int. J. Cancer 69, 184–189 (1996).
Blok, P., Craanen, M. E., Dekker, W. & Tytgat, G. N. Loss of E-cadherin expression in early gastric cancer. Histopathology 34, 410–415 (1999).
Hofmann, M. et al. Assessment of a HER2 scoring system for gastric cancer: results from a validation study. Histopathology 52, 797–805 (2008).
Kim, S. H., Kim, Y. J. & Chung, W. C. HER-2 positivity is a high risk of recurrence of stage I gastric cancer. Korean J. Intern. Med. 36, 1327–1337 (2021).
Liu, X. et al. Clinical utility of HER2 assessed by immunohistochemistry in patients undergoing curative resection for gastric cancer. Onco Targets Ther. 9, 949–958 (2016).
Pattison, S. et al. Early relapses after adjuvant chemotherapy suggests primary chemoresistance in diffuse gastric cancer. PLOS ONE 12, e0183891 (2017).
Nshizirungu, J. P. et al. Reproduction of the Cancer Genome Atlas (TCGA) and Asian Cancer Research Group (ACRG) Gastric Cancer Molecular Classifications and their Association with clinicopathological characteristics and overall survival in Moroccan patients. Dis. Markers 2021, 9980410 (2021).
Shinozaki-Ushiku, A. S., Kunita, A. & Fukayama, M. Update on Epstein-Barr virus and gastric cancer (review) [review]. Int. J. Oncol. 46, 1421–1434 (2015).
Hudler, P. Genetic aspects of gastric cancer instability. ScientificWorldJournal 2012, 761909 (2012).
Smyth, E. C. et al. Mismatch repair deficiency, microsatellite instability, and survival: an exploratory analysis of the Medical Research Council Adjuvant Gastric Infusional Chemotherapy (MAGIC) Trial. JAMA Oncol. 3, 1197–1203 (2017).
Tsai, C. Y. et al. Is adjuvant chemotherapy necessary for patients with deficient mismatch repair gastric cancer?-autophagy inhibition matches the mismatched. Oncologist 25, e1021–e1030 (2020).
Kakeji, Y. et al. Gastric cancer with p53 overexpression has high potential for metastasising to lymph nodes. Br. J. Cancer 67, 589–593 (1993).
Sumiyoshi, Y. et al. Overexpression of hypoxia-inducible factor 1alpha and p53 is a marker for an unfavorable prognosis in gastric cancer. Clin. Cancer Res. 12, 5112–5117 (2006).
Gao, X. et al. Impact of HER2 on prognosis and benefit from adjuvant chemotherapy in stage II/III gastric cancer patients: a multicenter observational study. Int. J. Surg. 109, 1330–1341 (2023).
Chimal-Ramírez, G. K., Espinoza-Sánchez, N. A. & Fuentes-Pananá, E. M. Protumor activities of the immune response: insights in the mechanisms of immunological shift, oncotraining, and oncopromotion. J. Oncol. 2013, 835956 (2013).
Greten, F. R. & Grivennikov, S. I. Inflammation and cancer: triggers, mechanisms, and consequences. Immunity 51, 27–41 (2019).
Gajewski, T. F., Schreiber, H. & Fu, Y. X. Innate and adaptive immune cells in the tumor microenvironment. Nat. Immunol. 14, 1014–1022 (2013).
Maiorino, L., Daßler-Plenker, J., Sun, L. & Egeblad, M. Innate immunity and cancer pathophysiology. Annu. Rev. Pathol. 17, 425–457 (2022).
Watson, J., Salisbury, C., Banks, J., Whiting, P. & Hamilton, W. Predictive value of inflammatory markers for cancer diagnosis in primary care: a prospective cohort study using electronic health records. Br. J. Cancer 120, 1045–1051 (2019).
Islami, F. et al. Proportion and number of cancer cases and deaths attributable to potentially modifiable risk factors in the United States. CA Cancer J. Clin. 68, 31–54 (2018).
Rothwell, P. M. et al. Effect of daily aspirin on long-term risk of death due to cancer: analysis of individual patient data from randomised trials. Lancet 377, 31–41 (2011).
Rothwell, P. M. et al. Effect of daily aspirin on risk of cancer metastasis: a study of incident cancers during randomised controlled trials. Lancet 379, 1591–1601 (2012).
Nathan, C. & Ding, A. Nonresolving inflammation. Cell 140, 871–882 (2010).
Coussens, L. M. & Werb, Z. Inflammation and cancer. Nature 420, 860–867 (2002).
Mantovani, A., Allavena, P., Sica, A. & Balkwill, F. Cancer-related inflammation. Nature 454, 436–444 (2008).
Zhao, H. et al. Inflammation and tumor progression: signaling pathways and targeted intervention. Signal Transduct. Target. Ther. 6, 263 (2021).
Balkwill, F. R., Capasso, M. & Hagemann, T. The tumor microenvironment at a glance. J. Cell Sci. 125, 5591–5596 (2012).
Galon, J. et al. Type, density, and location of immune cells within human colorectal tumors predict clinical outcome. Science 313, 1960–1964 (2006).
Camus, M. et al. Coordination of intratumoral immune reaction and human colorectal cancer recurrence. Cancer Res. 69, 2685–2693 (2009).
Hegde, P. S., Karanikas, V. & Evers, S. The where, the when, and the how of immune monitoring for cancer immunotherapies in the era of checkpoint inhibition. Clin. Cancer Res. 22, 1865–1874 (2016).
Janjigian, Y. Y. et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet 398, 27–40 (2021).
Liu, J. et al. Systemic immune-inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio can predict clinical outcomes in patients with metastatic non-small-cell lung cancer treated with nivolumab. J. Clin. Lab. Anal. 33, e22964 (2019).
Wang, S. et al. The values of systemic immune-inflammation index and neutrophil-lymphocyte ratio in predicting testicular germ cell tumors: a retrospective clinical study. Front. Oncol. 12, 893877 (2022).
Xia, L. J. et al. Significance of neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio and prognostic nutritional index for predicting clinical outcomes in T1-2 rectal cancer. BMC Cancer 20, 208 (2020).
Zhu, S. et al. Prognostic value of the systemic immune-inflammation index and prognostic nutritional index in patients with medulloblastoma undergoing surgical resection. Front. Nutr. 8, 754958 (2021).
Hong, X. et al. Systemic immune-inflammation index, based on platelet counts and neutrophil-lymphocyte ratio, is useful for predicting prognosis in small cell lung cancer. Tohoku J. Exp. Med. 236, 297–304 (2015).
Wei, L., Xie, H. & Yan, P. Prognostic value of the systemic inflammation response index in human malignancy: A meta-analysis. Medicine 99, e23486 (2020).
Liang, W. & Ferrara, N. The complex role of neutrophils in tumor angiogenesis and metastasis. Cancer Immunol. Res. 4, 83–91 (2016).
Murray, P. J. Immune regulation by monocytes. Semin. Immunol. 35, 12–18 (2018).
Alissafi, T., Hatzioannou, A., Legaki, A. I., Varveri, A. & Verginis, P. Balancing cancer immunotherapy and immune-related adverse events: the emerging role of regulatory T cells. J. Autoimmun. 104, 102310 (2019).

No competing interests reported.

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Proportional Correlation Between Systemic Inflammation Response Index and Gastric Cancer Recurrence Time

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