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

Combined systemic inflammatory immune index and prognostic nutrition index as chemosensitivity and prognostic markers for locally advanced gastric cancer receiving neoadjuvant chemotherapy: a retrospective study

BACKGROUND

The prognosis nutritional index (PNI) and the systemic inflammatory immunological index (SII) are characteristic indicators of the nutritional state and the systemic inflammatory response, respectively. However, there is an unknown combined effect of these indicators in the clinic. Therefore, the practicality of using the SII-PNI score to predict prognosis and tumor response of locally advanced gastric cancer (LAGC) following chemotherapy was the main focus of this investigation.

METHODS

We retrospectively analyzed 181 patients with LAGC who underwent curative resection after neoadjuvant chemotherapy in a prospective study (NCT01516944). We divided these patients into tumour regression grade(TRG) 3 and non-TRG3 groups based on tumor response (AJCC/CAP guidelines). The SII and PNI were assessed and confirmed the cut-off values before treatment. The SII-PNI values varied from 0 to 2, with 2 being the high SII (≥ 471.5) as well as low PNI (≤ 48.6), a high SII or low PNI is represented by a 1 and neither is represented by a 0, respectively.

RESULTS

51 and 130 samples had TRG3 and non-TRG3 tumor responses respectively. Patients with TRG3 had substantially higher SII-PNI scores than those without TRG3 (p < 0.0001). Patients with greater SII-PNI scores had a poorer prognosis (p < 0.0001). The SII-PNI score was found to be an independent predictor of both overall survival (HR = 4.982, 95%CI: 1.890-10.234, p = 0.001) and disease-free survival (HR = 4.763, 95%CI: 1.994-13.903, p = 0.001) in a multivariate analysis.

CONCLUSION

The clinical potential and accuracy of low-cost stratification based on SII-PNI score in forecasting tumor response and prognosis in LAGC is satisfactory.

Inflammation and Colorectal Cancer: A Meta-Analysis of the Prognostic Significance of the Systemic Immune-Inflammation Index (SII) and the Systemic Inflammation Response Index (SIRI)

The overall prognosis for colorectal cancer (CRC) remains challenging as the survival time varies widely, even in patients with the same stage of disease. Recent studies suggest prognostic relevance of the novel markers of systemic inflammation, the systemic immune-inflammation index (SII), and the systemic inflammation response index (SIRI). We conducted a comprehensive meta-analysis to assess the prognostic significance of the SII and the SIRI in CRC. We searched the relevant literature for observational studies, and random effects models were employed to conduct a statistical analysis using the metaanalysisonline.com platform. Pooled effect sizes were reported with hazard ratios (HRs) and corresponding 95% confidence intervals (CI). Data from 29 studies published between 2016 and 2024, comprising 10,091 participants, were included in our meta-analysis on SII. CRC patients with high SII levels had worse disease outcomes, which were associated with poor OS (HR: 1.75; 95% CI: 1.4-2.19) and poor PFS/DFS/RFS (HR: 1.25; 95% CI: 1.18-1.33). This increased risk of worse OS was present irrespective of the treatment strategy, sample size (<220 and ≥220), and cutoff used to define high and low SII (<550 and ≥550) groups. Based on data from five studies comprising 2362 participants, we found a strong association between the high SIRI and worse OS (HR: 2.65; 95% CI: 1.6-4.38) and DFS/RFS (HR: 2.04; 95% CI: 1.42-2.93). According to our results, both the SII and SIRI hold great promise as prognostic markers in CRC. Further validations are needed for their age- and stage-specific utility in the clinical routine.

Predictive Value of Pretreatment Neutrophil to Albumin Ratio in Response to Neoadjuvant Chemotherapy of Breast Cancer

Background

The immune system appears to play a crucial role in how breast cancer responds to chemotherapy. In this study, we investigated a peripheral marker of immune and inflammation named the neutrophil to albumin ratio (NAR) to explore its potential relationship with pathological complete response (pCR) in locally advanced breast cancer patients who underwent neoadjuvant chemotherapy (NAC).

Methods

We conducted a retrospective analysis of 212 consecutive breast cancer patients who received NAC. The NAR was calculated by examining the complete blood cell count and albumin level in peripheral blood before starting NAC. Through ROC curve analysis, we determined the optimal cutoff value for NAR as 0.0877. We used Pearson's chi-square test or Fisher's exact test to evaluate the relationship between NAR and pCR, as well as other clinical and pathological characteristics. Logistic regression models were employed for univariate and multivariate analyses.

Results

The results of both univariate and multivariate logistic regression analyses showed that NAR was associated with tumor pathological regression. The NAR high group had a higher pCR rate compared to the NAR low group (OR 3.127 [95% CI 1.545-6.328]; p = 0.002).

Conclusion

According to this study, it was observed that patients with breast cancer who had high levels of NAR were more likely to achieve pCR when undergoing NAC.

