Background:
Systemic Immune-inflammation Index (SII) has been shown to correlate with the prognosis of numerous malignancies, but researchers have not yet reached an agreed conclusion on bladder cancer. To fill the blank, we conducted a meta-analysis to assess the prognostic role of SII in the prognosis of bladder cancer.
Methods:
After analyzing relevant literature published in PubMed, China National Knowledge Infrastructure, EMBASE, Cochrane Library, and Web Science up to April 30, 2022, we collected 83 articles to assess the significance of SII levels in assessing the prognosis of bladder cancer patients, and finally, 11 articles were included in the study. The correlation between pre-treatment Systemic Immunoinflammatory Index levels and survival in bladder cancer patients was assessed using risk ratio (HR) and 95% confidence interval (CI).
Results:
Our meta-analysis comprised 11 papers altogether, and the findings revealed that higher levels of pretreatment SII were significantly associated with poorer overall survival/cancer-specific survival/progression-free survival/recurrence-free survival in bladder cancer patients (pooled HR = 1.80; 95% CI, 1.28–2.51; pooled HR = 1.68; 95% CI, 1.14–2.47; pooled HR = 1.74; 95% CI, 1.25–2.42; pooled HR = 1.73; 95% CI, 1.26–2.39). The above result was also confirmed in the subgroup analysis.
Conclusions:
Higher SII levels were significantly connected with overall survival/cancer-specific survival/progression-free survival/recurrence-free survival rates in bladder cancer patients, suggesting that SII is an important predictor of prognosis in bladder cancer patients.
Keywords: bladder cancer, inflammation index, prognosis, systemic immune
1. Introduction
As one of the most frequent urological malignancies, bladder cancer would be held accountable for 81,180 new cases and 17,100 fatalities in the United States alone in 2022.[1] The biological behavior of bladder cancer dictates the need for more refined, individualized, and multimodal treatment protocols in different clinical stages. The American Urological Association divides bladder cancer patients into different risk categories. For patients with non-muscle invasive bladder cancer (NMIBC) in the low- and intermediate-risk types, their recurrence-free survival (RFS) rates at 5 years are 43% and 33%, respectively. Besides, 21% of the patients in the high-risk group progress to muscle-invasive bladder cancer.[2] Several novel treatment options have emerged in recent years, such as antibody-drug conjugates, targeted therapy, and checkpoint inhibition immunotherapy. However, stratification of patients for treatment has been increasingly prominent.[3] Therefore, it is urgent to uncover predictors of prognosis in patients with bladder cancer. Recent studies have disclosed that interference in the immune system of cancer patients in the development stage of tumor has positive results.[4] In addition, the tumor-promoting or tumor-suppressing effects of the inflammatory microenvironment have also been verified by many researchers.[5] tumor node metastasis staging is the most commonly used metric to assess the prognosis of patients with bladder cancer, and accurate risk stratification provides the best overall benefit for patients at different disease stages, such as determining the timing of radical cystectomy for patients with NMIBC and perioperative adjuvant treatment options for patients with muscle invasive bladder cancer, but there are still differences between patients based on their underlying conditions such as nutritional level/immune system. Tumor node metastasis stage patients still have different clinical outcomes.[6] In recent years, various prognostic prediction models have been developed, such as the European Organization for Research and Treatment of Cancer risk scale to assess the risk of recurrence progression of NMIBC after immunotherapy, but the accuracy of these models still needs to be improved.[7] Therefore, we tried to find new biomarkers that could help scholars to improve the predictive power of the models. Inflammatory markers, including C-reactive protein and neutrophils/lymphocytes, have been reported to be relevant to the prognosis of cancer.[8] Systemic Immunoinflammatory Index (SII) is a newly developed inflammatory index derived from neutrophils*platelets/lymphocytes ratios, which are identified by some meta-analyses as markers of better prognosis in pancreatic, breast, and esophageal cancer patients.[9–11] Meanwhile, some other meta-analyses validate the relevance between SII and the prognosis of urological tumors.[12,13] Nevertheless, extremely few studies on the subgroup of bladder cancer (only 1 or 2 in each case) are a dubious basis for those conclusions. Given the controversial views in the latest studies,[14,15] we performed this meta-analysis to elucidate the role of SII in the prognosis of bladder cancer.
