The Systemic Inflammation Response Index as an Independent Predictor of Survival in Breast Cancer Patients: A Retrospective Study

Geriatric Nutritional Risk Index (GNRI) and Prognostic Nutritional Index (PNI) Before Treatment as the Predictive Indicators for Bone Metastasis in Prostate Cancer Patients

Objective

Inflammation and nutritional status are involved in the occurrence and progression of cancer. The purpose of this study was to investigate the relationship of nutritional status indices (geriatric nutritional risk index (GNRI), neutrophil to albumin ratio (NAR), prognostic nutritional index (PNI)), and comprehensive inflammatory indices (pan-immune inflammation value (PIV), systemic immune inflammation index (SII), and system inflammation response index (SIRI)) and bone metastasis of prostate cancer.

Methods

A retrospective analysis was performed on 888 prostate cancer patients treated in Meizhou People's Hospital from November 2017 to December 2022. Clinical characteristics were collected, including age, body mass index (BMI), bone metastasis, and GNRI, NAR, PNI, PIV, SII, and SIRI levels. The optimal cutoff values of these indices were calculated by receiver operating characteristic (ROC) curve, and the relationship between these indices and bone metastasis was analyzed.

Results

There were 836 (94.1%) cases were ≥60 years old, indicating that the majority of prostate cancer patients were elderly men. There were 640 (72.1%) patients without bone metastasis and 248 (27.9%) patients with bone metastasis. The levels of GNRI and PNI in patients with bone metastasis were significantly lower than those without, while NAR, PIV, SII, and SIRI were not statistically significant. And the levels of GNRI and PNI in patients with multiple bone metastasis were significantly lower than those with single bone metastasis. When bone metastasis was taken as the endpoint of GNRI and PNI, the critical value of GNRI was 97.05 (sensitivity 55.2%, specificity 67.5%, area under the ROC curve (AUC) = 0.639), the PNI cutoff value was 44.925 (sensitivity 51.2%, specificity 67.2%, AUC = 0.634), and the AUC of GNRI plus PNI was 0.647.

Conclusion

Prostate cancer is more common in older men; about a quarter of patients have bone metastasis. GNRI and PNI have predictive efficacy in bone metastasis and multiple bone metastasis of prostate cancer, but NAR, PIV, SII, and SIRI do not.

Biomarkers for nasopharyngeal carcinoma

Nasopharyngeal Carcinoma (NPC) is a malignant tumor that is highly prevalent in Southeast Asia, particularly in China and Indonesia. According to the World Health Organization's global cancer statistics in 2022, there were 120,434 new cases and 73,485 deaths from NPC. Risk factors contribute to NPC development including genetic factors, dietary habits, and Epstein-Barr virus (EBV) infection. This paper reviews the comparison of different types of EBV test for NPC over the last few years and summarized the performance of novel diagnostic biomarker such as newly reported EBV antibody, anti-BNLF2b IgG (P85-Ab), microRNAs, DNA methylation and other markers for detection of NPC. Because approximately 40% of NPC patients show negative EBV DNA levels, additional markers are needed for NPC diagnosis, especially in cases without EBV infection, to make the result trustworthy. The potential biomarkers including circulating tumor cells, proteins, microRNAs and Rta-IgG for prognostic and therapeutic effect also be summarized. This review provides insights into potential biomarkers for early NPC detection and diagnosis, which could lead to improved prevention, treatment, and prognosis strategies.

Pathological complete response and prognostic predictive factors of neoadjuvant chemoimmunotherapy in early stage triple-negative breast cancer

Background

Neoadjuvant chemoimmunotherapy (nCIT) has shown promise in treating early-stage triple-negative breast cancer (eTNBC), but predictive biomarkers for pathological response and prognosis remain poorly defined.

Objective

This study aimed to explore pathological complete response and prognostic predictive factors in eTNBC patients treated with nCIT.

Materials and methods

We retrospectively analyzed 112 eTNBC patients who underwent surgery after nCIT at Sun Yat-sen University Cancer Center between June 2019 and June 2023. Pathological response was assessed using Miller-Payne grade. Clinicopathological features and hematologic markers were analyzed with univariate and multivariate logistic regression or Cox regression, as well as Kaplan-Meier survival curves. Objective response rate (ORR), pathological complete response (pCR), and disease-free survival (DFS) were evaluated. Nomograms predicting pCR and DFS were constructed based on significant risk factors and the systemic inflammatory response index (SIRI).

Results

Higher baseline lymphocyte counts (P=0.004) were independently associated with a higher pCR rate, while elevated monocyte counts (P=0.006), neutrophil-to-lymphocyte ratio (P=0.005), platelet-to-lymphocyte ratio (p = 0.005), SIRI (P=0.037), systemic immune-inflammation index (P=0.029), and preoperative SIRI (P=0.010) were associated with a lower pCR rate. Higher baseline SIRI (P= 0.009) was correlated with shorter DFS, while higher preoperative lymphocyte counts (P=0.019) predicted longer DFS. Nomograms incorporating SIRI showed high accuracy in predicting pCR and DFS.

Conclusion

Hematologic inflammatory markers, particularly SIRI, are cost-effective and reliable predictors of prognosis and treatment efficacy in eTNBC patients undergoing nCIT, helping clinicians develop personalized treatment strategies.

Clinical trial registration

https://www.medicalresearch.org.cn/, identifier MR-44-24-046099.