Predictive value of pretreatment circulating inflammatory response markers in the neoadjuvant treatment of breast cancer: meta-analysis

BACKGROUND

Systemic inflammatory response markers have been found to have a prognostic role in several cancers, but their value in predicting the response to neoadjuvant chemotherapy in breast cancer is uncertain. A systematic review and meta-analysis of the literature was carried out to investigate this.

METHODS

A systematic search of electronic databases was conducted to identify studies that explored the predictive value of circulating systemic inflammatory response markers in patients with breast cancer before commencing neoadjuvant therapy. A meta-analysis was undertaken for each inflammatory marker where three or more studies reported pCR rates in relation to the inflammatory marker. Outcome data are reported as ORs and 95% confidence intervals.

RESULTS

A total of 49 studies were included, of which 42 were suitable for meta-analysis. A lower pretreatment neutrophil-to-lymphocyte ratio was associated with an increased pCR rate (pooled OR 1.66 (95% c.i. 1.32 to 2.09); P < 0.001). A lower white cell count (OR 1.96 (95% c.i. 1.29 to 2.97); P = 0.002) and a lower monocyte count (OR 3.20 (95% c.i. 1.71 to 5.97); P < 0.001) were also associated with a pCR. A higher lymphocyte count was associated with an increased pCR rate (OR 0.44 (95% c.i. 0.30 to 0.64); P < 0.001).

CONCLUSION

The present study found the pretreatment neutrophil-to-lymphocyte ratio, white cell count, lymphocyte count, and monocyte count of value in the prediction of a pCR in the neoadjuvant treatment of breast cancer. Further research is required to determine their value in specific breast cancer subtypes and to establish optimal cut-off values, before their adoption in clinical practice.

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.

Prognostic significance of platelet-to-lymphocyte ratio (PLR) in patients with breast cancer treated with neoadjuvant chemotherapy: a meta-analysis

OBJECTIVE

Platelet-to-lymphocyte ratio (PLR), known as a key systemic inflammatory parameter, has been proved to be associated with response to neoadjuvant therapy in breast cancer (BC); however, the results remain controversial. This meta-analysis was carried out to evaluate the prognostic values of PLR in patients with BC treated with neoadjuvant chemotherapy (NACT).

DESIGN

Meta-analysis.

DATA SOURCES

Relevant literature published on the following databases: PubMed, Embase, Web of Science databases and the Cochrane Library.

ELIGIBILITY CRITERIA

All studies involving patients with BC treated with NACT and peripheral blood pretreatment PLR recorded were included.

DATA EXTRACTION AND SYNTHESIS

Two researchers independently extracted and evaluated HR/OR and its 95% CI of survival outcomes, pathological complete response (pCR) rate and clinicopathological parameters.

RESULTS

The last search was updated to 31 December 2022. A total of 22 studies with 5533 patients with BC treated with NACT were enrolled in the final meta-analysis. Our results demonstrate that elevated PLR value appears to correlate with low pCR rate (HR 0.77, 95% CI 0.67 to 0.88, p<0.001, I2=75.80%, Ph<0.001) and poor prognosis, including overall survival (OS) (HR 1.90, 95% CI 1.39 to 2.59, p<0.001; I2=7.40%, Ph=0.365) and disease-free survival (HR 1.97, 95% CI 1.56 to 2.50, p<0.001; I2=0.0%, Ph=0.460). Furthermore, PLR level was associated with age (OR 0.86, 95% CI 0.79 to 0.93, p<0.001, I2=40.60%, Ph=0.096), menopausal status (OR 0.83, 95% CI 0.76 to 0.90, p<0.001, I2=50.80%, Ph=0.087) and T stage (OR 1.05, 95% CI 1.00 to 1.11, p=0.035; I2=70.30%, Ph=0.005) of patients with BC.

CONCLUSIONS

This meta-analysis demonstrated that high PLR was significantly related to the low pCR rate, poor OS and disease-free survival (DFS) of patients with BC treated with NACT. Therefore, PLR can be used as a potential predictor biomarker for the efficacy of NACT in BC.

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.

Naples score: a novel prognostic biomarker for breast cancer patients undergoing neoadjuvant chemotherapy

BACKGROUND AND PURPOSE

The Naples Score (NPS) is a novel prognostic indicator that has been used in various cancers, but its potential in breast malignant tumor patients receiving neoadjuvant chemotherapy (NAC) has not been discovered. This study aimed to investigate the relationship between NPS and overall survival (OS) and disease-free survival (DFS) in breast cancer patients.

METHODS

A total of 217 breast cancer patients undergoing NAC were incorporated into this retrospectively research. K-M survival curves and log-rank tests are used to determine OS and DFS. Cox regression model was used to evaluate the relationship between NPS and OS and DFS. Nomogram was developed based on the results of multivariate Cox regression analysis. Prognostic models were internally validated using bootstrapping and the consistency index (C-index).

