High Systemic Immune-Inflammation Index Predicts Poor Survival in Patients with Human Epidermal Growth Factor Receptor-2 Positive Breast Cancer Receiving Adjuvant Trastuzumab

Systemic immune-inflammation index as a prognostic marker in HER2-positive breast cancer patients undergoing trastuzumab therapy

The prognostic value of SII (Systemic Immune-Inflammation Index) in HER-2-positive breast cancer (BC) patients, regardless of whether they receive trastuzumab treatment, and its potential value to distinguish patients who may benefit from trastuzumab therapy, warrant further investigation. Clinical data was collected from 797 HER-2-positive BC patients between July 2013 and March 2018. Baseline data differences were adjusted with propensity score matching. Univariate and multivariate analyses explored the correlation between clinical pathological factors, SII, and DFS. Four groups were established. Based on the baseline SII values of the participants, patients who did not receive trastuzumab treatment were divided into Group 1 (Low-SII) and Group 2 (High-SII), where SII had no predictive value for prognosis between groups. Participants who received trastuzumab treatment were also divided into two groups: the Low-SII group (Group 3) and the High-SII group (Group 4). The 5-year DFS was significantly higher in Group 3 than in Group 4 (91.76% vs. 82.76%, P = 0.017). Furthermore, multivariate analysis demonstrated a significant association between high SII and shorter DFS (HR = 3.430, 95% CI = 1.830-6.420, P < 0.001). In HER-2-positive BC patients treated with trastuzumab, those with lower SII showed a longer DFS, suggesting that SII may help in identifying patients who benefit from trastuzumab therapy.

Peripheral blood inflammatory indexes in breast cancer: A review

Immune and inflammatory responses play an important role in tumorigenesis and metastasis. Inflammation is an important component of the tumor microenvironment, and the changes in inflammatory cells may affect the occurrence and development of tumors. Complete blood count at the time of diagnosis and treatment can reflect the inflammatory status within the tumor. Studies have shown that the number of certain inflammatory cells in peripheral blood and their ratios are important prognostic factors for many malignancies, including neutrophil, lymphocyte, monocyte, and platelet counts, as well as neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, systemic immune-inflammation index, systemic inflammation response index and pan-immune-inflammation-value. The value of peripheral blood inflammation indexes in predicting the efficacy and prognosis of breast cancer neoadjuvant therapy is worth recognizing. This review details the application of peripheral blood inflammation indexes in the evaluation of efficacy and prediction of prognosis in neoadjuvant therapy for breast cancer, aiming to provide a more comprehensive reference for the comprehensive diagnosis and treatment of breast cancer.

Predictive Significance of Systemic Immune-Inflammation Index in Patients with Breast Cancer: A Retrospective Cohort Study

Background

Peripheral blood inflammation indices, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), have become research hotspots in the diagnosis, treatment, and prognosis prediction of breast cancer, whereas existing research findings remain controversial.

Methods

Data pertaining to 1808 breast cancer patients were collected retrospectively to analyze the predictive value of NLR/PLR/SII for breast cancer clinicopathological characteristics, chemotherapy response, and relapse. 1489, 258, and 53 eligible breast cancer patients entered into the three analyses, respectively. Logistic regression analyses were used to assess the correlation between these indices and poor response to chemotherapy. A predictive scoring model was established to predict chemotherapeutic responses based upon the odds ratio values of significant variables identified in logistic regression analyses.

Results

Higher pretherapeutic NLR/PLR/SII values were significantly correlated with higher tumor stage, triple-negative breast cancer, premenopausal status, and younger age. Logistic regression analyses indicated that pretherapeutic high SII (as a continuous variable or with a cut-off value of 586.40) and HER2-negative status were independent predictors of poor response to neoadjuvant chemotherapy. A first-in-class SII-based predictive scoring model well distinguished patients who might not benefit from neoadjuvant chemotherapy, with an area under the curve of 0.751. In HR-positive cancers, SII was more strongly associated with clinicopathological features and chemotherapy response. In addition, a receiver operating characteristic curve analysis indicated that the specificity of follow-up SII in identifying cancer relapse was greater than 98.0% at a cut-off value of 900.

Conclusion

As a predictor of breast cancer, especially in the HR-positive subtype, SII may eclipse NLR/PLR. SII-high patients are more likely to have a worse chemotherapy response and a higher risk of recurrence.