The Diagnostic and Prognostic Role of Inflammatory Markers, Including the New Cumulative Inflammatory Index (IIC) and Mean Corpuscular Volume/Lymphocyte (MCVL), in Colorectal Adenocarcinoma

Background: Colorectal cancer affects a large number of patients worldwide, with numerous factors being involved in its etiopathogenesis and chronic inflammation playing an essential role in tumor development. In this study, we analyzed and compared several markers of inflammation that are relatively easy to obtain for a rapid and accurate diagnosis and prognosis. Methods: This study included 219 patients diagnosed with colorectal cancer, analyzing the inflammation scores derived from their blood cells and inflammatory circulating proteins. These inflammatory markers are neutrophil-to-lymphocyte ratio-NLR; platelet-to-lymphocyte ratio-PLR; lymphocyte-to-monocyte ratio-LMR; systemic immune inflammation index-SII; systemic inflammatory response index-SIRI; aggregate index of systemic inflammation-AISI; derived neutrophil-to-lymphocyte ratio-dNLR; C-reactive protein-to-albumin ratio-CAR; and fibrinogen-to-albumin ratio-FAR. In the analysis of patients with colorectal cancer, we have also introduced two new recently developed inflammatory markers: the cumulative inflammatory index (IIC) and the ratio between the mean corpuscular volume and lymphocytes (MCVL). This study aimed to correlate the inflammatory markers' levels with the colorectal cancer diagnostic stage, the tumor and clinical characteristics of the colorectal cancer patients, and 36 months' survival time and to evaluate the diagnostic and prognostic capacity and accuracy of these inflammatory markers in this type of cancer. Results: We showed that the levels of the analyzed inflammation markers correlate with the TNM stage, the tumor pathological differentiation grade, the age and gender of the patients, and overall survival, with their increased levels being associated with a lower survival rate. Conclusions: The analyzed markers, which are easy to perform right from the patient's admission, can be helpful both in diagnosis and, mostly, in prognosis, sustaining the role of inflammation in cancer. By comparing them, we showed which one can be useful for increased sensitivity and specificity in the diagnosis and prognosis of colorectal cancer patients.

Significant association between systemic inflammation response index and prognosis in patients with urological malignancies

Background

The systemic inflammation response index (SIRI) as an immune marker, is associated with prognosis of urological malignancies(UM). However, the conclusion remains controversial. Therefore, the objective of this study was to conduct a meta-analysis to comprehensively evaluate the predictive value of SIRI in patients with UM.

Methods

A comprehensive search of PubMed, Web of Science, and EMBASE databases was performed for articles investigating the association between SIRI and UM. The search deadline was August 28, 2024. Survival outcome such as overall survival (OS), disease-free survival (DFS), progression-free survival (PFS), and recurrence-free survival (RFS) were analyzed.

Results

15 studies from 13 articles involving 4985 patients were included in the meta-analysis. The results showed that increased SIRI was associated with poorer OS (HR: 2.16, 95% CI: 1.61-2.89) and DFS/PFS/RFS (HR: 3.56, 95% CI: 1.41-8.99). Subgroup analysis further confirmed the prognostic value of SIRI in urinary system cancer.

Peripheral blood immunoinflammatory biomarkers: prospective predictors of postoperative long-term survival and chronic postsurgical pain in breast cancer

Background

Tumor progression and chronic postsurgical pain (CPSP) in patients with breast cancer are both significantly influenced by inflammation. The associations between immunoinflammatory biomarkers and long-term survival, as well as CPSP, remain ambiguous. This study examined the predictive value of immunoinflammatory biomarkers for both long-term survival and CPSP.

Methods

Data on the clinicopathological characteristics and perioperative peripheral blood immunoinflammatory biomarkers of 80 patients who underwent breast cancer surgery were retrospectively collected. Optimal cut-off values for preoperative immunoinflammatory biomarkers, including the preoperative systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), and pan-immune-inflammation value (PIV), were established via receiver operating characteristic (ROC) curves. Kaplan-Meier curves and Cox regression analysis were used to evaluate the relationships between preoperative immunoinflammatory biomarkers and long-term survival. The relationships among the perioperative neutrophil count (NEU), monocyte count (MONO), lymphocyte count (LYM), platelet count (PLT), SII, SIRI, NLR, PIV, dynamic changes in peripheral blood cell counts, and CPSP were further assessed using logistic regression analysis.

Results

Kaplan-Meier curves revealed a considerable prolongation of disease-free survival (DFS) and overall survival (OS) in the low preoperative SII, SIRI, NLR, and PIV groups. Multivariate Cox regression analysis revealed that only an elevated preoperative SIRI was an independent risk factor for postoperative DFS (HR=8.890, P=0.038). The incidence of CPSP was 28.75%. Univariate logistic regression analysis revealed that body mass index (BMI), postoperative NEU, MONO, SIRI, and PIV were negatively correlated with the occurrence of CPSP, whereas subsequent multivariate logistic regression analysis revealed that only BMI was independently associated with CPSP (OR=0.262, P=0.023).

Conclusion

Elevated preoperative SIRI was an independent risk factor for poor DFS in breast cancer patients after surgery. In contrast, perioperative immunoinflammatory biomarkers had limited potential for predicting CPSP in patients who underwent breast cancer surgery.

Prognostic and clinicopathological value of systemic inflammation response index (SIRI) in patients with breast cancer: a meta-analysis

BACKGROUND

Many studies have explored the value of the systemic inflammation response index (SIRI) in predicting the prognosis of patients with breast cancer (BC); however, their findings remain controversial. Consequently, we performed the present meta-analysis to accurately identify the role of SIRI in predicting BC prognosis.

