Bladder cancer (BC) is one of the common urological malignancies, with an estimated 573,000 new BC cases and 213,000 deaths worldwide in 2020 (1). The disease could be divided into two subtypes, namely, non-muscle-invasive bladder cancer (NMIBC) and muscle-invasive bladder cancer (MIBC), according to different clinical progressions and prognoses. Approximately 75% of patients initially present with NMIBC, as NMIBC is associated with a lower risk of death and intravesical recurrence, the 5-year risk of recurrence ranges from 30% to 80%, even after transurethral resection of bladder tumor (TURBT) treatment (2, 3). In addition, despite the administration of postoperative adjuvant drug chemotherapy or immunotherapy, the 5-year overall survival (OS) rate for MIBC is approximately only 50%, and the risk of recurrence is high (4). Therefore, useful biomarkers should be sought in clinical practice to help diagnose, evaluate, and determine the prognosis of BC.

Accumulating evidence suggests that inflammatory responses in the tumor microenvironment (TME) might play a critical role in bladder tumorigenesis, proliferation, progression, and metastasis (5, 6). Inflammation can lead to leukocytosis, neutropenia, and thrombocytopenia. Therefore, various blood-based markers of inflammation, including neutrophil–lymphocyte ratio (NLR), platelet–lymphocyte ratio (PLR), and lymphocyte–monocyte ratio (LMR) have been explored to improve prognostic tools for BC risk stratification and outcomes (7). However, these markers integrate only two types of immune cells, and their predictive and prognostic capabilities are inadequate. The systemic immune-inflammation index (SII) is a novel index based on the count of neutrophils, lymphocytes, and platelets, which is reportedly correlated with survival outcomes for a variety of cancers (8).

Although previous studies have explored the prognostic value of SII in BC patients, the results were not consistent. SII was considered an important prognostic factor in some studies (9–11), whereas other studies have found no significant association between SII and survival outcomes of BC (12, 13). Therefore, this study aimed to use the available data to evaluate the prognostic role of preoperative SII in patients with BC and the association between SII and clinicopathological features of BC.

The high postoperative recurrence rate for patients with BC often affects the patient’s quality of life, which gives researchers the impetus to identify and analyze relevant risk factors affecting tumor recurrence and to develop individualized treatment and follow-up plans for patients with differing recurrence risks. Although histopathological types, histological grades, and pathological stages have been used to predict relapse and progression in patients with BC (3, 21), the heterogeneity of prognosis among patients with similar clinical presentations suggests that more reliable indicators are needed to identify high-risk patients. Recently, an inflammation-related SII obtained from blood samples was shown to be a novel biomarker for predicting the therapeutic efficacy or prognosis among patients with different types of cancers, regardless of the treatment regimen (8, 22). However, the prognostic value of this index in BC is still controversial. Huang et al. (22) performed a systematic review to analyze the prognostic value of SII in urological cancers, and they reported that BC patients with an elevated SII had poorer OS. However, they only analyzed two studies, which greatly reduced the reliability of their conclusions. With the successive publications of relevant studies, a comprehensive investigation of the potential value of SII in terms of clinicopathological features and the prognosis for BC patients is warranted.

To elucidate the role of the SII in the prognosis of BC, data were pooled from 10 studies involving 7,087 patients in the present meta-analysis. The pooled analysis suggested that patients with an increased preoperative SII had inferior OS, CSS, and RFS outcomes. Subgroup analysis also indicated that elevated SII was related to worse OS in MIBC. In addition, high preoperative SII was significantly associated with poor tumor differentiation, high tumor stage of MIBC, presence of LNI, and tumor size ≥3 cm. Taken together, SII could be a potential prognostic biomarker for BC.

Furthermore, host inflammatory responses in cancer have received increasing attention over the past 20 years. Growing evidence suggests that immune cells play an important role in the inflammation process, leading to the production of cytokines and chemokines that accelerate tumor growth, neovascularization, and metastasis (23, 24). A complex balance between inflammatory cells and inflammation-related substances might affect the type of peripheral circulating cells (18). Neutrophils have been linked to tumor progression (25). These cells can infiltrate into the TME and become tumor-related neutrophils, releasing chemical and cytokine factors related to tumor proliferation and metastasis such as vascular endothelial growth factor, elastase, and matrix metalloproteinases (26, 27). Similarly, platelets could release vascular endothelial growth factors, which promote the formation of blood vessels associated with the formation of new tumors and cause adhesion of tumor cells to the vascular wall. This further leads to the proliferation and metastasis of tumor cells (28). However, as the most important immune cells in the body, lymphocytes mainly induce the lysis and apoptosis of target cells and play an antitumor role (29). The lower the level of lymphocytes, the poorer the immune capability of patients; furthermore, the increase of neutrophils could inhibit the activation of T lymphocytes, leading to the decrease of antitumor ability of the body (30). The inflammation, therefore, is closely related to the TME and tumor progression.