2. Materials and methods
2.1. Search strategy
The PROSPERO Registry (CRD42022329556) has prospectively registered the program under consideration. To accomplish the goal, we searched PubMed, EMBASE, Cochrane Library, Web Science, and China National Knowledge Infrastructure for literature after 2017. The search terms used are (“Systemic Immune Inflammation Index” or “SII”) AND (“Bladder Carcinomas” or “Bladder Cancer”) AND (“prognosis” or “outcome” or “mortality” or “survival” or “recurrence” or “metastasis” or “progression”). The language is English or Chinese. Also, we manually screened the references for relevant literature that met the requirements.
2.2. Inclusion and exclusion criteria
Literature that (reported the association of the SII index with the prognosis of patients with bladder cancer, has a specific endpoint (e.g., overall survival [OS], cancer-specific survival [CSS], progression-free survival [PFS], RFS), provides available data including hazard ratios (HR) and a 95% confidence interval (CI) were included.
Review articles, case reports, expert opinions, studies not conducted on humans were excluded.
2.3. Data extraction and quality assessment
Two researchers independently performed literature screening, data extraction, and quality assessment. If the results were in dispute, a third researcher would adjudicate. Data including the first author’s name, publication year, country, cancer type, research methodology, therapy, and sample size, SII cut-off, specific endpoint, HR with 95% CI, and follow-up were extracted from the article.
Each article included was assessed by the Newcastle-Ottawa Scale,[16] for judging the quality of academic studies; the overall quality score ranged from 0 to 9, and articles with a final score >6 were deemed to have an excellent quality.
2.4. Statistical analysis
To better evaluate the influence of SII on the prognosis of bladder cancer patients, we analyzed mainly HR and 95% CI figures extracted from the articles. The Cochran Q test and Higgin I2 statistic were used to detect heterogeneity among the chosen papers. If there was heterogeneity (P < .05 or I2 > 50%), data were pooled by the random-effects model. Otherwise the fixed-effects model was adopted. In the meantime, a sensitivity assessment would also be carried out to improve the stability and reliability of the results. In addition, the Begg funnel plot was used to detect the existence of publication bias, and a P value of <.05 was considered statistically significant. Stata software version 14.0 was used for all of the analyses above.
2.5. Ethics
Since this study was a secondary literature study, no ethical review was required.
3. Results
3.1. Study characteristics
After rigorous screening (Fig. 1), we included 11 publications for 12 datasets in our meta-analysis. Table 1 lists basic characteristics of the literature collected. The total Newcastle-Ottawa Scale score of each research paper is generally 6 or greater, as is shown in Table 2. In terms of treatment, there were 9 surgical trials and 2 surgical plus immunotherapy studies. The article by Zhang and pan discusses the relationship between SII and OS in patients with bladder cancer; the article by Ke, Zhao, Li, and Wang focuses on RFS; Bi and Yamashita focus on OS and CSS; Yilmaz examines the relationship with OS/PFS; and Grossmann’s study includes OS, RFS, and CSS; Katayama’s study explores OS, RFS, CSS, and PFS. All studies, except for one, obtained cut-off values, which ranged from 276.685 to 895.95.
Figure 1.
Flow diagram of literature and selection process.
Table 1.