METHODS

PubMed, Embase, Cochrane Library, and Web of Science databases were comprehensively searched between their inception and February 10, 2024. The significance of SIRI in predicting overall survival (OS) and disease-free survival (DFS) in BC patients was analyzed by calculating pooled hazard ratios (HRs) and corresponding 95% confidence intervals (CIs).

RESULTS

Eight articles involving 2,997 patients with BC were enrolled in the present study. According to our combined analysis, a higher SIRI was markedly associated with dismal OS (HR = 2.43, 95%CI = 1.42-4.15, p < 0.001) but not poor DFS (HR = 2.59, 95%CI = 0.81-8.24, p = 0.107) in patients with BC. Moreover, based on the pooled results, a high SIRI was significantly related to T3-T4 stage (OR = 1.73, 95%CI = 1.40-2.14, p < 0.001), N1-N3 stage (OR = 1.61, 95%CI = 1.37-1.91, p < 0.001), TNM stage III (OR = 1.63, 95%CI = 1.34-1.98, p < 0.001), and poor differentiation (OR = 1.25, 95%CI = 1.02-1.52, p = 0.028).

CONCLUSION

According to our results, a high SIRI significantly predicted poor OS in patients with BC. Furthermore, elevated SIRI was also remarkably related to increased tumor size and later BC tumor stage. The SIRI can serve as a novel prognostic biomarker for patients with BC.

Comparison of multiple machine learning models for predicting prognosis of pancreatic ductal adenocarcinoma based on contrast-enhanced CT radiomics and clinical features

Objective

The aim of this study was to evaluate the prognostic potential of combining clinical features and radiomics with multiple machine learning (ML) algorithms in pancreatic ductal adenocarcinoma (PDAC).

Methods

A total of 116 patients with PDAC who met the eligibility criteria were randomly assigned to a training or validation cohort. Seven ML algorithms, including Supervised Principal Components, stepwise Cox, Random Survival Forest, CoxBoost, Least absolute shrinkage and selection operation (Lasso), Ridge, and Elastic network, were integrated into 43 algorithm combinations. Forty-three radiomics models were constructed separately using radiomics features extracted from arterial phase (AP), venous phase (VP), and combined arterial and venous phase (AP+VP) images. The concordance index (C-index) of each model was calculated. The model with the highest mean C-index was identified as the best model for calculating the radiomics score (Radscore). Univariate and multivariate Cox analyses were used to identify independent prognostic indicators and create a clinical model for prognosis prediction. The multivariable Cox regression was used to combine Radscore with clinical features to create a combined model. The efficacy of the model was evaluated using the C-index, calibration curves, and decision curve analysis (DCA).

Results

The model based on the Lasso+StepCox[both] algorithm constructed using AP+VP radiomics features showed the best predictive ability among the 114 radiomics models. The C-indices of the model in the training and validation cohorts were 0.742 and 0.722, respectively. Based on the results of the univariate and multivariate Cox regression analyses, sex, Tumor-Node-Metastasis (TNM) stage, and systemic inflammation response index were included to build the clinical model. The combined model, incorporating three clinical factors and AP+VP-Radscore, achieved the highest C-indices of 0.764 and 0.746 in the training and validation cohorts, respectively. In terms of preoperative prognosis prediction for PDAC, the calibration curve and DCA showed that the combined model had a good consistency and greatest net benefit.

Conclusion

A combined model of clinical features and AP+VP-Radscore screened using multiple ML algorithms has an excellent ability to predict the prognosis of PDAC and may provide a noninvasive and effective method for clinical decision-making.

ABO Blood Type and Pretreatment Systemic Inflammatory Response Index Associated with Lymph Node Metastasis in Patients with Breast Cancer

Background

Lymph node metastasis (LNM) is an important prognostic factor for breast cancer. Inflammatory stimulation can change tumor microenvironment and lead to LNM, but the relationship between LNM and peripheral immunoinflammatory indices has not been clarified in breast cancer.

Methods

The clinical information of 1918 patients with breast cancer admitted to Meizhou People's Hospital from October 2017 to December 2023 were retrospectively analyzed. The relationship of clinicopathological features (age, body mass index (BMI), ABO blood types, family history of cancer, tumor site, disease stage, LNM, distant metastasis, and molecular subtypes) and peripheral immunoinflammatory indices (pan-immune inflammation value (PIV), systemic immune inflammation index (SII), and system inflammation response index (SIRI)) were analyzed.

Results

There were 935 (48.7%) patients had no LNM and 983 (51.3%) had LNM. There were statistically significant differences in the distributions of ABO blood groups (p=0.022) and molecular subtypes (p<0.001) between the two groups. PIV, SII, and SIRI levels in patients with LNM were significantly higher than those without LNM (all p<0.05). The proportions of LNM in patients with high PIV, SII, and SIRI levels were higher than those with low PIV, SII, and SIRI levels, respectively. Logistic regression analysis showed that non-O blood type (non-O blood type vs O blood type, odds ratio (OR): 1.327, 95% confidence interval (CI): 1.056-1.667, p=0.015), luminal B subtype (luminal B vs luminal A, OR: 2.939, 95% CI: 2.147-4.022, p<0.001), HER2+ subtype (HER2+ vs luminal A, OR: 2.044, 95% CI: 1.388-3.009, p<0.001), and high SIRI level (≥0.875 vs <0.875, OR: 1.572, 95% CI: 1.092-2.265, p=0.015) were independently associated with LNM.