Leveraging the Dynamic Immune Environment Triad in Patients with Breast Cancer: Tumour, Lymph Node, and Peripheral Blood

During the anti-tumour response to breast cancer, the primary tumour, the peripheral blood, and the lymph nodes each play unique roles. Immunological features at each site reveal evidence of continuous immune cross-talk between them before, during and after treatment. As such, immune responses to breast cancer are found to be highly dynamic and truly systemic, integrating three distinct immune sites, complex cell-migration highways, as well as the temporal dimension of disease progression and treatment. In this review, we provide a connective summary of the dynamic immune environment triad of breast cancer. It is critical that future studies seek to establish dynamic immune profiles, constituting multiple sites, that capture the systemic immune response to breast cancer and define patient-selection parameters resulting in more significant overall responses and survival rates for breast cancer patients.

Platelet-to-lymphocyte ratio associated with the clinicopathological features and prognostic value of breast cancer: A meta-analysis

OBJECTIVE

The association of platelet-to-lymphocyte ratio (PLR) with the clinicopathological features and prognosis in patients with breast cancer was evaluated.

METHOD

Related studies were searched from PubMed, Embase, Cochrane Library, and Web of Science up to July 1, 2021. Then, basic characteristic and prognostic data were extracted from the included studies. We synthesized and compared primary outcomes such as overall survival. Subgroups analyses in pathology, geographical area, follow-up time, and sample size were conducted. The pooled hazard ratio (HR), odds ratio (OR), and 95% confidence interval (CI) served as measures to assess the relationship of PLR with prognosis and clinicopathological features of breast cancer patients. After literature retrieval and selection, 20 studies with 7484 patients were included in this meta-analysis.

RESULTS

High PLR was significantly related to poor overall survival (HR = 1.88; 95% CI 1.61, 2.19; P < 0.001) in breast cancer patients. Also, high PLR was associated with lymph node metastasis (LNM) (OR = 1.82; 95% CI 1.32, 2.52; P < 0.001), advanced tumor-node-metastasis (TNM) stage (OR = 1.89; 95% CI 1.25, 2.87; P = 0.003), and distant metastasis (OR = 1.76; 95% CI 1.14, 2.72; P = 0.01) in breast cancer. The stability and reliability of results in this meta-analysis were confirmed by sensitivity analysis.

CONCLUSION

Elevated PLR is related to a poor prognosis and a higher risk of LNM, advanced TNM stage, and distant metastasis in breast cancer patients. Therefore, PLR can be identified as a biomarker with potential prognostic value in breast cancer.

Pan-Immune-Inflammation Value: A New Prognostic Index in Operative Breast Cancer

Background

To build a predictive scoring model based on simple immune and inflammatory parameters to predict postoperative survival in patients with breast cancer.

Methods

We used a brand-new immuno-inflammatory index-pan-immune-inflammation value (PIV)-to retrospectively evaluate the relationship between PIV and overall survival (OS), and based on the results of Cox regression analysis, we established a simple scoring prediction model based on several independent prognostic parameters. The predictive accuracy of the model was evaluated and independently validated.

Results

A total of 1,312 patients were included for analysis. PIV was calculated as follows: neutrophil count (10⁹/L) × platelet count (10⁹/L) × monocyte count (10⁹/L)/lymphocyte count (10⁹/L). According to the best cutoff value of PIV, we divided the patients into two different subgroups, high PIV (PIV > 310.2) and low PIV (PIV ≤ 310.2), associated with significantly different survival outcomes (3-year OS, 80.26% vs. 86.29%, respectively; 5-year OS, 62.5% vs. 71.55%, respectively). Six independent prognostic factors were identified and used to build the scoring system, which performed well with a concordance index (C-index) of 0.759 (95% CI: 0.715-0.802); the calibration plot showed good calibration.

Conclusions

We have established and verified a simple scoring system for predicting prognosis, which can predict the survival of patients with operable breast cancer. This system can help clinicians implement targeted and individualized treatment strategies.

The Systemic Immune-Inflammation Index is an Independent Predictor of Survival in Breast Cancer Patients

Purpose

The current investigation examines the potential clinical value and prognostic significance of a systemic immune-inflammation index (SII) in patients with breast cancer.