In this context, some biomarkers based on peripheral blood cell counts have been proposed to predict tumor prognosis. Nevertheless, when only one or two parameters are involved, these predictors become unstable and are often susceptible to other confounding factors (31). SII is calculated in terms of the neutrophil count × platelet count/lymphocyte count, and it contains three types of inflammatory cells, which objectively reflect the balance between inflammation and the host immune response (20). A higher SII corresponds to higher platelet/neutrophil and/or lower lymphocyte counts. Thus, an elevated SII indirectly symbolizes the deficiency of immune function and the enhancement of tumor aggressiveness in cancer patients (32). As a composite immune index, SII may have better predictive power than parameters such as NLR, PLR, and LMR. Furthermore, the measurement of SII is simple, inexpensive, and reproducible, which makes it a promising biomarker for BC prognosis.

Several previous meta-analyses have investigated the prognostic role of SII in solid tumors. In a pooled analysis of data from 22 studies, Yang et al. (8) found that increased SII may be a reliable prognostic factor for worse OS in various malignancies. Qiu et al. (33) provided evidence that high pretreatment SII was significantly related to worse OS (HR = 1.40, p = 0.010) and several clinical features such as advanced tumor stage, positive node metastasis, and larger tumor size in gastric cancer (GC). They reported that SII can be monitored to guide prognosis and provide useful information about the risk of disease progression in GC. One recent study also indicated that a higher SII was independently related to inferior survival outcomes in renal cell carcinoma patients and that elevated SII suggested more aggressive disease (34). A baseline SII was also found to be useful in clinical practice to stratify patients with metastatic urothelial carcinoma (35). Moreover, Katayama et al. (17) also reported that SII could help improve the decision-making process regarding adjuvant therapy for patients at intermediate risk for NMIBC. The findings of this analysis indicated that SII had prognostic efficiency in terms of OS, CSS, and RFS in patients with BC, which was consistent with findings about other cancer types. We also indicated a significant association between higher SII and invasive pathologic features of BC. Based on these findings and those of other related studies, SII could be considered as an effective prognostic marker for BC that could facilitate risk stratification in patients with BC and help develop appropriate clinical treatment strategies.

Although this analysis provides additional substantial evidence regarding the prognostic value of preoperative SII in BC patients, this study also had several limitations. First, the included studies were retrospectively designed; therefore, inherent structural biases associated with retrospective studies may have contributed to inter-study heterogeneity. Second, although all patients with BC had been treated surgically, postoperative adjuvant therapy strategies and pathological indications are known to vary across institutions, which may have resulted in different survival outcomes. Third, different cutoff values and measurement methods of SII in the included studies may have led to bias in the results. Fourth, due to heterogeneity between the studies, an optimal SII cutoff value to predict postoperative outcomes in patients with BC cannot be determined presently. To address these limitations, further multicenter prospective studies with larger sample sizes are needed.

The present evidence indicates that a higher preoperative SII is associated with worse OS, CSS, and RFS in patients with BC. Furthermore, we demonstrate that elevated SII is independently correlated with adverse pathological features. SII as an effective prognostic indicator may have a crucial role in improving clinical decision-making during BC treatment. However, further study on the role of SII in BC prognosis is required before its widespread use in clinical practice.

The original contributions presented in the study are included in the article/ Supplementary Material . Further inquiries can be directed to the corresponding authors.

Conception/design: QW and TL. Collection and/or assembly of data: JL, DC, and YH. Data analysis and interpretation: JL, LL, QX, and DT. Article writing: JL and DC. Final approval of article: all authors.

This study was supported by the National Natural Science Foundation of China (Grant Number 81974098, 82000721); Post-Doctor Research Project, West China Hospital, Sichuan University (Grant Number 2019HXBH089); and Health Commission of Sichuan province (Grant Number 20PJ036).

The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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