Systemic Inflammatory Score predicts Overall Survival in patients with Cervical Cancer

Abstract

Background: To evaluate the prognostic value of the systemic inflammatory score (SIS) in cervical cancer patients. Methods: A total of 264 patients with FIGO stage (2009) IB-IIA cervical cancer undergoing radical resection from January 2014 to December 2017 were recruited. The optimal cutoff values for inflammatory biomarkers were calculated by X-tile software. The prognostic factors were investigated using univariate and multivariate Cox analyses. Time-dependent receiver operating characteristic (time-ROC) analysis and the concordance index (C-index) were used to compare the prognostic impact of factors. Results: In total, 264 patients with cervical cancer were included in the study. The optimal cutoff value for lymphocyte-to-monocyte ratio (LMR) was 4.1. In multivariate analysis, FIGO stage, lymphovascular invasion, lymph node metastasis, preoperative serum albumin (Alb), and LMR were independent prognostic factors (P<0.05). Then, we combined preoperative Alb and LMR to establish the SIS. Multivariate analysis showed that the SIS was an independent factor that affected survival (P<0.05). When stratified by FIGO stage, significant differences in survival were also found for patients with different SISs (P<0.05). When the SIS and FIGO stage were combined, the time-ROC curve was superior to that of FIGO stage only. The C-index of the model combining the SIS and FIGO stage was 0.786 (95% CI 0.699-0.873), which was significantly higher than that of the model with FIGO stage only (0.676, 95% CI 0.570-0.782, P=0.0049). Conclusions:The preoperative SIS is a simple and useful prognostic factor for postoperative survival in patients with cervical cancer. It might assist in the identification of high-risk patients among patients with the same FIGO stage.

Correlation of bone marrow 2-deoxy-2-[18F]fluoro-D-glucose uptake with systemic inflammation in patients with newly diagnosed endometrial cancer

“…In the present study, no significant differences in bone marrow SUV or BLR were noted according to FIGO stage. Xu et al [21] demonstrated that higher FIGO stage was significantly correlated with higher systemic inflammatory markers in patients with cervical cancer. Inflammation can promote the development, progression and metastasis of cancer [5].…”

Prognostic value of pretreatment systemic inflammatory markers in patients with stage I endometrial cancer

“…These findings indicate that a systemic inflammatory response is a basic feature of malignancy. Moreover, previous studies reported the association between the systemic inflammatory response and the prognosis of solid tumors, including gynecologic cancer [13][14][15][16][17][18].…”

“…The neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and monocyte-lymphocyte ratio (MLR) are the currently available markers of the systemic inflammatory response [12]. These markers have been clarified to show prognostic significance in solid cancers, including gynecologic cancer [13][14][15][16][17][18]. However, the prognostic value of these ratios in patients with stage I endometrioid EC is unclear.…”

Cohort Profile: Chinese Cervical Cancer Clinical Study

“…The effect of different management on patients with specific clinical stages of cervical cancer remains controversial (12)(13)(14)(15). Prognostic factors, including tumor characteristics, medical condition, sociodemographic characteristics, lifestyle behaviors, biomarkers, diagnosis, treatment, and care, are suggested for further detailed exploration (16)(17)(18)(19)(20)(21)(22). This may provide a potential way to reduce residual disease after treatment, as well as minimize recurrence, decrease the complications, and improve survival.…”

“…The Chinese Cervical Cancer Clinical (Four-C) Study was created in 2014 with the aim of collecting clinical and prognostic information on patients diagnosed with cervical cancer in mainland China since 2004. Its research objectives currently focus on four main themes: (i) to explore the associations of therapeutic strategies with complications as well as mid-and long-term clinical outcomes, including comparative effectiveness research based on marginal structural models or propensity scores (25-27); (ii) to widely evaluate the prognostic factors of cervical cancer (such as late access to care and the influence of nutritional status) and then guide treatment as well as care options, and to precisely predict the prognosis of patients so as to develop much more effective program of personalized followup and intervention (21,22); (iii) to utilize artificial intelligence (AI) and machine learning (ML) approaches for multimodal data aggregation and multifactorial examination in order to develop a knowledge base of cervical clinical auxiliary diagnosis and prognostic prediction (28)(29)(30). What' more, as the Four-C Study relatively represents the occurrence of cervical cancer across mainland China in terms of age, geographical origin, year of diagnosis, clinical stage, gross type, and histological type, it can also serve to map the burden of cervical cancer in different districts and monitor trends in incidence of cervical cancer, which could potentially inform prevention and control strategies (31).…”