The Prognostic Prediction Value of Systemic Inflammation Score and the Development of a Nomogram for Patients With Surgically Treated Breast Cancer

Abstract

Background: Systemic inflammation score (SIS) has been verified as a novel prognostic indicator in several cancer types. However, its prognostic value in breast cancer remains unknown. Furthermore, a nomogram based on SIS is yet to be constructed for breast cancer. We conducted this study to explore the association between SIS and prognosis of breast cancer, and to construct a good prognostic nomogram model. Methods: A total of 1,180 breast cancer patients who underwent curative surgery between December 2010 and January 2013 were recruited. They were randomly assigned to the training set (n = 944) or the validation set (n = 236). All patient blood samples were collected within 1 week prior to operation. According to previous reports, SIS was calculated for all patients, who were then classified into two groups: high-SIS and low-SIS. The Kaplan-Meier method was employed for survival analyses, and univariate and multivariate analyses (Cox proportional hazards regression model) were used for prognostic assessment. A nomogram was constructed based on the results of multivariate analysis. Calibration curves and concordance index (C-index) were compiled to determine predictive and discriminatory capacity.Results: In the training set, the median follow-up time was 6.07 years. Patients in the high-SIS group had an average OS time of 68.05 months, which is shorter than that of the low-SIS group (72.87 months; P = 0.033). Patients in the high-SIS group had average RFS and DMFS times of 56.04 and 54.46 months, respectively, which are shorter than those of the low-SIS group (60.85 and 59.47 months, respectively; P = 0.247 and P = 0.032). Univariate and multivariate analyses revealed SIS to be an independent prognostic factor for OS and DMFS time. The nomogram for the training set indicated OS and DMFS C-indexes of 0.794 (95% CI, 0.772-0.816) and 0.712 (95% CI, 0.684-0.740), respectively.In the validation set, the OS and DMFS C-indexes were 0.889 (95% CI, 0.845-0.933) and 0.696 (95%. CI, 0.611-0.781), respectively.Conclusions: SIS was confirmed as an independent prognostic predictor among patients with breast cancer who had undergone surgery with curative intent. Higher preoperative SIS may indicate higher risk of metastasis and shorter overall survival time. The prognostic nomogram based on SIS was dependable for breast cancer patients who underwent curative surgery.

A Novel Inflammatory-Nutritional Prognostic Scoring System for Patients with Early-Stage Breast Cancer

“… 11 , 37 As mediators of inflammatory response, inflammatory cells play a very important part in tumor microenvironment (TME), 36 and circulating inflammatory-nutritional biomarkers, including PLR, NLR, MLR, CONUT, SIS, SIRI, SII, and AAPR, are significantly associated with survival and have been considered as independent predictors for breast cancer patients. 16–18 , 21 , 23 , 26 Over the past few years, optimal predictors or prognostic models based on one or a few inflammatory-nutritional biomarkers for women with breast cancer have been explored extensively, but they have limited clinical value because the weight values of individual inflammatory biomarkers to the risk score are not equal. For example, a high NLR is usually considered as an indicator of a poor prognosis, 19 , 38 but NLR failed to show independent value in the multivariate Cox analysis in other studies when identifying patients with a pathological complete response or achievement of disease-free status.…”

“…Integration of multiple biomarkers could provide prognostic models with substantially higher predictive accuracy than that achieved with models based on one or a few inflammatory biomarkers. 12 , 21 , 37 But most of current studies simply combined candidate inflammatory parameters with strong collinearity and correlation into a multivariate Cox regression model to identify independent predictors, which can lead to conflict between parameters and certain statistical problems. 12 In this study, we performed the LASSO Cox regression analysis to include the maximal number of available inflammatory-nutritional biomarkers and effectively single out four valuable inflammatory indexes, namely, NLR, MLR, PNI, and AAPR; this approach could avoid the influence of multicollinearity to some extent.…”

“…These three variable scores were stratified into four levels ( Supplementary Table 1 ), and the best cutoff value of 2 for CONUT was decided per our previous study. 16 , 32 Similarly, SIS was calculated integrating serum albumin concentrations and LMR according to our previous study, 21 patients with both hypoalbuminemia (<40 gL−1) and low LMR (<4.44) were scored as 2; patients with either hypoalbuminemia (<40 gL−1) or low LMR (<4.44) were scored as 1; patients with hyperalbuminemia (≥40 gL−1) and LMR ≥ 4.44 were scored as 0. A cutoff value of 1 of SIS was also determined following this study.…”

“…[12][13][14][15] In terms of breast cancer, several studies have shown that inflammatory-nutritional indexes, including the platelet-lymphocyte ratio (PLR), systemic inflammation score (SIS), neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), Controlling Nutritional Status (CONUT), and systemic immune-inflammation index (SII), are markedly associated with survival outcomes. [16][17][18][19][20][21] Qi et al first recognized the system inflammation response index (SIRI) as a predictor for pancreatic cancer. The prognostic value of this index in patients with breast cancer was also explored in our previous study.…”

A Systemic Inflammation Response Score for Prognostic Prediction of Breast Cancer Patients Undergoing Surgery

“…Among the prognostic models that included blood markers, Cho et al conducted a small sample study and only verified the role of PLR, but failed to include important factors that have been confirmed, such as LMR, NLR, NMR and ALB [ 31 ]. Huang et al reported that the systemic inflammation score (SIS) based on ALB and LMR could predict the survival of breast cancer patients [ 32 ]. Zheng et al found that fibrinogen-albumin ratio and platelet-lymphocyte ratio score was a prognostic factor of breast cancer [ 33 ], and NLR has been shown to predict the efficacy of neoadjuvant chemotherapy in breast cancer [ 34 , 35 ].…”