Main characteristics of individual studies included in the meta-analysis.
| Study, year | Country | Duration | Study design | Sample size | Age | Follow-up (mo) | Cancer type | Treatment | Cut-off | Survival outcome |
|---|---|---|---|---|---|---|---|---|---|---|
| Zhang 2019 1[17] | China | 2005–2019 | Retrospective | 139 | Median: 67 | NR | Mixed | With-surgery | 507 | OS |
| Zhang 2019 2[17] | China | 2005–2019 | Retrospective | 70 | Median: 66 | NR | Mixed | With-surgery | 507 | OS |
| Bi 2020[18] | China | 2004–2014 | Retrospective | 387 | 69.49 ± 10.84 | Median: 108 | NMIBC | With-surgery | 467.76 | OS, CSS |
| Pan 2020[19] | China | 2012–2014 | Retrospective | 113 | NR | NR | MIBC | With-surgery | 632.17 | OS |
| Yilmaz 2020[14] | Turkey | 1999–2019 | Retrospective | 152 | Median: 66 | Median: 16 | MIBC | With-surgery | 768 | OS, PFS |
| Grossmann 2021[20] | 12 countries | NR | Retrospective | 4335 | Median: 67 | Median: 42 | Mixed | With-surgery | NR | OS, RFS, CSS |
| Katayama 2021[15] | US and Europe | 1996–2007 | Retrospective | 1117 | Median: 67 | Median: 64 | NMIBC | With-surgery | 580 | OS, RFS, CSS, PFS |
| Ke 2021[21] | China | 2014–2021 | Retrospective | 184 | 61.88 ± 10.63 | Median: 15 | NMIBC | Immunotherapy | 439.8333 | RFS |
| Yamashita 2021[22] | Japan | 2009–2018 | Retrospective | 237 | Median: 73 | Median: 38 | Mixed | With-surgery | 438 | OS, CSS |
| Zhao 2021[23] | China | 2013–2018 | Retrospective | 216 | Median: 59 | Mean: 59.41 | NMIBC | With-surgery | 276.685 | RFS |
| Li 2022[24] | China | 2014–2017 | Retrospective | 257 | NR | Median: 63 | NMIBC | With-surgery | 340.57 | RFS |
| Wang 2022[25] | China | 2014–2020 | Retrospective | 330 | 65.74 ± 11.86 | 21.42 ± 17.23 | NMIBC | Immunotherapy | 895.95 | RFS |
CSS = cancer-specific survival, MIBC = muscle-invasive bladder cancer, NMIBC = non-muscle-invasive bladder cancer, NOS = Newcastle-Ottawa Scale, NR = not reported, OS = overall survival, PFS = progression-free survival, RFS = recurrence-free survival.
Table 2.
Newcastle-Ottawa quality assessments scale.
| Studies | Selection | Comparability | Outcome | Scores | |||||
|---|---|---|---|---|---|---|---|---|---|
| 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | ||
| Zhang 2019 (1) | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | 8 | |
| Zhang 2019 (2) | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | 8 | |
| Bi 2020 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Pan 2020 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | 8 | |
| Yilmaz 2020 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Grossmann 2021 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Katayama 2021 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Ke 2021 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Yamashita 2021 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Zhao 2021 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Li 2022 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | ★ | 9 |
| Wang 2022 | ★ | ★ | ★ | ★ | ★★ | ★ | ★ | 8 | |
1 = representativeness of the exposed cohort, 2 = selection of the non-exposed cohort, 3 = ascertainment of exposure, 4 = outcome of interest not present at start of study, 5 = outcome of interest not present at start of study, 6 = assessment of outcome, 7 = assessment of outcome, 8 = adequacy of follow up of cohorts.
(1) and (2) represent two datasets in the same article.
3.2. Correlation between SII and OS in bladder cancer
The association between SII and OS in bladder cancer patients was investigated in 8 different trials, including 6550 patients. Due to the high heterogeneity, we calculated the pooled HR results using a random-effects model (P < .01, I2 = 79.4%), as is shown in Figure 2A. The results suggested that relatively high SII was substantially correlated with reduced OS in bladder cancer (pooled HR = 1.80; 95% CI, 1.28–2.51). Subsequent subgroup analyses disclosed that heterogeneity stemmed from regional differences, different cancer types, sample sizes <1000, and cut-off values >507. There was a remarkable connection between SII and bladder cancer prognosis in all data sets with different sample sizes (>1000: HR = 1.12, 95% CI 1.03–1.22; <1000: HR = 2.47, 95% CI 1.61–3.78). Negative correlations were also present across cut-off values (≥507: HR = 2.34, 95%CI 1.13–4.83; <507: HR = 2.10, 95%CI 1.48–2.98) and in mixed cancer types (HR = 2.03, 95%CI 1.10–3.75). Finally, an intimate relation might exist between higher SII and OS in the Chinese population (HR = 2.99, 95%CI 2.01–4.44). Table 3 summarized the detailed findings of the subgroup analysis.
