Predictive value of preoperative inflammatory indexes for postoperative early recurrence of hepatitis B-related hepatocellular carcinoma

SII as a predictor of mortality in patients with non-ST-segment elevation myocardial infarction and diabetes mellitus

Background

Systemic immune inflammation index (SII) is an innovative marker reflecting immune and inflammatory responses.

Objectives

To explore the predictive value of SII on the risk of death in patients with NSTEMI combined with T2DM.

Methods

An analysis of 448 patients with NSTEMI and T2DM admitted to our institution between December 2017 and May 2022 was conducted in this retrospective study. SII values were used to divide patients into high and low SII groups and investigate their impact on mortality.

Results

According to the analysis results, elevated SII levels are significantly linked to a poor prognosis in patients with NSTEMI and T2DM. Over an average follow-up period of 22.75 months, 106 (23.7 %) all-cause deaths were recorded. The optimal threshold for predicting death was found to be an SII value of 1384.596 × 109/L through ROC curve analysis. Kaplan-Meier analysis indicated that the survival rates were higher in the low SII group compared to the high SII group (P < 0.001). Elevated SII levels were independently linked to increased mortality in patients with NSTEMI and T2DM, according to univariate (HR:3.19, 95 % Cl: 2.18-4.68) and multivariate COX (HR: 2.72, 95 % Cl: 1.81-4.09) regression analyses.

Conclusion

High SII values were strongly associated with mortality in patients with NSTEMI and T2DM. SII serves as a valuable prognostic tool, enhancing the management and prognosis of patients with concurrent NSTEMI and T2DM.

A CECT-Based Radiomics Nomogram Predicts the Overall Survival of Patients with Hepatocellular Carcinoma After Surgical Resection

Objective: The primary objective of this study was to develop and validate a predictive nomogram that integrates radiomic features derived from contrast-enhanced computed tomography (CECT) images with clinical variables to predict overall survival (OS) in patients with hepatocellular carcinoma (HCC) after surgical resection. Methods: This retrospective study analyzed the preoperative enhanced CT images and clinical data of 202 patients with HCC who underwent surgical resection at the Affiliated Hospital of North Sichuan Medical College (Institution 1) from June 2017 to June 2021 and at Nanchong Central Hospital (Institution 2) from June 2020 to June 2022. Among these patients, 162 patients from Institution 1 were randomly divided into a training cohort (112 patients) and an internal validation cohort (50 patients) at a 7:3 ratio, whereas 40 patients from Institution 2 were assigned as an independent external validation cohort. Univariate and multivariate Cox proportional hazards regression analyses were performed to identify clinical risk factors associated with OS after HCC resection. Using 3D-Slicer software, tumor lesions were manually delineated slice by slice on preoperative non-contrast-enhanced (NCE) CT, arterial phase (AP), and portal venous phase (PVP) images to generate volumetric regions of interest (VOIs). Radiomic features were subsequently extracted from these VOIs. LASSO Cox regression analysis was employed for dimensionality reduction and feature selection, culminating in the construction of a radiomic signature (Radscore). Cox proportional hazards regression models, including a clinical model, a radiomic model, and a radiomic-clinical model, were subsequently developed for OS prediction. The predictive performance of these models was assessed via the concordance index (C-index) and time-ROC curves. The optimal performance model was further visualized as a nomogram, and its predictive accuracy was evaluated via calibration curves and decision curve analysis (DCA). Finally, the risk factors in the optimal performance model were interpreted via Shapley additive explanations (SHAP). Results: Univariate and multivariate Cox regression analyses revealed that BCLC stage, the albumin-bilirubin index (ALBI), and the NLR-PLR score were independent predictors of OS after HCC resection. Among these three models, the radiomic-clinical model exhibited the highest predictive performance, with C-indices of 0.789, 0.726, and 0.764 in the training, internal and external validation cohorts, respectively. Furthermore, the time-ROC curves for the radiomic-clinical model showed 1-year and 3-year AUCs of 0.837 and 0.845 in the training cohort, 0.801 and 0.880 in the internal validation cohort, and 0.773 and 0.840 in the external validation cohort. Calibration curves and DCA demonstrated the model's excellent calibration and clinical applicability. Conclusions: The nomogram combining CECT radiomic features and clinical variables provides an accurate prediction of OS after HCC resection. This model is beneficial for clinicians in developing individualized treatment strategies for patients with HCC.