Conclusion

Non-O blood type, luminal B and HER2+ subtypes, and high SIRI level (≥0.875) have potential role in predicting the status of LNM in breast cancer patients.

KRAS Gene Mutation Associated with Grade of Tumor Budding and Peripheral Immunoinflammatory Indices in Patients with Colorectal Cancer

Background

The efficacy of targeted therapy for colorectal cancer (CRC) is affected by hub genes of epidermal growth factor receptor (EGFR) signaling pathways, such as KRAS. Immune cell infiltration may lead to gene mutation, but the relationship between KRAS status and peripheral immune-inflammatory indices has not been clarified in CRC.

Methods

Clinical records of CRC patients were collected. The relationship between KRAS status and clinicopathological characteristics, peripheral immune-inflammatory indices (pan-immune inflammation value (PIV) (monocyte×neutrophil×platelet/lymphocyte), systemic immune inflammation index (SII) (platelet×neutrophil/lymphocyte), and system inflammation response index (SIRI) (monocyte×neutrophil/lymphocyte)) were analyzed.

Results

1033 CRC patients were collected, there were 514 (49.8%) patients with KRAS wild-type and 519 (50.2%) with KRAS mutation. Patients with KRAS mutation had higher proportions of female, III-IV stage, and lymph node metastasis and lower proportion of low grade of tumor budding (the presence of single tumor cells or small clusters of up to 5 cells in mesenchyma at the front of tumor invasion) than those with KRAS wild-type. The PIV, SII, and SIRI levels in KRAS mutation patients were significantly higher than those in KRAS wild-type patients. The proportion of aged ≥65 years old, dMMR, distant metastasis, and KRAS mutation were high in patients with high PIV, SII, and SIRI levels. Logistic regression analysis showed that non-low grade of tumor budding (odds ratio (OR): 1.970, 95% confidence interval (CI): 1.287-3.016, p=0.002), and high SII level (≥807.81 vs <807.81, OR: 1.915, 95% CI: 1.120-3.272, p=0.018) were independently associated with KRAS mutation.

Conclusion

Non-low grade of tumor budding, and high SII level were independently associated with KRAS mutation in CRC. It provides additional references for diagnosis and treatment options for patients with CRC.

Role of systemic immune-inflammatory index and systemic inflammatory response index in predicting the diagnosis of necrotizing pneumonia in children

BACKGROUND

Necrotizing pneumonia (NP) is a rare serious complication of community-acquired pneumonia (CAP) in children, which is characterized by a protracted course of the disease and a prolonged hospital stay. This study aimed to assess the role of systemic immune-inflammatory index and systemic inflammatory response index in predicting early lung necrotization in children with CAP.

METHODS

This study included all children hospitalized in Pediatric Pulmonology Unit, Tanta University, Egypt, with CAP between the ages of two months and 18 years. Systemic inflammatory indices, including the neutrophil/lymphocyte ratio (NLR), platelet/lymphocyte ratio (PLR), monocyte/lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), and systemic inflammation response index (SIRI), were calculated on patients' admission.

RESULTS

The study involved a total of 228 children, 42 patients had NP, 46 patients had parapneumonic effusion, and 140 patients had non-complicated CAP. Patients with NP were substantially younger (p = 0.002), stayed in the hospital longer (p < 0.001), had a longer duration of symptoms before hospital admission (p < 0.001), and had fever for a longer duration than those in the other groups (p < 0.001). Regarding the inflammatory ratios, patients with NP had significantly higher MLR, PLR, SII, and SIRI than those in the other groups (p = 0.020, p = 0.007, p = 0.001, p = 0.037, respectively). ROC curve analysis showed that the combined SII + SIRI + D-dimer showed the highest AUC with a good specificity in predicting the diagnosis of NP.

CONCLUSIONS

SII, SIRI, and D-dimer may be beneficial biomarkers for predicting the occurrence of NP in children when performed on patients' admission. In addition, it was found for the first time that combined SII + SIRI + D-dimer had a good sensitivity and specificity in the diagnosis of NP.

The Association of Pretreatment Systemic Immune Inflammatory Response Index (SII) and Neutrophil-to-Lymphocyte Ratio (NLR) with Lymph Node Metastasis in Patients with Papillary Thyroid Carcinoma

Objective

Immunoinflammatory response can participate in the development of cancer. To investigate the relationship between pretreatment systemic immune inflammatory response index (SII), systemic inflammatory response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and lymph node metastasis in patients with papillary thyroid carcinoma (PTC).

Methods

A retrospective analysis was performed on 547 PTC patients treated in Meizhou People's Hospital from January 2018 to December 2021. Clinicopathological data were collected, including gender, age, Hashimoto's thyroiditis, maximum tumor diameter, extra-membrane infiltration, disease stage, BRAF V600E mutation, pretreatment inflammatory index levels, and lymph node metastasis. The optimal cutoff values of SII, SIRI, NLR, PLR and LMR were calculated by receiver operating characteristic (ROC) curve, and the relationship between inflammatory indexes and other clinicopathological features and lymph node metastasis was analyzed.

