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This study aimed to evaluate whether preoperative systemic inflammatory response index (SIRI) could predict lymph node metastasis (LNM) in endometrial cancer (EC), and to develop a nomogram that combines SIRI with clinicopathological parameters for individualized LNM risk assessment. We retrospectively enrolled 1, 336 EC patients who underwent primary surgery. Among them, 947 cases from the First Affiliated Hospital of Chongqing Medical University served as the training cohort, and 389 cases from the Chongqing Maternal and Child Health Hospital comprised the external validation cohort. Preoperative SIRI was calculated using peripheral neutrophil, monocyte, and lymphocyte counts. Logistic regression analyses were used to identify independent predictors of LNM, which were then incorporated into a nomogram. Model performance was evaluated by ROC curves and calibration curves in both cohorts. Kaplan-Meier analysis was applied to compare recurrence-free survival (RFS) and overall survival (OS) between high- and low-risk groups stratified by the model. SIRI yielded an area under the curve (AUC) of 0.773 for predicting LNM, with a sensitivity of 74.2% and specificity of 75.8%. The optimal cutoff value of SIRI was 1.115. Multivariate analysis showed that age, CA125, histological type, molecular classification, and SIRI were independently associated with LNM (P < 0.001). A nomogram integrating these five factors was then constructed. This combined model achieved AUC of 0.889 in the training cohort, outperforming the models based solely on SIRI (AUC&#xa0;=&#xa0;0.750) or solely on clinicopathological parameters (AUC&#xa0;=&#xa0;0.836). Calibration curves indicated good agreement between predictions and observations. Using a cutoff of 0.136, we divided patients into high- and low-risk groups and found marked differences in both RFS and OS between training and validation cohorts (P < 0.05). Preoperative SIRI is an independent predictor of LNM in patients with EC. The nomogram model incorporating SIRI and clinicopathological parameters demonstrated superior performance in predicting LNM compared to models containing either SIRI alone or only traditional parameters, providing a valuable tool for individualized preoperative risk stratification and surgical decision-making.

This studyaimed to examine the association between Life's Crucial 9 (LC9) score and the prevalence of coronary heart disease (CHD) among U.S. adults, as well as explore the potential statistical contribution of Systemic Inflammatory Response Index (SIRI) in this association. Data were obtained from 23,508 participants in the National Health and Nutrition Examination Survey (NHANES) from 2005 to 2018. LC9 score quartiles were used to summarize continuous and categorical variables, which were then reported as weighted means&#x2009;&#xb1;&#x2009;standard deviations or weighted frequencies and proportions, respectively. Differences among groups were examined using weighted t-tests and weighted chi-square tests. The relationship between LC9 scores, Ln-SIRI values, and the prevalence of CHD was investigated using weighted logistic regression models following the natural logarithmic transformation of skewed SIRI results. Furthermore, restricted cubic spline regression was utilized to investigate plausible nonlinear connections, subgroup and likelihood ratio tests investigated interaction effects, and weighted quantile sum (WQS) regression was incorporated to determine the relative contributions of LC9 components to CHD. An exploratory non-causal mediation analysis using 1,000 bootstrap samples was conducted to assess SIRI as a potential statistical explanatory variable in the association between LC9 and the prevalence of CHD. In Model 3, a 10-point increase in the LC9 score correlated with a 24% decrease in the odds of CHD prevalence; participants in the Q4 group had 59% lower odds of CHD compared with those in the Q1 group (P&#x2009;<&#x2009;0.001 trend). Each Ln-SIRI unit was associated with 56% higher odds of CHD, with Q4 showing 2.02-fold higher odds than Q1 (P&#x2009;<&#x2009;0.001 trend). Restricted cubic spline regression revealed linear relationships between LC9, Ln-SIRI, and the prevalence of CHD. In particular, LC9 was negatively associated with CHD, whereas Ln-SIRI was positively associated with CHD. Age significantly moderated the association between LC9 and CHD (P for interaction&#x2009;<&#x2009;0.05), with stronger inverse associations in younger adults. WQS regression identified glucose (weight&#x2009;=&#x2009;0.34) and tobacco (weight&#x2009;=&#x2009;0.33) as key CHD-associated factors. Exploratory non-causal mediation analysis revealed that about 6.5% of the LC9-CHD relationship was statistically accounted for by SIRI (P&#x2009;<&#x2009;0.001), with the majority of factors associated with the link remaining unexplained. This indicates that other factors may be the primary contributors to the LC9-CHD relationship. This study showed that higher LC9 scores were significantly associated with lower odds of prevalent self-reported CHD, while higher SIRI was associated with higher odds.