The Role of the Systemic Immune-Inflammation Index in Predicting Postoperative Complications in Ovarian Cancer Patients: A Retrospective Cohort Study

OBJECTIVE

Cytoreductive surgery (CRS) is the most important treatment method that increases survival in advanced-stage ovarian cancer (OC) patients. However, complications after CRS are seen as a significant cause of morbidity and mortality. Preoperative risk assessment of patients is of great importance. In recent years, inflammatory markers have been the subject of many studies evaluating malignancy and surgical outcomes. Ca125, Neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), Monocyte-lymphocyte ratio (MLR), systemic inflammation index (SII), and systemic inflammatory response index (SIRI) stand out as prognostic and predictive tools in malignancies. This study aims to evaluate the preoperative inflammatory markers in patients who underwent CRS for advanced-stage epithelial ovarian cancer and to investigate the predictive power of postoperative complications.

MATERIALS AND METHODS

This retrospective study examines patients who underwent CRS due to advanced-stage epithelial OC at Sakarya University Training and Research Hospital between 2014 and 2023. Postoperative complications of the patients were graded according to the Clavien-Dindo classification (CDC); Ca125, NLR, PLR, SII, SIRI and MLR values were calculated using preoperative laboratory data, and the predictive values of inflammatory markers were analysed with ROC curves.

RESULTS

A significant relationship was found between complications with CDC ≥ 3 and NLR, PLR, MLR, SII, and SIRI. The AUC value of SII was calculated as 0.740 (p < 0.001), NLR as 0.719 (p = 0.001), PLR as 0.668 (p = 0.011), and SIRI as 0.651 (p = 0.022). SII stands out as the marker with the highest predictive power. SII is a strong marker in predicting postoperative complications, especially in advanced-stage OC patients.

CONCLUSIONS

It was shown that preoperative inflammation markers may be an effective method for predicting postoperative complications in advanced-stage OC patients undergoing CRS. These findings may contribute to optimising surgical management and reducing complications. In future studies, these markers should be evaluated in groups with more patients, and their predictive power should be investigated.

Construction and validation of a novel liver function-tumor burden-inflammation-nutrition (LTIN) score for HCC patients underwent hepatectomy

OBJECTIVE

Liver function, tumor burden, inflammation level, and nutritional status are critical factors influencing tumor onset, progression, and metastasis. This study sought to investigate the prognostic significance and clinical relevance of biomarkers associated with these factors to develop a novel liver function-tumor burden-inflammation-nutrition (LTIN) score for patients with hepatocellular carcinoma (HCC) who received hepatectomy.

METHODS

A retrospective analysis was conducted on 285 patients with HCC undergoing hepatectomy at two medical centers between July 2019 and July 2023. The patients were divided into a training set (n = 200) and a validation set (n = 85). The study evaluated the prognostic significance of eight relevant clinical indicators and developed an LTIN score using Least Absolute Shrinkage and Selection Operator (LASSO) regression. Kaplan-Meier survival curves and multivariate Cox regression analysis were utilized to determine the prognostic value of the LTIN score. Time-dependent receiver operating characteristic (ROC) analyses were used to compare the predictive performance of various prognostic factors.

RESULTS

The LTIN score, derived from the albumin-bilirubin (ALBI) grade, tumor burden score (TBS), prognostic nutritional index (PNI), and prognostic inflammatory index (PII), effectively classified patients into high- and low-risk groups based on the optimal cut-off value. Patients with low-risk scores exhibited significantly better overall survival (OS) and recurrence-free survival (RFS) than those with high-risk groups in both the training and validation sets (P < 0.001). Furthermore, the LTIN score was identified as a significant independent prognostic factor for both OS (P < 0.001) and RFS (P < 0.001). The LTIN score also exhibited superior prognostic capabilities compared to the other indicators, Tumor-Node-Metastasis (TNM) staging system, and Barcelona Clinic Liver Cancer (BCLC) staging system.

CONCLUSION

Our findings indicated that the preoperative LTIN score has significant potential as a reliable predictor of OS and RFS for HCC patients underwent radical surgery. The LTIN score could further effectively guide treatment decisions and optimize follow-up strategies to enhance patients prognosis.