Figure 2.
Forest plot of survival outcomes for bladder cancer. (A) OS for individual studies. (B) RFS for individual studies. (C) CSS for individual studies. (D) PFS for individual studies. CSS = cancer-specific survival, OS = overall survival, PFS = progression-free survival, RFS = recurrence-free survival.
Table 3.
Results of subgroup analysis of OS.
| Subgroup | No. of studies | HR (95% CI) | P | Heterogeneity | Model | |
|---|---|---|---|---|---|---|
| I2 (%) | Ph | |||||
| Cancer type | ||||||
| Mixed | 4 | 2.03 (1.10–3.75) | .23 | 81 | 0.01 | Random |
| NMIBC | 2 | 1.42 (0.72–2.82) | .315 | 81.2 | 0.021 | Random |
| MIBC | 2 | 2.73 (0.54–13.77) | .224 | 88.2 | 0.004 | Random |
| Country | ||||||
| China | 4 | 2.99 (2.01–4.44) | <.001 | 39.4 | 0.175 | Fixed |
| Non-China | 4 | 1.23 (0.98–1.55) | .074 | 59.4 | 0.06 | Random |
| Sample size | ||||||
| >1000 | 2 | 1.12 (1.03–1.22) | .007 | 0 | 0.561 | Fixed |
| <1000 | 6 | 2.47 (1.61–3.78) | <.001 | 52.9 | 0.059 | Random |
| Cut-off | ||||||
| ≥507 | 5 | 2.34 (1.13–4.83) | .022 | 81.5 | <0.001 | Random |
| <507 | 2 | 2.10 (1.48–2.98) | <.001 | 0 | 0.996 | Fixed |
| NR | 1 | 1.13 (1.03–1.23) | .006 | – | – | – |
| NOS | ||||||
| 8 | 3 | 4.56 (2.53–8.2) | <.001 | 0 | 0.515 | Fixed |
| 9 | 5 | 1.35 (1.04–1.74) | .021 | 67.3 | 0.016 | Random |
95% CI = 95% confidence interval, HR = hazard ratio, MIBC = muscle invasive bladder cancer, NOS = Newcastle-Ottawa Scale, NMIBC = non-muscle invasive bladder cancer, NR = not reported, OS = overall survival.
3.3. Correlation between SII and RFS in bladder cancer
Six groups of studies involving 6439 patients reported the predictive effect of SII on bladder cancer patients’ RFS. High heterogeneity of the pooled results (P < .01, I2 = 86.8%) was observed, which implied a notably close relationship between RII and bladder cancer patients’ RFS (pooled HR = 1.73; 95% CI, 1.26–2.39) (Fig. 2B). Subsequent subgroup analyses (Table 4) indicated that differences in regions, treatment protocols, sample sizes, and cut-off values were possibly accountable for potential heterogeneity, but statistical significance regardless of regions and sample sizes had a cut-off value of < 507. In patients undergoing surgery alone, SII had a higher predictive value (HR = 1.38, 95% CI 1.07–1.77).
Table 4.