Inflammation- and nutrition-associated biomarkers have received increasing interest in esophageal cancer research. Nevertheless, the diagnostic value of the systemic inflammation response index (SIRI), albumin (ALB), and hemoglobin-albumin-lymphocyte-platelet (HALP) score across different pathological stages has not yet been fully clarified. We evaluated the performance of SIRI, ALB, and HALP, alone and in combination, for the auxiliary discrimination of esophageal cancer (EC), and examined their associations with clinicopathological characteristics in stage-stratified analyses. This retrospective study enrolled 168 esophageal cancer patients and 117&#xa0;healthy controls (HC). SIRI and HALP were calculated preoperatively from routine hematological parameters. Cancer cases were divided into stage I/II (n = 32) and stage III/IV (n = 136) groups. ROC curve analysis evaluated the discriminatory efficacy of SIRI, ALB, HALP, and their combined model. The combined model was constructed using binary logistic regression incorporating SIRI, ALB, and HALP, and its discriminatory performance was evaluated by ROC analysis. Multivariable logistic regression adjusted for age and sex was performed, and bootstrap internal validation (1000 resamples) assessed model optimism. Compared with healthy controls, patients with esophageal cancer exhibited significantly increased SIRI levels and significantly decreased ALB and HALP levels. The combined model achieved an AUC of 0.803 for distinguishing stage III/IV disease from healthy controls and 0.746 for stage I/II disease. SIRI was significantly associated with T stage and N stage. ALB with tumor length and T stage. HALP with smoking history and T stage. After adjustment for age and sex, HALP retained significance mainly in the all-cancer and stage III/IV analyses. SIRI, ALB, and HALP were associated with the occurrence and stage of esophageal cancer. Their combined model demonstrated improved discriminatory performance over single markers, particularly in stage III/IV disease, and retained additional value after adjustment for age and sex. These biomarkers may serve as convenient exploratory indicators for auxiliary assessment of esophageal cancer.

Inflammation plays a pivotal role in the pathophysiology of post-stroke depression (PSD). However, the relationship between novel systemic inflammatory indices-the systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI)-and early-onset PSD remains inadequately explored. Early-onset PSD was diagnosed 2 weeks after acute ischemic stroke (AIS). Depression severity was assessed using the 17-item Hamilton Depression Rating Scale (HAMD-17); patients with scores &#x2265;7 were classified into the early-onset PSD group. Spearman rank correlation analysis was performed to evaluate associations of SII and SIRI with HAMD-17 scores across all participants. Binary logistic regression was used to examine the independent associations of SII and SIRI with early-onset PSD. Receiver operating characteristic (ROC) analysis was employed to assess the SII and SIRI capacity to differentiate early-onset PSD. Of the 1,113 prospectively enrolled patients, 372 (33.42%) were diagnosed with early-onset PSD. HAMD-17 scores showed significant positive correlations with SII (r&#x202f;=&#x202f;0.440, p&#x202f;<&#x202f;0.001) and SIRI (r&#x202f;=&#x202f;0.418, p&#x202f;<&#x202f;0.001). Both SII (OR&#x202f;=&#x202f;1.762, 95% CI: 1.261-1.946, p&#x202f;<&#x202f;0.001) and SIRI (OR&#x202f;=&#x202f;1.672, 95% CI: 1.348-1.932, p&#x202f;=&#x202f;0.004) emerged as independent predictors of early-onset PSD. The areas under the curve (AUC) for SII, SIRI, and their combination were 0.767, 0.718, and 0.807, respectively. SII and SIRI may serve as independent risk factors for early-onset PSD. These indices offer potential utility for risk stratification and could inform prevention strategies and prognosis management in this patient population.