Changes in systemic immune-inflammation index (SII) predict the prognosis of patients with hepatitis B-related hepatocellular carcinoma treated with lenvatinib plus PD-1 inhibitors

PURPOSE

This study aimed to evaluate the prognostic significance of changes in inflammatory markers in patients with Hepatitis B virus-related hepatocellular carcinoma (HBV-HCC) treated with first-line lenvatinib plus a programmed cell death protein 1 (PD-1) inhibitor.

METHODS

This study retrospectively included 117 HBV-HCC patients treated with first-line lenvatinib in combination with a PD-1 inhibitor. Independent factors affecting progression-free survival (PFS) and overall survival (OS) were explored based on baseline indicators and inflammatory markers changes after one treatment cycle.

RESULTS

Multivariate analysis revealed that an alpha-fetoprotein (AFP) level ⩾ 400 ng/mL [hazard ratio (HR), 1.69; 95% confidence interval (CI), 1.11-2.58; P = 0.01] was identified as an independent risk factor, platelet-to-neutrophil ratio (PNR) ⩽ 65.43 (HR 0.50; 95% CI 0.30-0.84; P < 0.01 ) and SII ⩽ 539.47 (HR 0.54; 95% CI 0.30-0.96; P = 0.03) were identified as independent protective factors for PFS. Additionally, multivariate analysis demonstrated that AFP ⩾ 400 ng/mL, HBV-HCC patients with diabetes mellitus (DM), and SII > 303.66 were independent risk factors of OS. The patients whose SII had increased after one cycle of treatment showed a poorer PFS (HR 1.61; 95 %CI 1.10-2.37; P = 0.015) and OS (HR 1.76; 95 % CI 1.15-2.70; P = 0.009) than patients whose SII had decreased. The objective response rate (ORR) was higher in the SII-decreased patients (47.5% vs 32.5%, P = 0.11). Mann-Whitney test found a significant difference in therapeutic response between the SII-increased patients and the SII-decreased patients (P = 0.04).

CONCLUSION

SII can be associated with outcomes in patients with HBV-HCC treated with first-line lenvatinib plus PD-1 inhibitors.

Predicting post-hepatectomy liver failure using a nomogram based on portal vein width, inflammatory indices, and the albumin-bilirubin score

BACKGROUND

Post-hepatectomy liver failure (PHLF) after liver resection is one of the main complications causing postoperative death in patients with hepatocellular carcinoma (HCC). It is crucial to help clinicians identify potential high-risk PHLF patients as early as possible through preoperative evaluation.

AIM

To identify risk factors for PHLF and develop a prediction model.

METHODS

This study included 248 patients with HCC at The Second Affiliated Hospital of Air Force Medical University between January 2014 and December 2023; these patients were divided into a training group (n = 164) and a validation group (n = 84) via random sampling. The independent variables for the occurrence of PHLF were identified by univariate and multivariate analyses and visualized as nomograms. Ultimately, comparisons were made with traditional models via receiver operating characteristic (ROC) curves, calibration curves, and decision curve analysis (DCA).

RESULTS

In this study, portal vein width [odds ratio (OR) = 1.603, 95%CI: 1.288-1.994, P ≤ 0.001], the preoperative neutrophil-to-lymphocyte ratio (NLR) (OR = 1.495, 95%CI: 1.126-1.984, P = 0.005), and the albumin-bilirubin (ALBI) score (OR = 8.868, 95%CI: 2.144-36.678, P = 0.003) were independent risk factors for PHLF. A nomogram prediction model was developed using these factors. ROC and DCA analyses revealed that the predictive efficacy and clinical value of this model were better than those of traditional models.

CONCLUSION

A new Nomogram model for predicting PHLF in HCC patients was successfully established based on portal vein width, the NLR, and the ALBI score, which outperforms the traditional model.

MRI Features and Neutrophil-to-Lymphocyte Ratio (NLR)-Based Nomogram to Predict Prognosis of Microvascular Invasion-Negative Hepatocellular Carcinoma

Purpose

This study aimed to develop a novel nomogram to predict recurrence-free survival (RFS) for microvascular invasion (MVI)-negative hepatocellular carcinoma (HCC) patients after curative resection.