RESULTS

Age group was correlated with NPS (p < 0.05). Low and moderate Naples risk patients had higher 5-year OS and DFS rates than high risk Naples patients (93.8% vs. 75.4% vs. 60.0%; X2 = 9.2, P = 0.01; 82.4% vs 64.5% vs 43.7%; X2 = 7.4, P = 0.024; respectively). The nomogram based on demonstrated good performance in predicting OS and DFS (AUC = 0.728, 0.630; respectively).

CONCLUSIONS

In breast cancer patients who have undergone NAC, NPS is a novel prognostic indicator. NPS combined with clinicopathological features showed good predictive ability, and its performance was better than that of traditional pathological TNM staging.

High Levels of SII and PIV are the Risk Factors of Axillary Lymph Node Metastases in Breast Cancer: A Retrospective Study

Purpose

To investigate the predictive value of systemic immune-inflammation-index (SII) and Pan-Immune-Inflammation-value (PIV) for axillary lymph node (ALN) metastasis in patients with breast cancer.

Patients and Methods

We retrospectively collected data of 247 patients with invasive breast from the Affiliated Hospital of Jiangnan University. The state of axillary lymph node (ALN) metastasis was confirmed by pathological diagnosis. Clinicopathological data (age, ER, PR, HER2, Ki67 expression levels, diapause status, weight, histological grade, vascular invasion, and state of axillary lymph node) were compared between differences of SII and PIV groups and an association between clinical indexes and ALN metastasis was evaluated.

Results

The cut-off values of SII and PIV were 320.04 and 92.01, respectively. The significant difference between vascular invasion (P=0.023) and axillary lymph node metastases (P<0.001) in the high and low SII levels. Significant differences were observed in tumor size (p=0.024), PR expression level (P=0.033) and the status of axillary lymph node metastases (p<0.001) between the high PIV group and the low PIV group. Univariate analysis showed that vascular invasion, tumor size, Ki67 expression level, SII, and PIV were significantly correlated with axillary lymph node metastases (p<0.05). Then, multivariate analysis revealed that the vascular invasion (p<0.001), HER2 expression levels (p<0.047), SII (p<0.001) and PIV (p<0.030) were risk factors for axillary lymph node metastases.

Conclusion

High levels of SII, PIV, LVI, and HER2 are the risk factors for axillary lymph node metastases in breast cancer patients.

Systemic Immune-Inflammation Index Predicts Acute Symptomatic Hydrocephalus After Spontaneous Nonaneurysmal Subarachnoid Hemorrhage

OBJECTIVE

The authors sought to investigate the association between white blood cell counts and acute hydrocephalus in spontaneous nonaneurysmal subarachnoid hemorrhage (nSAH).

METHODS

We conducted a retrospective analysis of 105 consecutive patients with spontaneous nSAH. Univariate and multivariable logistic regression analyses were performed to investigate factors associated with hydrocephalus. Receiver operating characteristic curve analysis determined the optimal cutoff to differentiate between patients with and without hydrocephalus. The admission characteristics of hydrocephalic patients with aneurysmal and nSAH were compared.

RESULTS

A total of 70 patients met inclusion criteria, of which 21 (30%) presented with hydrocephalus. In univariate logistic regression, leukocytes, neutrophils, lymphocytes, neutrophil-to-lymphocyte ratio, lymphocyte-to-monocyte ratio, neutrophil-monocyte-to-lymphocyte ratio, and the systemic immune-inflammation (SII) index ([neutrophils × platelets/lymphocytes]/1000) were associated with hydrocephalus. After adjustments, the SII index independently predicted acute hydrocephalus with the highest odds among laboratory values (odds ratio 2.184, P = 0.006). Receiver operating characteristic curve analysis revealed the SII index differentiated between patients with and without hydrocephalus (area under the curve = 0.799, 95% CI: 0.688-0.909, P < 0.001) with an optimal cutoff of 1.385 103/μL. SII indices did not differ between aneurysmal and nSAH patients with hydrocephalus (3.5 vs. 3.6 103/μL, P = 0.795).

CONCLUSIONS

A SII index ≥1.385 103/μL on admission predicts acute hydrocephalus in spontaneous nSAH. Hydrocephalic patients with aneurysmal and nSAH exhibit similar SII indices, and thus, an exaggerated inflammatory and thrombotic response follows spontaneous subarachnoid hemorrhage irrespective of hemorrhage etiology.