Results

There were 303 (55.4%) PTC patients with lymph node metastasis. The levels of SII, SIRI, NLR, and PLR in patients with lymph node metastasis were significantly higher than those in patients without lymph node metastasis, while the levels of LMR were significantly lower than those in patients without lymph node metastasis (all p<0.05). When lymph node metastasis was taken as the endpoint, the critical value of SII was 625.375, the SIRI cutoff value was 0.705, the NLR cutoff value was 1.915 (all area under the ROC curve >0.6). The results of regression logistic analysis showed that age <55 years old (OR: 1.626, 95% CI: 1.009-2.623, p=0.046), maximum tumor diameter >1cm (OR: 2.681, 95% CI: 1.819-3.952, p<0.001), BRAF V600E mutation (OR: 2.709, 95% CI: 1.542-4.759, p=0.001), SII positive (≥625.375/<625.375, OR: 2.663, 95% CI: 1.560-4.546, p<0.001), and NLR positive (≥1.915/<1.915, OR: 1.808, 95% CI: 1.118-2.923, p=0.016) were independent risk factors for lymph node metastasis of PTC.

Conclusion

Age <55 years old, maximum tumor diameter >1cm, BRAF V600E mutation, SII positive, and NLR positive were independent risk factors for lymph node metastasis in PTC.

PD-1 Inhibitors Combined with Tyrosine Kinase Inhibitors with or without Hepatic Artery Infusion Chemotherapy for the First-Line Treatment of HBV-Related Advanced Hepatocellular Carcinoma: A Retrospective Study

Purpose

Comparing the efficacy and safety of programmed cell death protein-1 (PD-1) inhibitors combined with tyrosine kinase inhibitors (TKIs) with or without hepatic artery infusion chemotherapy (HAIC) in HBV-related advanced HCC and exploring prognostic predictors of the combined regimen.

Patients and Methods

A total of 194 patients diagnosed with HBV-related advanced HCC between 2020 and 2022 were included in the study, including 99 in the HAIC combined with PD-1 inhibitors plus TKIs (HPT group) and 95 in the PD-1 inhibitors plus TKIs (PT group). The efficacy was evaluated according to the tumor response rate and survival, and the safety was evaluated according to the adverse events.

Results

The HPT group showed higher overall response rate and disease control rate than the PT group. The median overall survival (OS) of the HPT group and the PT group were 18.10 months and 12.57 months, respectively, and the difference was statistically significant (hazard ratio (HR) = 0.519, 95% confidence interval (CI): 0.374-0.722, P < 0.001). The median progression-free survival (PFS) was 9.20 months in the HPT group and 6.33 months in the PT group (HR = 0.632, 95% CI: 0.470-0.851, P = 0.002). In addition, albumin bilirubin (ALBI) and systemic inflammatory response index (SIRI) are independent prognostic factors affecting HAIC combined with targeted immunotherapy and can be used as prognostic predictors. Almost all patients included in the study experienced treatment-related adverse events (TRAEs) of varying degrees of severity, with grade 1-2 adverse events predominating.

Conclusion

The HPT group had better OS and PFS than the PT group in patients with HBV-related advanced HCC. In addition, high ALBI and high SIRI were associated with poor prognosis in the HAIC combined group.

Prognostic and clinicopathological significance of systemic inflammation response index in patients with hepatocellular carcinoma: a systematic review and meta-analysis

Background

It is unclear whether the systemic inflammation response index (SIRI) can predict the prognosis of patients with hepatocellular carcinoma (HCC). Consequently, the present study focused on systematically identifying the relationship between SIRI and the prognosis of patients with HCC through a meta-analysis.

Methods

Systematic and comprehensive studies were retrieved from PubMed, Web of Science, Embase, and the Cochrane Library from their inception to August 10, 2023. The role of SIRI in predicting overall survival (OS) and progression-free survival (PFS) in HCC was determined using pooled hazard ratios (HRs) and 95% confidence intervals (CIs). Odds ratios (ORs) and 95% CIs were pooled to analyze the correlations between SIRI and the clinicopathological features of HCC.

Results

Ten articles involving 2,439 patients were included. An elevated SIRI was significantly associated with dismal OS (HR=1.75, 95% CI=1.52-2.01, p<0.001) and inferior PFS (HR=1.66, 95% CI=1.34-2.05, p<0.001) in patients with HCC. Additionally, according to the combined results, the increased SIRI was significantly related to multiple tumor numbers (OR=1.42, 95% CI=1.09-1.85, p=0.009) and maximum tumor diameter >5 cm (OR=3.06, 95% CI=1.76-5.30, p<0.001). However, the SIRI did not show any significant relationship with sex, alpha-fetoprotein content, Child-Pugh class, or hepatitis B virus infection.

Conclusion

According to our results, elevated SIRI significantly predicted OS and PFS in patients with HCC. Moreover, the SIRI was significantly associated with tumor aggressiveness.

Systematic review registration

https://inplasy.com/inplasy-2023-9-0003/, identifier INPLASY202390003.

Preoperative inflammation and nutrition-based comprehensive biomarker for predicting prognosis in resectable colorectal cancer

BACKGROUND

Colorectal cancer (CRC) remains a major global health concern, with significant morbidity and mortality rates. In this study, we aimed to develop a comprehensive blood indicator based on systemic inflammation and nutritional condition to predict the prognosis of resectable CRC patients.

METHODS

A retrospective cohort of 210 CRC patients who underwent radical resection at the First Affiliated Hospital of Chongqing Medical University, China, between January 2015 and December 2017, was included in the analysis. Baseline characteristics, preoperative blood markers, including neutrophil count, monocyte count, lymphocyte count, platelets, albumin, and CEA were retrospectively reviewed. Various blood indicators, such as NLR, PLR, MLR, SIRI and OPNI were calculated. The least absolute shrinkage and selection operator (LASSO) method was employed to select indicators to establish a novel comprehensive biomarker (named PSI). Kaplan-Meier survival curves and log-rank tests were used to evaluate the prognostic impact of preoperative OPNI, SIRI, and PSI. Univariate and multivariate Cox regression model were conducted to identify independent prognostic factors for CRC. The receiver operating characteristic (ROC) method assessed the predictive ability of PSI, stage, OPNI, and SIRI.