Patients and Methods

A total of 143 pathologically confirmed MVI-negative HCC patients were analyzed retrospectively. Baseline MRI features and inflammatory markers were collected. We used univariable and multivariable Cox regression analysis to identify the independent risk factors for RFS. And we established a nomogram based on significant MRI features and inflammatory marker. The receiver operating characteristic (ROC) curve, concordance index (C-index) and calibration curve were used to evaluate the predictive accuracy and discriminative ability of the nomogram. The decision curve analysis (DCA) was performed to validate the clinical utility of the nomogram.

Results

In multivariate Cox regression analysis, neutrophil-to-lymphocyte ratio (NLR) (P = 0.018), tumor size (P = 0.002), and tumor capsule (P = 0.000) were independent significant variables associated with RFS. Nomogram with independent factors was developed and achieved a good C-index of 0.730 (95% confidence interval [CI]: 0.656-0.804) for predicting RFS. In ROC analysis, the areas under curve of the nomogram for 1-, 3- and 5-year RFS prediction were 0.725, 0.784 and 0.798, respectively. The risk score calculated by nomogram could divide MVI-negative HCC patients into high-risk group or low-risk group (P < 0.0001). DCA analysis revealed that the nomogram could increase net benefit and exhibited a wider range of threshold probabilities by the risk stratification than the independent risk factors in the prediction of MVI-negative HCC recurrence.

Conclusion

The nomogram prognostic model based on MRI features and NLR for predicting RFS showed high accuracy in MVI-negative HCC patients after curative resection. It can help clinicians make treatment decisions for MVI-negative HCC patients and identify high-risk patients for timely intervention.

The prognostic value of systemic inflammation response index in digestive system carcinomas: a systematic review and meta-analysis

BACKGROUND

Digestive system carcinomas (DSC) constitute a significant proportion of solid tumors, with incidence rates rising steadily each year. The systemic inflammation response index (SIRI) has been identified as a potential prognostic marker for survival in various types DSC. This meta-analysis aimed to evaluate the prognostic value of SIRI in patients with DSC.

METHODS

We conducted a comprehensive literature search of PubMed, Web of Science Core Collection, Embase, and Cochrane Library databases, searching for studies published from inception to May 30, 2023. Eligible studies included cohort studies that assessed the association between pre-treatment SIRI levels and DSC prognosis. We extracted and synthesized hazard ratios (HRs) and 95% confidence intervals (CIs) using STATA/SE 12.0, stratifying HRs based on univariable and multivariable analysis. Due to substantial heterogeneity, we applied a random-effect model for all pooled analyses. The primary outcome of interest was the overall survival (OS), while secondary outcomes included progression-free survival (PFS), disease-free survival (DFS), time to progression (TTP), and disease specific survival (DSS). Publication bias was evaluated using Begg's test and Egger's tests.

RESULTS

A total of 34 cohort studies encompassing 9628 participants were included in this meta-analysis. Notable heterogeneity was observedin the OS (I2 = 76.5%, p < 0.001) and PFS (I2 = 82.8%, p = 0.001) subgroups, whereas no significant heterogeneity was detected in the DFS, TTP, and DSS subgroups. Elevated SIRI was found to be significantly associated with shorter OS (HR = 1.98, 95% CI: 1.70-2.30, tau2 = 0.0966) and poorer PFS (HR = 2.36, 95% CI: 1.58-3.53, tau2 = 0.1319), DFS (HR = 1.80, 95% CI: 1.61-2.01, tau2 < 0.0001), TTP (HR = 2.03, 95% CI: 1.47-2.81, tau2 = 0.0232), and DSS (HR = 1.99, 95% CI: 1.46-2.72, tau2 < 0.0001). Furthermore, an increase in SIRI following treatment was linked to reduced OS, TTP, and DFS, while a decrease in SIRI post-treatment corresponded with improved OS, TTP, and DFS compared to baseline levels.

CONCLUSIONS

Elevated SIRI is associated with poorer clinical outcomes in patients with DSC. This index may serve as a valuable prognostic biomarker, offering a promising tool for predicting survival in DSC patients.

PROSPERO

REGISTRATION NUMBER: CRD42023430962.