Association between Posttreatment Serum Platelet-to-Lymphocyte Ratio and Distant Metastases in Patients with Hepatocellular Carcinoma Receiving Curative Radiation Therapy

Background: We sought to investigate whether serum immune and inflammatory parameters can help to predict distant metastasis (DM) in patients with unresectable hepatocellular carcinoma (HCC) undergoing curative radiation therapy (RT). Methods: A total of 76 RT courses were analyzed. The following variables were included in the analysis: systemic inflammation index, neutrophil-to-lymphocyte ratio, platelet-to-lymphocyte ratio (PLR), prognostic nutritional index (PNI), absolute lymphocyte count, lymphocyte-to-monocyte ratio, albumin, albumin-to-alkaline phosphatase ratio, RT-related parameters, and levels of total protein, hemoglobin, α-fetoprotein, and PIVKA-II. Distant control (DC) and overall survival (OS) rates were calculated and compared. Results: The mean age was 61.4 years, and most patients were men (n = 62, 81.6%). The median RT fraction number and fractional doses were 12 (range, 4–30) and 5 (range, 2–12) Gy, respectively. With a median follow-up of 12 (range, 3.1–56.7) months, the 1-year DC and OS rates were 64.4% and 55.2%, respectively. The development of DM significantly deteriorated OS (p = 0.013). In the multivariate analysis, significant independent prognostic indicators for DC and OS rates were the highest posttreatment PLR (≤235.7 vs. >235.7, p = 0.006) and the lowest posttreatment PNI (≤25.4 vs. >25.4, p < 0.001), respectively. Conclusions: Posttreatment serum PLR might be helpfully used as a predictive biomarker of DM in unresectable HCC patients undergoing RT. Future research is necessary to confirm our findings.

The preoperative systemic immune-inflammation index is associated with an unfavorable prognosis for patients undergoing curative resection of esophageal squamous cell carcinoma after neoadjuvant therapy

PURPOSES

Systemic inflammation and immune status play a critical role in the development and progression of cancers. We evaluated the clinical significance of the preoperative systemic immune-inflammation index (SII) for predicting the long-term outcomes of patients who received neoadjuvant therapy for esophageal squamous cell carcinoma (ESCC).

METHODS

The subjects of this study were 277 patients who underwent curative resection of ESCC after neoadjuvant therapy. The SII was calculated as follows: SII = neutrophil × platelet/lymphocyte counts. Patients were stratified into high and low preoperative SII groups according to the cut-off value calculated by a receiver operating characteristic curve analysis. The Kaplan-Meier method and Cox proportional regression analysis were used to evaluate the correlation of SII to prognosis.

RESULTS

The optimal cutoff of the preoperative SII was set at 700. Patients were categorized into preoperative SII-low (n = 203) and SII-high (n = 74) groups. The preoperative SII was significantly associated with tumor size. The relapse-free survival of patients in the SII-high group was significantly shorter (P = 0.0087) and preoperative SII-high was identified as an independent prognostic factor (hazard ratio [HR] 1.55, 95% confidence interval [CI] 1.06-2.28, P = 0.0229). The prevalence of hematogenous recurrence was significantly higher in the SII-high group. When we stratified patients into three groups with an additional cutoff value of 1200, we observed an incremental decrease in relapse-free survival rates.

CONCLUSIONS

High preoperative SII was associated with shorter relapse-free survival times for ESCC patients who underwent curative resection after neoadjuvant therapy.

The predictive value of the systemic immune-inflammatory index for left atrial appendage thrombus in non-valvular atrial fibrillation

OBJECTIVE

The systemic immune inflammatory index (SII) has prognostic value in cardiovascular diseases. The aim of current study was to investigate whether or not left atrial appendage (LAA) thrombus could be predicted by SII in patients with non-valvular atrial fibrillation.

METHOD

The study included 525 patients newly diagnosed with non-valvular atrial fibrillation, who had not previously had anticoagulant treatment (50.7% male, mean age 62.94±10.79 years). All patients underwent transoesophageal echocardiography.

RESULTS

LAA thrombus was observed in 86 patients (16.4%). In the ROC curve SII had a good diagnostic power in predicting LAA thrombus (AUC: 0.760, 95% CI: 0.703-0.818, P<0.001). In the multivariate regression analysis, diabetes (Hazard ratio: 2.264, 95% CI: 1.169-4.389, P=0.015), LAA emptying rate of <20 cm/s (Hazard ratio: 59.347, 95% CI: 25.397-138.680, P<0.001), and SII value of >750 (Hazard ratio: 4.291, 95% CI: 2.144-8.586 P<0.001) were determined as independent predictors for LAA thrombus. A poor correlation was found between SII and the CHADS2 VASc score (r=0.239, P<0.001) Conclusion: The SII, a practical and easily obtained test, can be used as a predictor of LAA thrombus in patients with non-valvular atrial fibrillation, and to decide on the anticoagulant treatment.

