Prognostic Value of Preoperative Systemic Immune-Inflammation Index in Patients with Cervical Cancer

Huang, Huaping; Liu, Qin; Zhu, Lixia; Zhang, Yan; Lu, Xiaobo; Wu, Yue; Liu, Li

doi:10.1038/s41598-019-39150-0

Cited by 231 publications

(225 citation statements)

References 37 publications

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“…No additional records were identified through manual searching. Finally, 9 published articles involving 2724 patients were included in this meta-analysis [11][12][13][14][15][16][20][21][22]. Among these 9 studies, two [11,14] contained the training and validation cohorts from different hospitals, and thus, 11 datasets were totally used for statistical analysis (Table 1).…”

Section: Study Characteristicsmentioning

confidence: 99%

“…Multivariate analysis proved that increased SII correlated with poor OS (Liu et al: HR = 2.60, 95% CI = 1.74-3.88; P < 0.001 [12]; Wang et al: HR = 2.96, 95% CI = 2.18-3.98; P < 0.00 1 [13]) and DFS (Liu et al: HR = 1.46, 95% CI = 1.01-2.12; P = 0.045 [12]; Wang et al: HR = 2.85, 95% CI = 1.62-3.81; P = 0.005 [13]) in patients with triple-negative breast cancer. Using primary (HR = 2.53, 95% CI = 1.32-4.83; P = 0.005) and validation (HR = 3.99, 95% CI = 1.388-11.47; P = 0.010) cohorts, the study of Huang et al supported that SII was an independent risk factor for prediction of OS in cervical cancer patients [14]. Furthermore, receiver operating characteristics curve analysis suggested that the prognostic accuracy of SII for 5-year OS in patients with cervical cancer was even higher than NLR [area under the curves (AUC): 0.64 vs 0.59, primary; 0.64 vs 0.59, validation] or PLR (AUC: 0.64 vs 0.60, primary; 0.64 vs 0.60, validation) [14], indicating SII may represent a promising biomarker for predicting survival of gynecological cancer patients clinically.…”

Section: Introductionmentioning

confidence: 95%

“…Using primary (HR = 2.53, 95% CI = 1.32-4.83; P = 0.005) and validation (HR = 3.99, 95% CI = 1.388-11.47; P = 0.010) cohorts, the study of Huang et al supported that SII was an independent risk factor for prediction of OS in cervical cancer patients [14]. Furthermore, receiver operating characteristics curve analysis suggested that the prognostic accuracy of SII for 5-year OS in patients with cervical cancer was even higher than NLR [area under the curves (AUC): 0.64 vs 0.59, primary; 0.64 vs 0.59, validation] or PLR (AUC: 0.64 vs 0.60, primary; 0.64 vs 0.60, validation) [14], indicating SII may represent a promising biomarker for predicting survival of gynecological cancer patients clinically. However, the associations between SII and clinical outcomes of gynecological and breast cancer patients were found to be nonsignificant in some other studies [15,16].…”

Section: Introductionmentioning

confidence: 95%

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Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis

Wang

2020

World J Surg Onc

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Background: Systemic immune-inflammation index (SII) has been suggested to be effective to reflect the inflammatory status and thus may be an underlying biomarker for prognosis prediction. This hypothesis has been demonstrated in meta-analyses on several cancer types. However, there was no study to confirm the prognostic roles of SII for gynecological and breast cancers, which was the goal of our study. Methods: PubMed, EMBASE, and Cochrane Library databases were searched to collect the articles exploring the associations of SII with prognostic outcomes [overall survival (OS), disease-free survival (DFS), progressionfree survival (PFS), lymph node metastasis (LNM), and lymphovascular invasion (LVI)] in gynecological and breast cancers. The prognostic value of SII was estimated by hazard ratio (HR) or relative risk (RR) with 95% confidence interval (CI). Results: Nine articles involving 2724 patients in 11 datasets were included. Meta-analysis showed that a high SII index was significantly associated with poor OS (HR = 2.12, 95% CI, 1.61-2.79, P < 0.001), DFS/PFS (HR = 2.28, 95% CI 1.52-3.41, P < 0.001) and an increased risk for LNM (RR = 1.34, 95% CI 1.20-1.50, P < 0.001) in patients with gynecological and breast cancers. Subgroup analysis confirmed the prognostic role of SII for OS was applicable to all cancer types, but the association with DFS/PFS and LNM was only significant for ovarian cancer and breast cancer, especially triple-negative breast cancer. No significant association was detected between SII and LVI. Conclusion: High SII may be a promising indicator for the prediction of poor prognosis in patients with gynecological and breast cancers, especially ovarian cancer and triple-negative breast cancer.