The prognostic impact of 1q21 gain/amplification in newly diagnosed multiple myeloma: a retrospective study based on a single center in China

1q21gain/amp is the most common in patients with multiple myeloma. However, there is limited research on the prognostic heterogeneity of 1q21+, and the prognostic of the 1q21 copy remains controversial. In this study, we primarily conducted a retrospective analysis of the prognostic significance of 1q21 gain/amp in 375 newly diagnosed multiple myeloma patients. 1q21 + was detected in 164 (43.7%) patients, including 103 (27.5%) with 3 copies and 61 (16.3%) with ≥ 4 copies. Patients with 1q21 + were more likely to be accompanied by anemia, hypercalcemia, t(4;14), and t(14;16). Compared with 1q21-, the progression-free survival (PFS) and overall survival (OS) of 1q21 + are shorter(p <0.0001; p = 0.036). The PFS of 1q21 amp was shorter than 1q21 gain (p = 0.0072). When accompanied by other high-risk abnormalities, 1q21 + was associated with earlier disease progression (all p<0.05). There were no significant differences in survival outcomes among patients with 1q21 gain alone, 1q21 amp alone, and FISH-. Autologous stem cell transplantation can prolong the survival of 1q21 + patients (p = 0.00062). A predictive scoring system based on 1q21 gain, 1q21 amp, del(17p), t(14;16), ISS II/III, and high LDH categorizes patients into three groups: low-risk (44.8%), intermediate-risk (38.9%), and high-risk (16.3%) (p < 0.0001; p < 0.0001). 1q21 + showed a relatively poor prognosis when coexisted with other high-risk cytogenetic abnormalities, especially 1q21 amp. The risk scoring system based on 1q21 copies is a potential risk stratification tool for multiple myeloma.

Prognostic value of preoperative systemic immune-inflammation index/albumin for patients with hepatocellular carcinoma undergoing curative resection

BACKGROUND

Hepatocellular carcinoma (HCC) is a major factor for cancer-associated mortality globally. Although the systemic immune-inflammation index (SII) and albumin (ALB) show individual prognostic value for various cancers, their combined significance (SII/ALB) in HCC patients undergoing curative hepatectomy is still unknown. It is hypothesized that a higher SII/ALB ratio correlates with poorer outcomes with regard to overall survival (OS) and recurrence-free survival (RFS).

AIM

To investigate the effect of preoperative SII/ALB in predicting the prognosis of HCC patients undergoing hepatectomy.

METHODS

Patients who received curative surgery for HCC at a single institution between 2014 and 2019 were retrospectively analyzed. Cox proportional hazards models and Kaplan-Meier curves were utilized to estimate OS and RFS. A nomogram was created using prognostic factors determined by the least absolute shrinkage and selection operator method and analyzed using multivariate Cox regression. This nomogram was assessed internally through the calibration plots, receiver operating characteristic (ROC) analysis, decision curve analysis (DCA) and the concordance index (C-index).

RESULTS

This study enrolled 1653 HCC patients. Multivariate analyses demonstrated that SII/ALB independently predicted OS [hazard ratio (HR) = 1.22, 95%CI: 1.03-1.46, P = 0.025] and RFS (HR = 1.19, 95%CI: 1.03-1.38, P = 0.022). Age, alpha-fetoprotein, hepatitis B surface antigen, albumin-bilirubin grade, tumor diameter, portal vein tumor thrombus, tumor number, and SII/ALB were incorporated into the nomogram to predict OS. The nomogram had a C-index of 0.73 (95%CI: 0.71-0.76) and 0.71 (95%CI: 0.67-0.74) for the training and validation cohorts, respectively. The area under the ROC curve, DCA and calibration curves demonstrated high accuracy and clinical benefits.

CONCLUSION

The SII/ALB may independently predict outcomes in HCC patients who receive curative surgical treatment. In addition, the nomogram can be used in HCC treatment decision-making.

Establishment and clinical application of a prognostic index for inflammatory status in triple-negative breast cancer patients undergoing neoadjuvant therapy using machine learning

OBJECTIVE

This study aims to establish a new prognostic index using machine learning models to predict the clinical outcomes of triple-negative breast cancer (TNBC) patients receiving neoadjuvant therapy.