Results of subgroup analysis of RFS.
| Subgroup | No. of studies | HR (95% CI) | P | Heterogeneity | Model | |
|---|---|---|---|---|---|---|
| I2 (%) | Ph | |||||
| Treatment | ||||||
| With-surgery | 4 | 1.38 (1.07–1.77) | .012 | 69.5 | 0.02 | Random |
| Immunotherapy | 2 | 2.55 (0.75–8.66) | .134 | 94.1 | <0.001 | Random |
| Country | ||||||
| China | 4 | 2.34 (1.32–4.16) | .004 | 82.6 | 0.001 | Random |
| Non-China | 2 | 1.15 (1.05–1.26) | .003 | 0 | 0.468 | Fixed |
| Sample size | ||||||
| >1000 | 2 | 1.15 (1.05–1.26) | .003 | 0 | 0.468 | Fixed |
| <1000 | 4 | 2.34 (1.32–4.16) | .004 | 82.6 | 0.001 | Random |
| Cuf-off | ||||||
| ≥507 | 2 | 2.39 (0.62–9.16) | .204 | 95.7 | <0.001 | Random |
| <507 | 3 | 1.63 (1.28–2.07) | <.001 | 37.4 | 0.202 | Fixed |
| NR | 1 | 1.13 (1.02–1.26) | .025 | – | – | – |
| NOS | ||||||
| 8 | 1 | 4.85 (2.89–8.14) | <.001 | – | – | – |
| 9 | 5 | 1.36 (1.11–1.66) | .003 | 63 | 0.029 | Random |
95% CI = 95% confidence interval, HR = hazard ratio, NOS = Newcastle-Ottawa Scale, NR = not reported, RFS = recurrence-free survival.
3.4. Correlation between SII and CSS/PFS in bladder cancer
Figure 2C and D outlines the predictive effect of SII on CSS/PFS in bladder cancer patients. According to the pooled results obtained using the random-effects model, SII was significantly associated with CSS in bladder cancer patients (pooled HR = 1.68; 95% CI, 1.14–2.47). Similar findings were obtained for the relationship of SII and PFS in bladder cancer patients from the pooled outcomes of the fixed-effects model.
3.5. Sensitivity analysis
Due to significant heterogeneity among the included studies, we excluded individual data sets one by one while performing sensitivity analyses of the results of relevance between SII and OS/RFS. Detailed steps are introduced in Figure 3A and B. It can be concluded that the pooled results were stable.
Figure 3.
Sensitivity analysis of each included study. (A) OS for individual studies. (B) RFS for individual studies. OS = overall survival, RFS = recurrence-free survival.
3.6. Publication bias
The P values for the Berger test regarding OS/RFS were .174 and .60, respectively. Their funnel plot was symmetrical (Fig. 3A,B), indicating that no significant publication bias was found.
4. Discussion
The association between SII and prognosis of patients with different kinds of cancers has been extensively studied previously. In 2017, Zhong et al[26] observed a connection between high levels of SII and a poor prognosis in patients with solid tumors, and they marked this as a novel prognostic signal for patients with reactive malignancies. In 2019, a predictive value of preconditioning SII for patients with non-small cell lung cancer was testified by Wang et al,[27] Similar conclusions are also supported by Zhang et al.[28] Wang backed the advice of immunotherapy for patients with high SII. In 2021, Shui discovered that SII was connected with short- and long-term poor prognosis in pancreatic cancer patients.[9] In patients with hepatocellular carcinoma, similar conclusions were reached by Wang et al.[29] Besides, it was proven by Li that SII was also proven to be an independent predictor of poor prognosis in patients with urologic malignancies.[30] Patients undergoing radical nephrectomy with a high preoperative SII level had substantially lower OS, PFS, and CSS rates than those with a lower SII level, according to Zheng (all P < .05).[31] Previous meta-analyses have argued the relationship between prognosis and RII in urological tumors; however, the size of samples included in the subgroup of bladder cancer was too small to be convincing, so we updated this meta-analysis in the field of bladder cancer. Our statistical analysis disclosed a significant association between elevated pretreatment SII levels and poorer survival outcomes (including OS, PFS, RFS and CSS) in patients with bladder cancer.