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Section: Study Characteristicsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 95%

Section: Introductionmentioning

confidence: 95%

See 1 more Smart Citation

Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis

Wang

2020

World J Surg Onc

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“…Among them, one concerning cervical cancer was disposed separately cause of providing HRs and survival outcomes for patients with two different treatments [21]. As a consequence, fifteen, nine, and four publications regarding to cervical [19,[21][22][23][24][25][26][27][28][29][30][31][32][33][34], ovarian [35][36][37][38][39][40][41][42][43], and endometrial cancer [44][45][46][47] were enrolled, respectively.…”

Section: Literature Search Results and Characteristicsmentioning

confidence: 99%

Prognostic function of platelet-to-lymphocyte ratio in gynecologic cancers: A systematic review and meta-analysis

Fan

Dai

Wang

et al. 2019

Preprint

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Background: Although along with the diagnosis and treatment level enhanced, current situation of the gynecologic malignancies improved, the risk of gynecologic tumor remains high. Nowadays, inflammatory markers increasingly employed as a tumor predictive factor. Herein, we focused on the association between the platelet-to-lymphocyte ratio (PLR) and gynecological cancers, including cervical, ovarian, and endometrial cancer. Methods: In this meta-analysis, we searched systematically on the EMBASE and PubMed databases from June 1, 1989 to May 31, 2019. After excluded some unqualified articles, we calculated the pooled hazard ratio (HR) with 95% confidence interval (CI) mainly to detect the relationship between PLR and prognostic survival, including overall survival (OS) and progression-free survival (PFS). Random-effect model was adopted when I 2 >50% after Higgins I 2 test. Subgroup analysis and funnel plot were used to seek for the possible source of heterogeneity and publication bias, respectively. All statistical tests were two-sided. Results: After a series of searching and selection, twenty-eight literatures containing 8290 participants totally. Among those recruited trials, 26 studies comprising 8109 patients reported HR for OS and 15 researches enrolled 4283 patients for PFS. Overall, a high value of PLR means a worse OS and PFS in women with gynecologic cancer except those with endometrial cancer for OS (pooled HR =1.35, 95% CI =0.73 to 2.53, P =0.33). Subgroup analyses indicated that the source of heterogeneity may be primarily from the sample size, PLR cut-off, study location, published year, and the cut-off year for the study. Publication bias manifested that bias was not evident. Conclusion: Elevated pretreatment PLR portends a poor prognosis among patients with gynecological tumor, as well as in women with cervical and ovarian malignancies for both OS and PFS. However, in patients with endometrial cancer, this connection is broken for OS but still available for PFS.

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“…Consequently, several immune scoring systems were developed based on the immune-related gene expression patterns through integrated analysis of The Cancer Genome Atlas (TCGA) database to explore the relationships between tumor cells and immunocytes in TME, as well as to quantify the immune microenvironment for each individual cancer case. Of them, the in ammation-based index was reported to be associated with the local immune response and prognosis in various cancers, including pancreatic cancer, colorectal cancer [15], non-small cell lung cancer [16] and tongue cancer [17] and so on. However, limited studies have been designed in an attempt to develop an immune-related prognostic signature for EC.…”

Section: Introductionmentioning

confidence: 99%

Bioinformatic Profiling Identifies Prognosis-Related Genes in the Immune Microenvironment of Endometrial Carcinoma

Cheng

Zheng

et al. 2020

Preprint

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Background: Endometrial carcinoma (EC) is a common malignancy of female genital system which exhibits a unique immune profile. It is a promising strategy to quantify immune patterns of EC for predicting prognosis and therapeutic efficiency. Here, we attempted to identify the possible immune microenvironment-related prognostic markers of EC. Methods: We obtained the RNA sequencing and corresponding clinical data of EC from TCGA database. Then, 3 immune scores based on the Estimation of STromal and immune cells in MAlignant Tumor tissues using Expression data (ESTIMATE) algorithm were computed. Correlation between above ESTIMATE scores and other immune-related scores, molecular subtypes, prognosis, and gene mutation status (including BRCA and TP53) were further analyzed. Afterwards, gene modules associated with the ESTIMATE scores were screened out through hierarchical clustering analysis and WGCNA. Differentially expressed analysis was performed and genes shared by the most relevant modules were found out. KEGG pathway enrichment analysis was conducted to explore the biological functions of those genes. Survival analysis was carried out to identify prognostic immune-related genes and GSE17025 database was used as external dataset for further validation.Results: The immune-related scores based on ESTIMATE algorithm was closely related to the immune microenvironment of EC. 3 gene modules that had the closest correlations with 3 ESTIMATE scores were obtained. 109 immune-related genes were preliminarily found out and 29 pathways were significantly enriched, most of which were associated with immune response. Univariate survival analysis revealed that there were 14 genes positively associated wicth both OS and PFS. Among which, 11 genes showed marked correlations with ImmuneScore values in GSE17025 database.Conclusion: Our current study profiled the immune status and identified 14 novel immune-related prognostic biomarkers for EC. Our findings may help to investigate the complicated tumor microenvironment and develop novel individualized therapeutic targets for EC.

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Prognostic Value of Preoperative Systemic Immune-Inflammation Index in Patients with Cervical Cancer

Cited by 231 publications

References 37 publications

Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis

Prognostic prediction of systemic immune-inflammation index for patients with gynecological and breast cancers: a meta-analysis

Prognostic function of platelet-to-lymphocyte ratio in gynecologic cancers: A systematic review and meta-analysis

Bioinformatic Profiling Identifies Prognosis-Related Genes in the Immune Microenvironment of Endometrial Carcinoma

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