METHODS

In this study, we collected data from the electronic medical records system of Harbin Medical University Cancer Hospital to establish a training set of 501 breast cancer patients who received neoadjuvant therapy from January 2017 to December 2021. Additionally, we collected data from Harbin Medical University Affiliated Cancer Hospital, Harbin Medical University Affiliated Second Hospital, and Harbin Medical University Affiliated Sixth Hospital to establish a validation set of 1533 patients during the same period. All patients underwent blood tests, and the following inflammatory and immune indices were calculated for each patient: neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic inflammatory response index (SIRI), and advanced lung cancer inflammation index (ALI). The observed outcomes included Disease-free survival (DFS) and overall survival (OS). Survival analysis was performed using Kaplan‒Meier survival curves, Cox survival analysis, propensity score matching analysis (PSM), and a nomogram to comprehensively investigate the impact of inflammatory status on patient survival.

RESULTS

The training set comprised 501 patients with a mean age of 48.63 (9.41) years, while the validation set comprised 1533 patients with a mean age of 49.01 (9.51) years. The formula for ANLR established through Lasso regression analysis on the training set is: ANLR index = NLR - 0.04 × ALB (g/L). In both the training and validation sets, ANLR was significantly associated with patient DFS and OS (all P < 0.05). Additionally, ANLR was found to be an independent prognostic factor in this study. PSM analysis further confirmed its significant correlation with patient DFS and OS (76 cases vs. 76 cases, χ2 = 2.179, P = 0.001 and χ2 = 2.063, P = 0.002). The nomogram containing ANLR also demonstrated high prognostic value. The C-index for the nomogram in the training set was 0.742 (0.619-0.886) for DFS and 0.758 (0.607-0.821) for OS, while in the validation set, the C-index was 0.733 (0.655-0.791) for DFS and 0.714 (0.634-0.800) for OS.

CONCLUSION

ANLR was associated with the prognosis of TNBC patients receiving neoadjuvant therapy and could identify high-risk postoperative patients.

Association of different inflammatory indices with risk of early natural menopause: a cross-sectional analysis of the NHANES 2013-2018

Background

Early natural menopause, characterized by the cessation of ovarian function before the age of 45, has been a subject of prior research indicating that inflammation may predict the onset of menopause. However, the specific relationship between peripheral blood inflammatory parameters and early natural menopause remains ambiguous.

Methods

This observational study utilized data from the National Health and Nutrition Examination Survey (NHANES) spanning the years 2013-2018. The age at menopause was ascertained through the Reproductive Health Questionnaire (RHQ), with early natural menopause defined as menopause occurring before the age of 45 years. Complete blood counts were derived from laboratory test data, and seven indices of inflammation were calculated, including lymphocyte count (LC), neutrophil count (NC), systemic immune inflammation index (SII), product of platelet and neutrophil count (PPN), platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), and lymphocyte-monocyte ratio (LMR). A multivariate weighted logistic regression analysis was employed to estimate the association between these inflammatory indices and early natural menopause.

Results

A total of 2,034 participants were included in the analysis, of whom 460 reported experiencing menopause before the age of 45. Both Log2-NC and Log2-PPN were found to be positively correlated with early menopause, with odds ratios (OR) of 1.56 (95% CI: 1.16, 2.09; p = 0.005) and 1.36 (95% CI: 1.07, 1.72; p = 0.015), respectively. The results from models 1 and 2 were consistent with those from model 3. In the trend test, participants in the fourth quartile (Q4) of log2-LC exhibited a positive correlation with early menopause compared to those in the lowest quartile (Q1), with an OR of 1.41 (95% CI: 1.03, 1.93; p = 0.033). Similarly, the fourth quartile (Q4) of log2-NC and log2-PPN demonstrated a positive correlation with early menopause, with odds ratios (OR) of 1.76 (95% CI: 1.27-2.45; p < 0.001) and 1.66 (95% CI: 1.21-2.29; p = 0.002), respectively. In Model 3, log2-SII, log2-PLR, log2-NLR, and log2-LMR were not significantly associated with early menopause.

Conclusion

Our findings indicate that elevated levels of Log2-LC, Log2-NC, and Log2-PPN are positively correlated with an increased risk of early menopause among women in the United States.

Association of systemic immune biomarkers with metabolic dysfunction-associated steatotic liver disease: a cross-sectional study of NHANES 2007-2018

Objective

Numerous studies emphasize the pivotal role of inflammation in metabolic dysfunction-associated steatotic liver disease (MASLD) development. Some link specific systemic immune biomarkers (e.g., systemic immuno-inflammatory index [SII], neutrophil-to-albumin ratio [NPAR] and neutrophil-to-lymphocyte ratio [NLR]) to hepatic steatosis risk. However, the relevance of other markers like systemic immune-inflammation index [SIRI], platelet-to-lymphocyte ratio [PLR] and lymphocyte/monocyte ratio [LMR] in MASLD remains unclear. Limited literature covers all six markers together. This study aims to investigate the association between SII, SIRI, LMR, NLR, PLR, and NPAR and MASLD, assessing their predictive value.