Following long-term research of tumor recurrence and prognosis of humans, it is commonly assumed that inflammatory factors in the host play a role in tumor formation. It is well known that neutrophils are the natural immune defense mobilized by the body in case of infection. Studies have established that neutrophils in cancer patients can promote tumor neovascularization and distant dissemination by releasing cytokines such as OSM, TGF-β, HGF, and CXCL8.[32] Similarly, platelets may also facilitate the development of cancer. As is well known, a hypercoagulable state is one of the common manifestations of cancer. On the one hand, platelets encourage tumor progression by secreting multiple chemokines and cytokines.[33] On the other hand, platelets protect tumor cells from tumor necrosis factor α and natural killer cells through the GP receptor and tumor cell integrin α vβ-mediated pathway.[34] Therefore, platelets are closely related to the growth of tumor tissue. Lymphocytes can also influence the host immune response to malignant tumors. In the study of Hanahan et al,[35] lymphocytes had tumor defense effects as they activated the host immune response and participated in cancer immunosurveillance and immune clearance. To some extent, a decrease in lymphocytes predicts a reduction in the survival of cancer patients. Composed of neutrophils, platelets, and lymphocytes, SII is easy to acquire and simple to calculate. Having attracted much attention in recent years, SII has great potential in future clinical work. Although there is no clear explanation for how SII affects bladder cancer prognosis, the real mechanism can still be inferred from previous studies. Our meta-analysis included 11 articles, and a significant association was observed between elevated pretreatment SII levels and poorer survival outcomes (including OS, PFS, RFS and CSS) in patients with bladder cancer.
The greatest significance of this study is that it can be used by clinicians as an adjunctive marker to assess the prognosis of patients with bladder cancer, allowing for more accurate risk stratification and more precise treatment planning for patients with bladder cancer, such as the timing of radical cystectomy and the choice of whether to adjuvant therapy.
However, the current study still has limitations. First, all the studies we included were retrospective, which could lead to potential flaws and bias of the original data; second, most of the studies originated from China, and the regional richness of the samples might be relatively insufficient; third, due to the existence of differences in sample characteristics and treatment modalities, disagreements existed on the selection of cut-off values for SII in the studies; finally, publication bias could not be completely eliminated. Therefore, further improvements are needed in the follow-up study.
5. Conclusions
Our study results suggest an intimate correlation between higher SII levels and a worse prognosis in bladder cancer patients. Therefore, we can speculate that SII may be an independent factor for predicting bladder cancer prognosis. Our findings can provide clinicians with guidance on patients’ condition assessment and the development of further diagnosis and treatment plans. However, the study results are not sound enough in view of small sample sizes, and further research is warranted.
Author contributions
Conceptualization: Wei Cao, Shangzhang Zou, Jinguo Wang.
Methodology: Wei Cao, Na Wang, Yifeng Shao, Jinguo Wang
Software: Yifeng Shao, Na Wang
Supervision: Wei Cao, Jinguo Wang.
Visualization: Wei Cao
Writing – original draft: Wei Cao, Yifeng Shao.
Writing – review & editing: Wei Cao, Yifeng Shao, Shangzhang Zou.
Abbreviations:
- 95% CIs =
- 95% confidence intervals
- CSS =
- cancer-specific survival
- HRs =
- hazard ratio
- NMIBC =
- non-muscle invasive bladder cancer
- OS =
- overall survival
- PFS =
- progression-free survival
- RFS =
- recurrence-free survival
- SII =
- Systemic Immune-Inflammation Index
The authors have no conflicts of interest to disclose.
The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.
How to cite this article: Cao W, Shao Y, Zou S, Wang N, Wang J. Prognostic significance of systemic immune-inflammation index in patients with bladder cancer: A systematic review and meta-analysis. Medicine 2022;101:36(e30380).
Contributor Information
Wei Cao, Email: caoway@foxmail.com.
Yifeng Shao, Email: 740427713@qq.com.
Shangzhang Zou, Email: 760916287@qq.com.
Na Wang, Email: jinguo@jlu.edu.cn.