RESULTS

Patients with higher preoperative OPNI and lower SIRI values had significantly better overall survival (OS). PSI was identified as an independent prognostic factor for OS in both univariate and multivariate analysis. Patients with medium (28.3-43.4) and high (>43.4) PSI scores exhibited superior OS compared to those with low (≤ 28.3) PSI scores. PSI showed higher predictive ability (AUC: 0.734) than individual indicators alone (OPNI: 0.721, SIRI: 0.645, stage: 0.635).

CONCLUSION

The novel indicator, PSI, based on preoperative SIRI and OPNI, demonstrated significant prognostic value for resectable CRC patients. PSI outperformed individual indicators and could serve as a reliable tool for prognostic evaluation in CRC patients.

Prognostic value of systemic inflammation response index in hepatoblastoma patients receiving preoperative neoadjuvant chemotherapy

Introduction

Inflammation is closely associated with tumor development and patient prognosis. The objective of this study is to assess the prognostic value of the preoperative inflammatory indexes in pediatric hepatoblastoma patients who receive neoadjuvant chemotherapy.

Methods

A retrospective analysis was performed on clinical and pathological data of 199 hepatoblastoma patients who underwent hepatectomy with preoperative neoadjuvant chemotherapy from January 2015 to June 2020. The receiver operating characteristic curve was used to evaluate the prognostic value of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) in predicting OS and EFS. Patients were grouped based on optimal cutoff values of preoperative inflammatory indexes. Survival rates were calculated using the Kaplan-Meier method, and survival outcomes were compared between groups using the log-rank test. Univariate and multivariate Cox proportional hazards regression models were used to identify independent prognostic factors, and a nomogram was constructed using R software to predict the probability of OS.

Results

The receiver operating characteristic curve showed prognostic value for OS, not EFS, in preoperative inflammatory indexes. Patients were categorized into low/high groups: SII ≤ 266.70/higher, NLR ≤ 1.24/higher, PLR ≤ 85.25/higher, and SIRI ≤ 0.72/higher. High NLR, PLR, SII, and SIRI groups had significantly lower 5-year OS than their low counterparts (all p-value < 0.05). The Cox analysis identified four independent prognostic factors: SIRI (HR=2.997, 95% CI: 1.119-8.031), microvascular invasion (HR=2.556, 95% CI: 1.14-5.73), the post-treatment extent of disease (POSTTEXT) staging (IV vs. I: HR=244.204, 95% CI:11.306-5274.556), and alpha-fetoprotein (>100 ng/ml: HR=0.11, 95% CI: 0.032-0.381) for hepatoblastoma patients with neoadjuvant chemotherapy. High SIRI group had more patients with adverse NLR, SII, and POSTTEXT III (all p-value < 0.05). Independent prognostic factors led to an OS nomogram with a concordance index of 0.85 (95% CI: 0.78-0.91, p-value = 1.43e-27) and the calibration curve showed a good fit between the prediction curve and the true curve.

Conclusions

SIRI is an independent prognostic factor of hepatoblastoma patients receiving neoadjuvant chemotherapy. The OS nomogram based on SIRI, POSTTEXT staging, MiVI, and AFP can be used to assess the prognosis of those patients.

A Novel Albumin-Related Nutrition Biomarker Predicts Breast Cancer Prognosis in Neoadjuvant Chemotherapy: A Two-Center Cohort Study

BACKGROUND

Recently, there has been a growing focus on the prognostic significance of nutrition-related biomarkers. We attempted to explore the association between a novel albumin-related nutrition marker called "lymphocyte × albumin (LA)" and disease-free survival (DFS) in breast cancer patients undergoing neoadjuvant chemotherapy (NAC).

METHODS

In total, 711 non-metastatic breast cancer patients who underwent NAC at two medical centers were retrospectively analyzed. We performed least absolute shrinkage and selection operator (LASSO) Cox regression analysis as well as multivariate Cox regression analyses to identify the variables associated with DFS and to establish a predictive nomogram.

RESULTS

The nomogram incorporated four variables based on the multivariate analysis of DFS in the training cohort: LA, ypN stage, ypT stage, and hormone receptor status. In comparison with the traditional TNM staging system, the nomogram demonstrated superior discrimination, calibration ability, and clinical usefulness in both the training set and internal and external validation sets. Furthermore, patients stratified into different risk groups resulted in significant differences in DFS.

CONCLUSIONS

LA is an independent prognostic biomarker, and LA-based prognostic nomogram offers a more precise assessment of DFS for breast cancer patients treated with NAC, potentially serving as a valuable tool for personalized prognostic predictions.