The modified Glasgow prognostic score (MGPS) and the mortality prediction model II (MPM II) can predict mortality in patients with breast cancer admitted to intensive care: A retrospective cohort study

Background/Aim: Breast cancer is the second most common cause of cancer-related death in women worldwide. Predicting the prognosis in breast cancer with very high mortality is important in terms of disease treatment and increasing life expectancy. In our study, we aimed to examine the importance of some inflammatory markers and scoring systems in predicting prognosis in patients with breast cancer who were hospitalized in the intensive care unit. Methods: This retrospective cohort study was conducted in the Department of Medical Oncology and Intensive Care Unit between 2014 and 2020. Breast cancer patients who were admitted to the intensive care unit at any stage of their treatment during the study and followed up and treated in the medical oncology department of the hospital were included in the study. All data were compared between groups (discharged or exitus) based on survival status. Socio-demographic information, laboratory findings (hemoglobin, leukocytes, neutrophils, lymphocytes, platelets, eosinophils, monocytes, C-reactive protein [CRP], albumin, lactate dehydrogenase [LDH], clinical status [co-morbidities, length of stay in intensive care, mechanical ventilation, and reason for hospitalization in the intensive care unit]), and survival data of the patients were collected retrospectively from hospital medical records. We also recorded treatment-related data and relapse/progression information. Neutrophil–lymphocyte, platelet–lymphocyte, and lymphocyte–monocyte ratios (NLR, PLR, and LMR, respectively) were calculated. Results: Thirty-seven (52.1%) patients died and 34 (47.9%) patients survived. The NLR (P=0.021), Modified Glasgow Prognostic score (P<0.001), APACHE II score (P<0.001) and mortality probability model (MPM II) upon admission (P<0.001) were significantly higher in the exitus group than in the survivors. The lymphocyte_monocyte ratio (P=0.030) and prognostic nutritional index (P=0.004) were significantly higher in the discharged group than in the death group. When we evaluated performance of the prognostic scores to predict mortality, we found that the APACHE II score (area under the curve [AUC]: 0.939, 95% confidence interval [CI]: 0.888–0.990), MPM II-Admission (AUC: 0.936, 95% CI: 0.880–0.992), and modified Glasgow Prognostic Score ([mGPS] AUC: 0.727, 95% CI: 0.600–0.854) had the highest area under curve values. Multivariable regression revealed that longer chemotherapy duration (≥2 weeks), an mGPS score of two points, and high MPM-II (≥36 points) were independently associated with mortality. Conclusion: Among the inflammatory markers and scores examined, mGPS and MPM-II were found to be independently associated with mortality in breast cancer patients who were hospitalized in the intensive care unit. In addition, patients with longer chemotherapy duration had a higher risk of mortality, but this result was limited by various possible confounders.

A Novel Inflammatory and Nutritional Prognostic Scoring System for Nonpathological Complete Response Breast Cancer Patients Undergoing Neoadjuvant Chemotherapy

Background

It has been demonstrated that inflammatory and nutritional variables are associated with poor breast cancer survival. However, some studies do not include these variables due to missing data. To investigate the predictive potential of the INPS, we constructed a novel inflammatory-nutritional prognostic scoring (INPS) system with machine learning.

Methods

This retrospective analysis included 249 patients with malignant breast tumors undergoing neoadjuvant chemotherapy (NAC). After comparing seven potent machine learning models, the best model, Xgboost, was applied to construct an INPS system. K-M survival curves and the log-rank test were employed to determine OS and DFS. Univariate and multivariate analyses were carried out with the Cox regression model. Additionally, we compared the predictive power of INPS, inflammatory, and standard nutritional variables using the Z test.

Results

After comparing seven machine learning models, it was determined that the XGBoost model had the best OS and DFS performance (AUC = 0.865 and 0.771, respectively). For overall survival (OS, cutoff value = 0.3917) and disease-free survival (cutoff value = 0.4896), all patients were divided into two groups by the INPS. Those with low INPS had higher 5-year OS and DFS rates (77.2% vs. 50.0%, P < 0.0001; and 59.6% vs. 32.1%, P < 0.0001, respectively) than patients with high INPS. For OS and DFS, the INPS exhibited the highest AUC compared to the other inflammatory and nutritional variables (AUC = 0.615, P = 0.0003; AUC = 0.596, P = 0.0003, respectively).

Conclusion

The INPS was an independent predictor of OS and DFS and exhibited better predictive ability than BMI, PNI, and MLR. For patients undergoing NAC for nonpCR breast cancer, INPS was a crucial and comprehensive biomarker. It could also forecast individual survival in breast cancer patients with low HER-2 expression.

Prognostic value of a modified systemic inflammation score in breast cancer patients who underwent neoadjuvant chemotherapy

BACKGROUND AND PURPOSE

The modified systemic inflammation score (mSIS) system, which is constructed based on the neutrophil to lymphocyte ratio (NLR) and albumin (Alb), has not been applied to evaluate the prognosis of malignant breast cancer patients who underwent neoadjuvant chemotherapy (NAC). The present study aimed to explore the relationship between the mSIS and overall survival (OS), disease-free survival (DFS) and pathological complete response (pCR).