Methods

In this cross-sectional analysis of adults from NHANES (2007-2018), we investigated the relationship between six systemic immune biomarkers, stratified by quartiles: quartile1 (Q1), quartile2 (Q2), quartile3 (Q3) and quartile4 (Q4), and the outcome of MASLD assessed by Fatty Liver Index (FLI) and United States Fatty Liver Index (USFLI). Logistic regression and restricted cubic splines (RCS) were employed to assess the association between systemic immune biomarkers and MASLD risks. Propensity score matching controlled for potential confounders, and receiver operating characteristic (ROC) curve analysis evaluated the biomarkers' predictive performances for MASLD. Subgroup and interaction analysis were conducted to explore the effects of systemic immune biomarkers on MASLD risks. Multicollinearity was quantified using the variance inflation factor.

Results

In total, 14,413 participants were included and 6,518 had MASLD. Compared with non-MASLD, participants with MASLD had higher SII, SIRI, NLR, PLR, and NPAR (p < 0.001). SII, SIRI, NLR, and NPAR were further validated in the restricted cubic splines (RCS) regression model and identified as positive linear relationships (p for nonlinear >0.05). The prevalence of MASLD increased with the Q4 of SII [OR = 1.47, 95%CI (1.24, 1.74)], SIRI [OR = 1.30, 95%CI (1.09, 1.54)], NLR [OR = 1.25, 95%CI (1.04, 1.49)], PLR [OR = 1.29, 95%CI (1.09, 1.53)] and NPAR [OR = 1.29, 95%CI (1.09, 1.54)] compared to the Q1 after adjusting for the bias caused by potential confounders. However, the propensity score matching analysis only supported an association between the highest SII, SIRI, NLR NPAR and the risk of MASLD. The results of the subgroup analysis showed considerable robustness in the relationship.

Conclusion

Higher SII, SIRI, NLR and NPAR were positively associated with a heightened risk of MASLD. NPAR showed the superior predictive value, followed by SII, SIRI and NLR. This needs to be validated in additional longitudinal studies and clinical trials.

The systemic inflammation response index as a risk factor for hepatic fibrosis and long-term mortality among individuals with metabolic dysfunction-associated steatotic liver disease

BACKGROUND AND AIMS

The systemic inflammation response index (SIRI) is associated with various diseases with inflammatory components, but its relationship with the progression of hepatic fibrosis and survival outcomes in patients with metabolic dysfunction-associated steatotic liver disease (MASLD) is still unclear. This study was designed to investigate the potential associations between the SIRI and advanced hepatic fibrosis (AHF) as well as between the SIRI and long-term outcomes in individuals with MASLD.

METHODS AND RESULTS

A prospective cohort study was conducted using data gathered from the National Health and Nutrition Examination Survey (NHANES) spanning from 2005 to 2016. Weighted binary logistic regression, the Cox proportional hazards model, and time-dependent receiver operating characteristic (ROC) analyses were employed to assess the relationships among the SIRI, AHF, and mortality in patients with MASLD. Our study included a total of 5126 patients with MASLD. A higher SIRI was significantly associated with increased odds of AHF (OR 1.55, 95% CI 1.22, 1.96). According to the survival analyses, a higher SIRI was associated with greater all-cause (HR 1.19, 95% CI 1.15, 1.22) and cardiovascular mortality (HR 1.25, 95% CI 1.19, 1.32) after adjustment. The time-dependent ROC analysis indicated that the SIRI had a modest predictive value for discriminating MASLD individuals at higher versus lower mortality risk over 3-year, 5-year, and 10-year follow-up.

CONCLUSIONS

The SIRI is a promising tool for identifying MASLD individuals at risk of progressing to AHF and for predicting mortality outcomes.