References
- [1].Siegel RL, Miller KD, Fuchs HE, et al. Cancer statistics, 2022. CA Cancer J Clin. 2022;72:7–33. [DOI] [PubMed] [Google Scholar]
- [2].Ritch CR, Velasquez MC, Kwon D, et al. Use and validation of the AUA/SUO risk grouping for nonmuscle invasive bladder cancer in a contemporary cohort. J Urol. 2020;203:505–11. [DOI] [PubMed] [Google Scholar]
- [3].Lenis AT, Lec PM, Chamie K, et al. Bladder cancer: a review. JAMA. 2020;324:1980–91. [DOI] [PubMed] [Google Scholar]
- [4].Hanahan D, Coussens LM. Accessories to the crime: functions of cells recruited to the tumor microenvironment. Cancer Cell. 2012;21:309–22. [DOI] [PubMed] [Google Scholar]
- [5].Fridman WH, Pagès F, Sautès-Fridman C, et al. The immune contexture in human tumours: impact on clinical outcome. Nat Rev Cancer. 2012;12:298–306. [DOI] [PubMed] [Google Scholar]
- [6].Zhang Y, Wang Y, Wang J, et al. The immune cell infiltration patterns and characterization score in bladder cancer to identify prognosis. Front Genet. 2022;13:852708. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [7].Xylinas E, Kent M, Kluth L, et al. Accuracy of the EORTC risk tables and of the CUETO scoring model to predict outcomes in non-muscle-invasive urothelial carcinoma of the bladder. Br J Cancer. 2013;109:1460–6. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [8].Masson-Lecomte A, Rava M, Real FX, et al. Inflammatory biomarkers and bladder cancer prognosis: a systematic review. Eur Urol. 2014;66:1078–91. [DOI] [PubMed] [Google Scholar]
- [9].Shui Y, Li M, Su J, et al. Prognostic and clinicopathological significance of systemic immune-inflammation index in pancreatic cancer: a meta-analysis of 2,365 patients. Aging. 2021;13:20585–97. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [10].Jiang Y, Xu D, Song H, et al. Inflammation and nutrition-based biomarkers in the prognosis of oesophageal cancer: a systematic review and meta-analysis. BMJ Open. 2021;11:e048324. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [11].Ji Y, Wang H. Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis. World J Surg Oncol. 2020;18:197. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [12].Wang Q. Prognostic value of systemic immune-inflammation index in patients with urinary system cancers: a meta-analysis. Eur Rev Med Pharmacol Sci. 2021;25:1302–10. [DOI] [PubMed] [Google Scholar]
- [13].Li X, Gu L, Chen Y, et al. Systemic immune-inflammation index is a promising non-invasive biomarker for predicting the survival of urinary system cancers: a systematic review and meta-analysis. Ann Med. 2021;53:1827–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [14].Yilmaz A, Yilmaz H, Tekin SB, et al. The prognostic significance of hemoglobin-to-red cell distribution width ratio in muscle-invasive bladder cancer. Biomark Med. 2020;14:727–38. [DOI] [PubMed] [Google Scholar]
- [15].Katayama S, Mori K, Pradere B, et al. Prognostic value of the systemic immune-inflammation index in non-muscle invasive bladder cancer. World J Urol. 2021;39:4355–61. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [16].Stang A. Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol. 2010;25:603–5. [DOI] [PubMed] [Google Scholar]
- [17].Zhang W, Wang R, Ma W, et al. Systemic immune-inflammation index predicts prognosis of bladder cancer patients after radical cystectomy. Ann Transl Med. 2019;7:431. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [18].Bi H, Shang Z, Jia C, et al. Predictive values of preoperative prognostic nutritional index and systemic immune-inflammation index for long-term survival in high-risk non-muscle-invasive bladder cancer patients: a single-centre retrospective study. Cancer Manag Res. 2020;12:9471–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [19].Pan Z-B, Cheng W-S, Cai H-R, et al. Correlation between preoperative systemic immune inflammatory index and prognosis of muscle-infiltrating bladder cancer. Gen Med Clin Educ. 2020;18:506–9. [Google Scholar]