METHODS

A total of 305 malignant breast tumor patients who underwent NAC were incorporated into this retrospective analysis. We determined OS and DFS using K-M survival curves and the log-rank test. The relationship between the mSIS and OS and DFS was evaluated by a Cox regression model. A nomogram was constructed based on Cox regression analysis.

RESULTS

Patients in the mSIS low-risk group had better 5- and 8-year OS rates than those in the mSIS high-risk group (59.8% vs. 77.0%; 50.1% vs. 67.7%; X² = 8.5, P = 0.0035, respectively). Patients in the mSIS (1 + 2 score) + pCR subgroup had the highest 5- and 8-year OS and disease-free survival (DFS) rates (OS: 55.0% vs. 75.7% vs. 84.8, 42.8% vs. 65.7% vs. 79.8%, X² = 16.6, P = 0.00025; DFS: 38.8% vs. 54.7% vs. 76.3%, 33.3% vs. 42.3 vs. 72.1%, X2 = 12.4, P = 0.002, respectively). Based on the mSIS, clinical T stage and pCR results, the nomogram had better predictive ability than the clinical TNM stage, NLR and Alb.

CONCLUSIONS

mSIS is a promising prognostic tool for malignant breast tumor patients who underwent NAC, and the combination of mSIS and pCR is helpful in enhancing the ability to predict a pCR.

Systemic Immun e–Inflammation Index as a Predictor for Head and Neck Cancer Prognosis: A Meta-Analysis

Background

Studies have reported inconsistent results regarding the prognostic value of the systemic immune–inflammation index (SII) in head and neck cancer (HNC). Thus, the present meta-analysis assessed the literature on the prognostic value of SII in those with HNC.

Methods

The Cochrane Library, EMBASE, and PubMed databases were searched, and study methodological quality was assessed using the Newcastle–Ottawa quality assessment scale. To determine the association of the SII with survival outcomes, pooled hazard ratios (HRs) as well as the associated 95% confidence intervals (CIs) were used. To assess the associations of the SII with clinicopathological features, the odds ratios (ORs) and corresponding 95% CIs were considered. Begg’s funnel plot and Egger’s linear regression test were used to assess publication bias.

Results

A total of 12 studies that together enrolled 4369 patients with HNC were analyzed. In the pooled results, a high pretreatment SII was correlated with poorer overall survival (HR = 2.09, 95% CI = 1.62–2.70, p < 0.001), disease-free survival (HR = 2.79, 95% CI = 1.99−3.89, p < 0.001), and progression-free survival (HR = 1.80, 95% CI = 1.30−2.48, p < 0.001). A stratified analysis indicated that SII for overall survival was applicable regardless of tumor site, treatment modality, overall stage, sample size, SII cutoff, and method for determining the SII cutoff. Furthermore, a high SII was correlated with a more advanced T classification (OR = 1.14, 95% CI = 1.09–1.18, p < 0.001) and nodal metastasis (OR = 1.55, 95% CI = 1.18–2.05, p = 0.002) in patients with HNC.

Conclusions

An elevated pretreatment SII predicts more advanced tumor and nodal status and poorer survival outcomes in cases of HNC. Because the measurement of SII is convenient and its use is cost-effective, we suggest that it can be applied by clinicians in the management of HNC.

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.

Comparison of systemic immune-inflammation index levels in patients with isolated coronary artery ectasia versus patients with obstructive coronary artery disease and normal coronary angiogram

Coronary artery ectasia (CAE) is associated with increased risk of mortality, equivalent to that of patients with obstructive coronary artery disease (CAD). Considering the role of inflammation in the pathogenesis of CAE, we aimed to investigate whether there is an association between systemic immune-inflammation index (SII) and isolated CAE. The study population included 510 patients of which 170 patients with isolated CAE, 170 patients with obstructive CAD and 170 patients with normal coronary angiograms (NCA). The severity of CAE was determined according to the Markis classification. Patients with isolated CAE had significantly higher SII values compared to those with obstructive CAD and NCA [median 550 IQR (404-821), median 526 IQR (383-661), and median 433 IQR (330-555), respectively, p < .001]. In multivariate analysis, SII (OR 1.032, 95% CI 1.020-1.044, p = .003), male gender (OR 2.083, p = .008), eGFR (OR 0.979, p = .016), and CRP (OR 1.105, p = .005) were independent factors of isolated CAE. Moreover, in the Spearman correlation analysis, there was a moderate but significant positive correlation between SII and CRP (r = 0.379, p < .001). In conclusion, higher SII levels were independently associated with the presence of isolated CAE. This result suggests that a more severe inflammatory process may play a role in the development of this variant of CAD.