Decoding the Prognostic Significance and Therapeutic Implications of Inflammation-Based Scores in Hepatocellular Carcinoma: A Comprehensive Review

Hepatocellular carcinoma (HCC) is the most common primary liver cancer, posing a significant global health challenge with an increasing incidence. In recent years, multiple staging systems and scores have been proposed, emphasising the necessity for the development of precise prognostic tools. The well-documented etiological relationship between chronic inflammation and carcinogenesis has prompted researchers to explore novel prognostic markers associated with the inflammatory status of HCC patients. This review summarises the current data about inflammation-based scores in the context of HCC. We discuss established scores like the Glasgow Prognostic Score (GPS), modified GPS (mGPS) and the neutrophil-to-lymphocyte ratio (NLR) and others not as extensively studied, examining their utility in predicting survival outcomes and treatment response in HCC patients. Furthermore, we explore emerging scores, including the prognostic nutritional index (PNI) and other lymphocyte-based scores, assessing their potential in refining risk stratification and guiding therapeutic decisions in the era of precision medicine. As research progresses and these scores undergo further refinement and integration into the evolving landscape of HCC management, they carry significant potential for improving patient outcomes.

Development and Validation of a Novel Prognostic Nomogram Based on Platelet and CD8+T Cell Counts in Hepatocellular Carcinoma Patients with Portal Vein Tumor Thrombosis

Purpose

Portal vein tumor thrombosis (PVTT) is one of the hallmarks of advanced Hepatocellular carcinoma (HCC). Platelet (PLT) function parameters and CD8+T cells (CD8+Ts) play an important role in HCC progression and metastasis. This study is committed to establishing an efficient prognosis prediction model and exploring the combined effect of PLT and CD8+Ts on PVTT prognosis.

Patients and Methods

This retrospective study collected 932 HCC patients with PVTT from 2007 to 2017 and randomly divided them into a training cohort (n = 656) and a validation cohort (n = 276). We performed multivariable Cox and Elastic-net regression analysis, constructed a nomogram and used Kaplan-Meier survival curves to compare overall survival and progression-free survival rates in different substrata. Relationships between indicators involved were also analyzed.

Results

We found tumor number, size, treatment, PLT, γ-glutamyl transferase, alpha-fetoprotein, mean platelet volume, and CD8+Ts were related to the 5-year OS of patients with PVTT, and established a nomogram. The area under the receiver operating characteristic curve (AUCs) for predicting the 1-year OS rates were 0.767 and 0.794 in training and validation cohorts. The calibration curve and decision curve indicated its predictive consistency and strong clinical utility. We also found those with low PLT (<100*10^9/L) and high CD8+Ts (>320 cells/μL) had a better prognosis.

Conclusion

We established a well-performing prognostic model for PVTT based on platelet functional parameters and CD8+Ts, and found that PT-8 formed by PLT and CD8+Ts was an excellent predictor of the prognosis of PVTT.

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.

Systemic Immune-Inflammation Index and Systemic Inflammatory Response Index as Predictors of Mortality in ST-Elevation Myocardial Infarction

(1) Background: The systemic inflammatory response index (SIRI; neutrophil count × monocyte/lymphocyte count), and the systemic immune-inflammation index (SII; platelet count × neutrophil count/lymphocyte count) are recently proposed biomarkers to assess the immune and inflammatory status. However, data on SIRI and SII are still relatively lacking and do not definitively and exhaustively define their role as predictors of an adverse prognosis in acute myocardial infarction (AMI). The aim of the present study was to evaluate SII and SIRI determinants as well as to assess SIRI and SII prognostic power in ST-elevation myocardial infarction (STEMI). (2) Methods: A total of 105 STEMI patients (74 males, 70 ± 11 years) were studied (median follow-up 54 ± 25 months, 24 deaths). (3) Results: The main determinants of SIRI and SII were creatinine and brain natriuretic peptide (BNP) (multivariate regression). Patients with higher SIRI (>75th percentile, 4.9) and SII (>75th percentile, 1257.5) had lower survival rates than those in the low SIRI/SII group (Kaplan-Meier analysis). Univariate Cox regression revealed that high SIRI and SII were associated with mortality (HR: 2.6, 95% CI: 1.1-5.8, p < 0.05; 2.2, 1-4.9, p ≤ 0.05, respectively); however, these associations lost their significance after multivariate adjustment. (4) Conclusions: SIRI and SII association with mortality was significantly affected by confounding factors in our population, especially creatinine and BNP, which are associated with both the inflammatory indices and the outcome.