Patients and Methods

A total of 477 individuals underwent neoadjuvant chemotherapy, and 308 individuals did not at our center between January 1998 and December 2016 were selected. An optimized SII threshold was generated using a receiver operating characteristic curve (ROC). The relationship between various factors and breast cancer in predicting disease-free survival (DFS) and overall survival (OS) were analyzed.

Results

The SII < 560 group (Low SII group) and SII ≥ 560 group (High SII group) are divided according to the threshold value. SII was an independent predictor for breast cancer DFS and OS based on univariate and multivariate analyses. Low SII patients had higher mean DFS and OS in contrast to those in the high SII groups (46.65 vs 27.37 months and 69.92 vs 49.53 months). Those in the low SII cohort who also had early or advanced breast cancer, different molecular subtypes, and with or without lymph vessel invasion all had higher mean survival time of DFS and OS in contrast to those with raised SII values (P<0.05). The mean DFS and OS durations also varied based on different Miller and Payne grades (MPG) (P <0.005), and different response groups (P<0.05).

Conclusion

SII can be used as an easily accessible and minimally invasive potential prognostic factor in individuals with breast cancer and may also guide clinicians in treating and prognosticating patients with breast cancer.

Predictive value of immune cell counts and neutrophil-to-lymphocyte ratio for 28-day mortality in patients with sepsis caused by intra-abdominal infection

Background

The current study aimed to evaluate the value of immune cell counts and neutrophil-to-lymphocyte ratio (NLR) when attempting to predict 28-day mortality.

Methods

We conducted an observational retrospective study that included consecutive septic patients. Severity scores on the first day and peripheral circulating immune cell counts (at day 1, day 3, day 5 and day 7 of admission) were collected during each patient’s emergency intensive care unit stay. We assessed the associations of peripheral circulating immune cell counts and NLR with the severity of illness. The relationships between 28-day mortality and peripheral circulating immune cell counts and NLR with were evaluated using Cox proportional cause-specific hazards models.

Results

A total of 216 patients diagnosed with sepsis caused by IAI were enrolled. The lymphocyte counts (days 1, 3, 5 and 7) and monocyte counts (days 3, 5 and 7) were significantly lower in non-survivors (n = 72) than survivors (n = 144). The NLR values at each time point were significantly higher in non-survivors. The day 1 lymphocyte counts, as well as the monocyte counts, were significantly lower in the highest-scoring group, when stratified by the Acute Physiology and Chronic Health Evaluation II and Sequential Organ Failure Assessment scores, than in the other groups (p < 0.05). The day 1 NLR was significantly higher in the highest-scoring group than in the other groups (p < 0.05). The day 5 and day 7 lymphocyte counts, day 3 and day 7 monocyte counts and day 7 NLR were significant predictors of 28-day mortality in the Cox proportional hazards models (day 5 lymphocyte count: hazard ratio, 0.123 (95% CI, 0.055–0.279), p < 0.001; day 7 lymphocyte count: hazard ratio, 0.115 (95% CI, 0.052–0.254), p < 0.001; day 3 monocyte count: hazard ratio, 0.067 (95% CI, 0.005–0.861), p = 0.038; day 7 monocyte count: hazard ratio, 0.015 (95% CI, 0.001–0.158), p < 0.001; day 7 NLR: hazard ratio, 0.773 (95% CI, 0.659–0.905), p = 0.001).

Conclusions

The results showed that circulating lymphocytes and monocytes were dramatically decreased within 7 days in non-survivors following sepsis from an IAI. Lymphocyte counts, monocyte counts and NLR appeared to be associated with the severity of illness, and they may serve as independent predictors of 28-day mortality in septic patients with IAIs.

Systemic Immune-Inflammation Index (SII) Predicts Increased Severity in Psoriasis and Psoriatic Arthritis