The Value of the Systemic Immune-Inflammation Index in Predicting Survival Outcomes in Patients with Brain Metastases of Non-Small-Cell Lung Cancer Treated with Stereotactic Radiotherapy

Background

As a parameter integrating platelet (P), neutrophil (N), and lymphocyte (L) levels, the systemic immune-inflammation index (SII) has been used as a prognostic marker for patient survival in various types of solid malignant tumors. However, there is no in-depth study in non-small-cell lung cancer (NSCLC) patients with brain metastases after stereotactic radiotherapy. Therefore, we performed a retrospective analysis to determine the clinical and prognostic value of the SII in NSCLC patients with brain metastases who underwent stereotactic radiotherapy.

Materials and Methods

We enrolled 124 NSCLC patients with brain metastases treated with stereotactic radiotherapy in our hospital between May 2015 and June 2018. We obtained all baseline blood samples within one week prior to stereotactic radiotherapy. The SII was calculated by the following formula: neutrophil counts × platelet counts/lymphocyte counts. The optimal cutoff value of the SII for predicting prognosis was assessed by receiver operating characteristic (ROC) curves with the maximum log-rank values. The discriminative ability of predicting prognosis was calculated and compared using the Kaplan–Meier method and log-rank test. The hazard ratio (HR) and 95% confidence interval (CI) were combined to evaluate the prognostic impact of the blood index on overall survival (OS) and progression-free survival (PFS). Only those parameters that proved to be associated with statistically significant differences in clinical outcomes were compared in multivariate analysis using a multiple Cox proportional hazard regression model to identify independent prognostic factors.

Results

Of the total enrolled patients, 53.2% and 46.8% have high SII and low SII, respectively. In this study, Kaplan–Meier curve analysis revealed that the median PFS was 9 months (range: 2–22 months) and the median OS was 18 months (range: 4–37 months). Applying an optimal cutoff of 480 (SII), the median PFS was better in the low SII group patients (11.5 vs. 9 months), and the median OS was significantly longer in the low SII group patients (20 vs. 18 months). A SII > 480 was significantly associated with worse OS (HR: 2.196; 95% CI 1.259–3.832; P = 0.006) and PFS (HR: 2.471; 95% CI 1.488–4.104; P < 0.001) according to univariate analysis. In multivariate analysis, only age (HR: 2.159; 95% CI 1.205–3.869; P = 0.010), KPS (HR: 1.887; 95% CI 1.114–3.198; P = 0.018), and SII (HR: 1.938; 95% CI 1.046–3.589; P = 0.035) were independently correlated with OS, and SII (HR: 2.224; 95% CI 1.298–3.810; P = 0.004) was an independent prognostic predictor of PFS, whereas we found that other inflammation-based indices lost their independent value.

Conclusions

The SII, which is an integrated blood parameter based on platelet, neutrophil, and lymphocyte counts, may be an independent prognostic indicator and may be useful for the identification of NSCLC patients with brain metastases after stereotactic radiotherapy at high risk for recurrence.

Association between systemic immune-inflammation index and neoadjuvant chemotherapy efficacy as well as prognosis in triple-negative breast cancer

OBJECTIVES

Triple-negative breast cancer (TNBC) is a highly aggressive subtype of breast cancer with a relatively poor prognosis. Neoadjuvant chemotherapy (NAC) is the main treatment method. Due to the heterogeneity of the tumor, the chemotherapy response of TNBC patients is significantly different. Inflammation is closely related to the occurrence and development of cancer. The systemic immune-inflammation index (SII) is an indicator that can comprehensively reflect the state of systemic inflammation. This study aims to explore the association between SII and the NAC efficacy as well as the prognosis in TNBC.

METHODS

The data of TNBC patients who underwent NAC and systemic treatment in Xiangya Hospital of Central South University from January 2015 to June 2019 were collected. According to the inclusion and exclusion criteria, 231 TNBC patients were finally included. The pre-NAC SII was calculated according to the blood routine results of the patients at 1 week before chemotherapy, and the patients were divided into a pre-NAC low SII group (SII<412, 115 cases) and a pre-NAC high SII group (SII≥412, 116 cases). The SII after chemotherapy was calculated according to the blood routine results of the patients at 2 to 3 months after the end of chemotherapy, and the patients were divided into a low SII group after chemotherapy (SII<474, 115 cases) and a high SII group after chemotherapy (SII≥474, 116 cases). Pearson's chi-square test was used to analyze the relationship between SII and other clinical characteristics of TNBC patients, and the relationship between the NAC efficacy and clinical characteristics of TNBC patients. Binary logistic regression analysis was used to find independent factors that affect the efficacy of NAC in TNBC patients. Kaplan-Meier curve analysis was used to analyze factors affecting the prognosis of TNBC patients. Cox regression model was used to find independent factors affecting the prognosis of TNBC patients.