- [20].Grossmann NC, Schuettfort VM, Pradere B, et al. Impact of preoperative systemic immune-inflammation Index on oncologic outcomes in bladder cancer patients treated with radical cystectomy. Urol Oncol Semin Orig Investig. 2022;40:106.e11–9. [DOI] [PubMed] [Google Scholar]
- [21].Ke ZB, Chen H, Chen JY, et al. Preoperative abdominal fat distribution and systemic immune inflammation were associated with response to intravesical Bacillus Calmette-Guerin immunotherapy in patients with non-muscle invasive bladder cancer. Clin Nutr. 2021;40:5792–801. [DOI] [PubMed] [Google Scholar]
- [22].Yamashita S, Iwahashi Y, Miyai H, et al. Usefulness of preoperative high systemic immune-inflammation index as a prognostic biomarker in patients who undergo radical cystectomy for bladder cancer: multicenter analysis. Diagnostics. 2021;11:2194. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [23].Zhao R, Shan J, Nie L, et al. The predictive value of the ratio of the product of neutrophils and hemoglobin to lymphocytes in non-muscular invasive bladder cancer patients with postoperative recurrence. J Clin Lab Anal. 2021;35:e23883. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [24].Li P, Wang Bowen Y, Hong X, et al. Prognostic value of preoperative systemic immunoinflammatory index in assessing the prognosis of non-muscle invasive bladder cancer. Basic Clin Oncol. 2022;35:23–7. [Google Scholar]
- [25].Wang Z, Chen Y, Liu J, et al. Systemic immune-inflammation index holds high prognostic value in patients undergoing Bacillus Calmette-Guerin -immunotherapy for bladder cancer. Asian J Surg. 2022;45:744–5. [DOI] [PubMed] [Google Scholar]
- [26].Zhong JH, Huang DH, Chen ZY. Prognostic role of systemic immune-inflammation index in solid tumors: a systematic review and meta-analysis. Oncotarget. 2017;8:75381–8. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [27].Wang Y, Li Y, Chen P, et al. Prognostic value of the pretreatment systemic immune-inflammation index (SII) in patients with non-small cell lung cancer: a meta-analysis. Ann Transl Med. 2019;7:433. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [28].Zhang Y, Chen B, Wang L, et al. Systemic immune-inflammation index is a promising noninvasive marker to predict survival of lung cancer. Medicine (Baltim). 2019;98:e13788. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [29].Wang B, Huang Y, Lin T. Prognostic impact of elevated pre-treatment systemic immune-inflammation index (SII) in hepatocellular carcinoma. Medicine (Baltim). 2020;99:e18571. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [30].Li X, Gu L, Chen Y, et al. Systemic immune-inflammation index is a promising non-invasive biomarker for predicting the survival of urinary system cancers: a systematic review and meta-analysis. Ann Med. 2021;53:1827–38. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [31].Zheng Y, Yu D, Yu Z, et al. Association of preoperative systemic immune-inflammation index and prognostic nutritional index with survival in patients with upper tract urothelial carcinoma. J Cancer. 2020;11:5665–77. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [32].Tecchio C, Scapini P, Pizzolo G, et al. On the cytokines produced by human neutrophils in tumors. Semin Cancer Biol. 2013;23:159–70. [DOI] [PubMed] [Google Scholar]
- [33].Kusumanto YH, Dam WA, Hospers GAP, et al. Platelets and granulocytes, in particular the neutrophils, form important compartments for circulating vascular endothelial growth factor. Angiogenesis. 2003;6:283–7. [DOI] [PubMed] [Google Scholar]
- [34].Haemmerle M, Stone RL, Menter DG, et al. The platelet lifeline to cancer: challenges and opportunities. Cancer Cell. 2018;33:965–83. [DOI] [PMC free article] [PubMed] [Google Scholar]
- [35].Hanahan D, Weinberg RA. Hallmarks of cancer: the next generation. Cell. 2011;144:646–74. [DOI] [PubMed] [Google Scholar]