Systemic inflammatory indices for predicting prognosis of myelofibrosis

The impact of inflammatory markers such as systemic immune-inflammation (SII) index and systemic inflammation response index (SIRI) on myelofibrosis (MF) prognosis was evaluated for the first time in this study. Data from 60 patients diagnosed with MF between March 2011 and September 2022 were retrospectively analyzed. In addition to disease-related markers, the impact of SII and SIRI on prognosis was evaluated. In our study, the overall median survival (OS) was 64 months. OS was significantly shorter in patients older than 65 years, with high ferritin and lymphocyte levels, transfusion dependence at diagnosis, platelet count below 100 × 109/L, Hb level below 8 g/dl, and high risk according to the dynamic international prognostic scoring system (DIPSS)-Plus score. When these variables were included in the multivariate Cox regression model, it was found that being older than 65 years, having a high ferritin value, being at high risk according to the DIPSS-plus score and Hb values below 8 increased the risk of death. Platelet-to-lymphocyte ratio (PLR) and SII index were lower in patients with a fatal outcome. No statistically significant relationship was found between SIRI and mortality. The findings of this study showed that low PLR and high ferritin were associated with poor prognosis in MF. Elevated SII and SIRI, evaluated for the first time in patients with myelofibrosis, did not predict prognosis. Since non-inflammatory variables play a role in the pathogenesis of MF, bone marrow indicators and systemic inflammation indicators derived from hematologic parameters may not be accurate.

A nonlinear relationship between systemic inflammation response index and short-term mortality in patients with acute myocardial infarction: a retrospective study from MIMIC-IV

Background

This investigation aimed to evaluate the efficacy of the Systemic Inflammatory Response Index (SIRI) in prognosticating short-term all-cause mortality among patients diagnosed with acute myocardial infarction (AMI) in the intensive care unit (ICU).

Methods and Results

Clinical data were obtained from the Medical Information Mart for Intensive Care-IV (MIMIC-IV) database. A total of 4,291 patients were included in the cohort. Results from multivariate regression analyses showed that the quartile of the natural logarithm of SIRI (ln-SIRI) was independently associated with mortality. Compared to patients in the first quartile (Q1), patients in the second quartile (Q2) and fourth quartile (Q4) were significantly associated with an increased risk of 30-day (HR = 2.031, 95% CI: 1.604-2.571, p < 0.001 and HR = 1.703, 95% CI: 1.32-2.195, p < 0.001) and 90-day all-cause mortality (HR = 2.063, 95% CI: 1.68-2.532, p < 0.001 and HR = 1.788, 95% CI: 1.435-2.227, p < 0.001), which is consistent with the results of the Kaplan-Meier analysis and the results of multivariate regression analyses by classifying into 12 groups based on dodeciles of SIRI. Curve fitting showed a curvilinear relationship and further threshold saturation effects showed that, for 90-day mortality, each unit increased in ln-SIRI, when the ln-SIRI level is less than 2.9, the patient's mortality increases by 23.2% (OR: 1.232; 95% CI: 1.111-1.367; p < 0.001); when the ln-SIRI is greater than 2.9 and less than 4.6, the patient's mortality decreases by 44.4% (OR: 0.554; 95% CI: 0.392-0.789; p = 0.001); when ln SIR > 4.6, the patient's mortality increases by 24.7% (OR: 1.247; 95% CI: 1.108-1.404; p < 0.001). Moreover, the length of stay in the hospital was lower in patients in the third quartile (Q3) (coefficient: -1.999; 95% CI: -2.834 - -1.165, p < 0.001). The length of stay in the ICU was higher in patients in Q2 and Q4 (coefficient: 0.685;95% CI: 0.243-1.128; p = 0.0024 and coefficient: 0.989;95% CI: 0.528-1.451; p < 0.001). Furthermore, SIRI may outperform NLR in predicting short-term mortality.

Conclusion

SIRI is an independent risk factor for 30- and 90-day mortality, and length of stay in ICU for critical AMI patients.

High preoperative CEA and systemic inflammation response index (C-SIRI) predict unfavorable survival of resectable colorectal cancer

BACKGROUND

CEA and systemic inflammation were reported to correlate with proliferation, invasion, and metastasis of colorectal cancer. This study investigated the prognostic significance of the preoperative CEA and systemic inflammation response index (C-SIRI) in patients with resectable colorectal cancer.

METHODS

Two hundred seventeen CRC patients were recruited from Chongqing Medical University, the first affiliated hospital, between January 2015 and December 2017. Baseline characteristics, preoperative CEA level, and peripheral monocyte, neutrophil, and lymphocyte counts were retrospectively reviewed. The optimal cutoff value for SIRI was defined as 1.1, and for CEA, the best cutoff values were 4.1 ng/l and 13.0 ng/l. Patients with low levels of CEA (< 4.1 ng/l) and SIRI (< 1.1) were assigned a value of 0, those with high levels of CEA (≥ 13.0 ng/l) and SIRI (≥ 1.1) were assigned a value of 3, and those with CEA (4.1-13.0 ng/l) and SIRI (≥ 1.1), CEA (≥ 13.0 ng/l), and SIRI (< 1.1) were assigned a value of 2. Those with CEA (< 4.1 ng/l) and SIRI (≥ 1.1) and CEA (4.1-13.0 ng/l) and SIRI (< 1.1) were assigned a value of 1. The prognostic value was assessed based on univariate and multivariate survival analysis.

RESULTS

Preoperative C-SIRI was statistically correlated with gender, site, stage, CEA, OPNI, NLR, PLR, and MLR. However, no difference was observed between C-SIRI and age, BMI, family history of cancer, adjuvant therapy, and AGR groups. Among these indicators, the correlation between PLR and NLR is the strongest. In addition, high preoperative C-SIRI was significantly correlated with poorer overall survival (OS) (HR: 2.782, 95% CI: 1.630-4.746, P < 0.001) based on univariate survival analysis. Moreover, it remained an independent predictor for OS (HR: 2.563, 95% CI: 1.419-4.628, p = 0.002) in multivariate Cox regression analysis.