RESULTS

Before NAC, the differences in SII between groups with different ages and tumor sizes were significant (P=0.007 and P=0.002, respectively); after chemotherapy, there were no significant differences in SII between different ages, tumor sizes, histological grades, lymph node staging, and Ki-67 groups (all P>0.05). There were 115 patients with low SII before NAC, with a pathological complete response (pCR) rate of 15.7%; there were 116 patients with high SII before NAC, with a pCR rate of 6.0%. Patients with low SII before NAC had a higher pCR rate than patients with high SII before NAC, and the difference was statistically significant (P=0.019).There were 156 patients with lymph node staging pN0, with a pCR rate of 14.7%; and there were 75 patients with lymph node staging pN1-pN2, with a pCR rate of 2.7%. Patients with lymph node staging pN0 had a higher pCR rate than those with lymph node staging pN1-pN2, and the difference was significant (P=0.006). During the follow-up, 34 patients had local recurrence or distant metastasis. The Kaplan-Meier survival curve showed that the 3-year disease-free survival (DFS) rates for patients with low SII before NAC and high SII before NAC were 87.8% and 82.8%, respectively, and the former was significantly higher than the latter (P=0.005); the 3-year DFS rates for patients with tumor sizes of T1-T2 and T3 were 89.0% and 67.5%, respectively, and the former was significantly higher than the latter (P=0.001); the 3-year DFS rates for patients with lymph node staging of pN0 and pN1-pN2 were 87.8% and 82.8%, respectively, and the former was significantly higher than the latter (P=0.009). Cox analysis showed that SII before NAC and tumor size were independent influencing factors of patients' DFS (P=0.038, P=0.010, respectively).

CONCLUSIONS

SII has important clinical significance in predicting the efficacy and prognosis of NAC in TNBC patients, and it has the potential to be a biomarker.

Role of neutrophil-to-lymphocyte ratio as a prognostic biomarker in patients with breast cancer receiving neoadjuvant chemotherapy: a meta-analysis

OBJECTIVE

The neutrophil-to-lymphocyte ratio (NLR) is recognised as a suitable prognostic biomarker in patients with breast cancer. Nevertheless, the efficacy of this biomarker in predicting the pathological complete response (pCR) and survival in patients with breast cancer receiving neoadjuvant chemotherapy (NACT) is still controversial. This meta-analysis aimed to identify the association between baseline NLR and the prognosis of patients with breast cancer treated with NACT.

DESIGN

Meta-analysis.

DATA SOURCES

Relevant literature published before 1 May 2021 was searched using the Cochrane Library, Embase, PubMed and the Web of Science databases.

ELIGIBILITY CRITERIA

All studies involving patients with breast cancer treated with NACT and peripheral blood pretreatment NLR recorded as a dichotomous variable were included.

DATA EXTRACTION AND SYNTHESIS

Two researchers independently extracted and evaluated OR/HR and its 95% CIs of survival outcomes and clinicopathological parameters.

RESULTS

A total of 19 studies were identified. From each study, the impact of NLR on the pCR, OR and HR, with their 95% CIs were extracted and combined using either a random or fixed-effects model. The results indicate that a higher pCR in patients with a low NLR (OR 1.620, 95% CI 1.209 to 2.169, p＜0.001). In addition, an elevated NLR predicted lower disease-free survival (HR 2.269, 95% CI 1.557 to 3.307, p<0.001) and overall survival (HR 1.691, 95% CI 1.365 to 2.096, p<0.001) in patients with breast cancer treated with NACT.

CONCLUSIONS

NLR is a suitable biomarker for predicting pCR and survival in patients with breast cancer receiving NACT.

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

Background: Systemic inflammatory response is related to the occurrence, progression, and prognosis of cancers. In this research, a novel systemic inflammation response score (SIRS) was calculated, and its prognostic value for postoperative stage I-III breast cancer (BC) patients was analyzed. Methods: 1583 BC patients were included in this research. Patients were randomly divided into a training cohort (n = 1187) and validation cohort (n = 396). SIRS was established in the training cohort based on independent prognostic hematological indicator, its relationship between prognosis and clinical features was analyzed. Then, a nomogram consisted of SIRS and clinical features was established, its performance was examined by calibration plots and receiver operating characteristic curve analysis. Results: The SIRS was an independent prognostic indicator for BC patients, and a high-SIRS was related to multifocality, advanced N stage, and worse prognosis. Incorporating SIRS into a nomogram could accurately predict the prognosis of BC patients, the results of receiver operating characteristic (ROC) curve analysis showed that the area under the curve (AUC) of nomogram was up to 0.806 in training cohort and 0.905 in the validation cohort. Conclusion: SIRS was associated with the prognosis of patients with breast cancer. Nomogram based on SIRS can accurately predict the prognosis of breast cancer patients.