Background: Psoriasis is a common chronic inflammatory dermatosis. Systemic immune inflammation index (SII) is an inflammation-based biomarker, which has been shown to be an effective prognostic factor in diseases with an inflammation-related etiology. Objectives: The aim of the present study was to investigate the potential efficacy of SII as a prognostic factor in patients with psoriasis and psoriatic arthritis. Materials and methods: This is a study developed based on the analysis of the medical records of patients with psoriasis. The study retrospectively evaluated the records of the participants for complete blood count results. The SII was calculated by the formula: neutrophil x platelet/lymphocyte. Neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR) and platelet-lymphocyte ratio (PLR) were determined. Results: SII was significantly higher in patients with psoriasis than in controls (578.1 vs. 396, p<0.001). The differences between the median NLR (2.2 vs. 1.5, p<0.001), MLR (0.25 vs. 0.21, p<0.001) and the mean red cell distribution width coefficient of variation (13.8 vs. 12.8, p<0.001) values of patient and control group were significant. SII was higher in patients with moderate/severe psoriasis than patients with mild psoriasis (687.3 vs. 506.6, p=0.034). A positive correlation was observed between SII and PASI (p<0.001; r=0.37). SII was higher in patients with arthritis than patients without (672.1 vs. 548.2, p=0.018). Conclusion: This is the first study to prove that SII might serve as an independent prognostic indicator for patients with psoriasis and psoriatic arthritis.

Systemic Immune-Inflammation Index Is Superior to Neutrophil to Lymphocyte Ratio in Prognostic Assessment of Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy

Results

SII, NLR, and PLR did not define patient groups with distinct clinicopathological characteristics. SII, NLR, and PLR cut-off values were 547, 2.13, and 88.23, as determined by ROC analysis; the corresponding areas under the curve (AUCs) were 0.625, 0.555, and 0.571, respectively. Cox regression models identified SII as independently associated with OS. Patients with low SII had prolonged OS (65 vs. 41 months, P = 0.017, HR: 3.24, 95% CI: 1.23-8.55). In the Z test, the difference in AUC between SII and NLR was statistically significant (Z = 2.721, 95% CI: 0.0194-0.119, P = 0.0065).

Conclusion

Our study suggests that the pretreatment SII value is significantly correlated with OS in breast cancer patients undergoing NAC and that the prognostic utility of SII is superior to that of NLR and PLR.

Prognostic value of the systemic immune-inflammation index in patients with breast cancer: a meta-analysis

Background

Although previous studies have evaluated the prognostic role of the systemic immune-inflammation index (SII) in patients with breast cancer, the results were inconsistent. Therefore, in this context, we aimed to identify the prognostic and clinicopathological value of the SII in patients with breast cancer by performing a meta-analysis.

Methods

A literature search was using PubMed, Web of Science, EMBASE, and Cochrane Library databases for relevant articles, from their inception to May 12, 2020. The prognostic value of the SII in breast cancer was assessed by pooling the hazard ratios (HRs) with 95% confidence intervals (CIs). The clinical outcomes included the overall survival (OS), disease-free survival (DFS), recurrence-free survival (RFS), and distant metastasis-free survival (DMFS). The methodological quality of all the included studies was evaluated using the Newcastle–Ottawa quality assessment scale. The odds ratios (ORs) with 95% CIs were combined to evaluate the correlation between the SII and clinicopathological characteristics of patients with breast cancer. Publication bias was evaluated using the Begg funnel plot and the Egger linear regression test. All statistical analyses were performed using Stata software, version 12.0 (Stata Corporation, College Station, TX, USA). A p value of < 0.05 was considered statistically significant.

Results

Eight studies involving 2642 patients were included in the current meta-analysis. The combined data showed that patients with a high SII had worse OS (HR = 1.79, 95% CI 1.33–2.42, p < 0.001), poorer DFS/RFS (HR = 1.79, 95% CI 1.31–2.46, p < 0.001), and inferior DMFS (HR = 1.64, 95% CI 1.32–2.03, p < 0.001) than patients with a low SII. In addition, a high SII was correlated with the presence of lymph node metastasis (OR = 1.38, 95% CI 1.12–1.69, p = 0.002), higher T stage (OR = 1.49, 95% CI 1.17–1.89, p < 0.001), advanced TNM stage (OR = 1.37, 95% CI 1.07–1.77, p = 0.014), and higher histological grade (OR = 3.71, 95% CI 1.00–13.73, p = 0.049). However, there was no significant association between the SII and the pathological type (OR = 0.82, 95% CI 0.55–1.23, p = 0.345) or lymphatic invasion (OR = 1.30, 95% CI 0.82–2.08, p = 0.266).

Conclusions

The results of our meta-analysis suggest that an elevated SII predicts poor survival outcomes and is associated with clinicopathological features that indicate tumor progression of breast cancer.