CONCLUSION

Our study showed that preoperative C-SIRI could serve as a significant prognostic biomarker in patients with resectable colorectal cancer.

The response prediction and prognostic values of systemic inflammation response index in patients with advanced lung adenocarcinoma

PURPOSE

This study aimed to assess the response prediction and prognostic values of different peripheral blood cell biomarkers for advanced lung adenocarcinoma (LUAD) patients receiving first-line therapy.

METHODS

Patients diagnosed with advanced LUAD as well as healthy controls and patients with benign pulmonary diseases were collected in this retrospective study. Propensity score matching (PSM) was performed in a 1:1 ratio. Survival state was estimated by the Kaplan-Meier method and the Cox proportional hazard model was used to assess the prognostic factors.

RESULTS

Compared with the control groups, the level of peripheral blood leucocyte, neutrophil, monocyte, platelet, and neutrophil to lymphocyte ratio, monocyte to lymphocyte ratio, platelet to lymphocyte ratio, and systemic inflammation response index (SIRI) were higher in LUAD patients (all p < 0.001). Some inflammatory markers decreased at the time of optimal response and then increased again as the disease progressed. Multivariate analysis revealed that SIRI and lactate dehydrogenase (LDH) were independent prognostic factors no matter before or after PSM analysis. Area under the curve (AUC) of SIRI and LDH were 0.625 (p < 0.001) and 0.596 (p = 0.008), respectively. When SIRI and LDH were combined, the AUC reached 0.649 (p < 0.001).

CONCLUSIONS

Pretreatment SIRI was an independent prognostic factor of progression free survival (PFS) in advanced LUAD patients. Dynamic monitoring of inflammatory index changes could help to predict therapeutic efficacy. The combination of SIRI and LDH is expected to be a promising clinically accessible biomarker in the future.

Role of Systemic Inflammatory Indices in the Prediction of Moderate to Severe Bronchopulmonary Dysplasia in Preterm Infants

INTRODUCTION

The role of systemic inflammatory indices in the diagnosis of bronchopulmonary dysplasia (BPD) is unknown. The aim of the study was to determine the possible clinical utility of systemic inflammatory indices in the prediction of moderate to severe BPD.

METHODS

Premature infants<32 weeks of gestational age were included in the study. Neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), pan-immune-inflammation value (PIV), and systemic inflammation response index (SIRI) were calculated at birth and at the time of diagnosis of BPD (at 36th weeks of postmenstrual age). The patients were divided into two groups as no or mild BPD and moderate or severe BPD.

RESULTS

A total of 1146 infants were included in the study, 957 in Group 1 and 189 in Group 2. The SIRI value was significantly higher in moderate or severe BPD both at birth and at the 36th week of postmenstrual age (p<0.001 and p<0.001, respectively). The AUC value of SIRI was 0.809 and the cut-off value was>0.98 in the predictivity of BPD at birth. The AUC value of SIRI was 0.842 and the cut-off value was>1.33 for the diagnosis of BPD at 36th week of postmenstrual age. After multiple logistic regression analysis, SIRI was shown to be a significant parameter for the diagnosis of BPD (OR 2.847, 95% CI 1.557-4.875).

CONCLUSIONS

SIRI may be a useful biomarker for predicting moderate to severe BPD and a marker of clinical importance in the follow-up of infants with BPD.

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.

Controlling Nutritional Status (CONUT) as a Novel Postoperative Prognostic Marker in Breast Cancer Patients: A Retrospective Study

PURPOSE

This investigation seeks to elucidate the potential prognostic significance as well as the clinical utility of the controlling nutritional status (CONUT) score in breast cancer patients.

METHODS

Breast cancer patients managed in our center between January 2010 and December 2016 were recruited for our study. They comprised 187 patients who did not undergo neoadjuvant chemotherapy and 194 who did. A receiver operating characteristic curve (ROC) was utilized in identifying the ideal cut-off CONUT value. This cut-off score was then used to reclassify patients into those with high CONUT scores (≥1) and low CONUT scores (<1). The outcomes were analyzed by statistical methods.

RESULTS

Univariate and multivariate Cox regression survival analyses revealed that a CONUT score cut-off of 1 was able to significantly predict duration of disease-free survival (DFS) (p < 0.001; hazard ratio [HR]: 3.184; 95% CI: 1.786-5.677; and p < 0.001; HR: 2.465; 95% CI: 1.642-3.700) and overall survival (OS) (p < 0.001; HR: 2.326; 95% CI: 1.578-3.429; and p < 0.001; HR: 2.775; 95% CI: 1.791-4.300). The mean DFS and OS in those with lower CONUT scores were 41.59 (95% CI: 37.66-45.51 months) and 77.34 months (95% CI: 71.79-82.90 months), respectively. On the other hand, the average DFS and OS for all individuals in the raised CONUT score group were 39.18 (95% CI: 34.41-43.95 months) and 71.30 months (95% CI: 65.47-77.12 months), respectively. Moreover, Kaplan-Meier survival analysis revealed that those in the raised CONUT score cohort had remarkably worse DFS and OS survival rates compared to individuals in the low CONUT score cohort (Log-rank test, DFS: χ 2 = 12.900, p = 0.0003, and OS: χ 2 = 16.270, p < 0.0001).

CONCLUSION

The survival times of breast cancer patients may be reliably predicted using the CONUT score. This score is an easy, convenient, readily accessible, and clinically significant means of prognosticating patients with breast cancer.