During the pandemic era, rapid and accessible prognostic tools were essential to support clinical decision-making for emergency department (ED) patients presenting with acute infectious symptoms. Hematologic inflammatory indices derived from complete blood count (CBC) parameters, such as the systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), and pan-immune-inflammation value (PIV), have been increasingly investigated for risk stratification. This retrospective cohort study evaluated the age-stratified prognostic performance of these indices for 30-day mortality in ED patients during the pandemic period. This retrospective cohort study included adults presenting to a tertiary-care ED between March 1 and May 31, 2020. All included patients were retrospectively confirmed to have SARS-CoV-2 infection by RT-PCR. CBC-derived inflammatory markers (SII, SIRI, and PIV) were calculated at admission. The primary outcome was 30-day mortality; the secondary outcome was ICU admission. Age-stratified analyses (<65 and &#x2265;65 years) were performed. Receiver operating characteristic (ROC) analyses, area under the curve (AUC) values, optimal cut-offs, and negative predictive values (NPVs) were determined; logistic regression models assessed independent associations with mortality. A total of 2,778 PCR-confirmed patients were included (mean age 47.8&#x2009;&#xb1;&#x2009;16.2; 58.7% male). Thirty-day mortality was 6.2%. In the overall cohort, SII, SIRI, and PIV demonstrated modest prognostic performance for mortality (AUCs: 0.663, 0.659, and 0.649, respectively). In patients <65 years, performance improved particularly for SII (AUC 0.727), with SIRI and PIV yielding AUCs of 0.676 and 0.677, respectively. Among patients &#x2265;65 years, discrimination was lower (SII: 0.570; SIRI: 0.604; PIV: 0.588). Formal DeLong testing confirmed statistically significant age-related attenuation for SII (&#x394;AUC&#x2009;=&#x2009;0.159; P&#x2009;=&#x2009;0.0055), with non-significant trends for SIRI and PIV. As an exploratory secondary outcome, direct ED-to-ICU admission occurred in 2.9% of patients; this endpoint primarily reflects the institutional pandemic-era pathway of low-threshold ward admission with subsequent ICU escalation upon clinical deterioration. All indices demonstrated high negative predictive values, particularly in younger patients, indicating potential utility for identifying lower-risk individuals during high-volume pandemic ED operations. Hematologic inflammatory indices obtained at ED presentation demonstrated age-dependent prognostic performance for 30-day mortality, with SII showing good discrimination and high negative predictive value (98.9%) in patients younger than 65 years and reduced discriminatory performance in elderly patients. These readily available and cost-effective parameters may support rule-out decisions for younger adults in emergency settings, while in elderly patients clinical assessment and comorbidity profiling should be prioritized over inflammatory marker interpretation.

To investigate the specific diagnostic value of the systemic immune-inflammation index (SII) and systemic inflammation response index (SIRI) combined with the prognostic nutritional index (PNI) and tumor markers (CA19-9 and CEA) in the stage diagnosis of pancreatic cancer. This single-center retrospective cohort study consecutively enrolled 257 patients with pathologically confirmed pancreatic cancer. Patients with stage I-II disease were classified as the early-stage pancreatic cancer group, while those with stage III-IV disease were classified as the non-early group. Clinical and pathological characteristics, as well as pretreatment peripheral blood inflammatory, nutritional, and tumor marker data, were collected. SII, SIRI, and PNI were calculated. Differences in these parameters were compared across tumor stages and degrees of differentiation. Compared with the early-stage group, patients with non-early-stage pancreatic cancer had significantly higher levels of SII, SIRI, CA19-9, and CEA, while PNI was significantly lower (all P&#xa0;<&#xa0;0.01). With advancing TNM stage, SII, SIRI, and tumor marker levels progressively increased, whereas PNI gradually decreased (all P&#xa0;<&#xa0;0.05). Among individual indicators, PNI demonstrated the best diagnostic performance for early-stage pancreatic cancer (AUC&#xa0;=&#xa0;0.78), followed by CA19-9 (AUC&#xa0;=&#xa0;0.75), SII (AUC&#xa0;=&#xa0;0.72), and SIRI (AUC&#xa0;=&#xa0;0.70). The combined inflammatory and nutritional model (SII + SIRI + PNI) achieved an AUC of 0.82, which was significantly superior to that of any single marker. When inflammatory, nutritional, and tumor markers were fully combined, diagnostic performance was further improved (AUC&#xa0;=&#xa0;0.88, sensitivity 84.6%, specificity 81.2%). In the subgroup of CA19-9-negative patients, the combined inflammatory and nutritional model still showed good diagnostic value (AUC&#xa0;=&#xa0;0.85). The combination of systemic immune-inflammation indices with nutritional parameters and tumor markers significantly enhances the specificity and accuracy of early-stage pancreatic cancer diagnosis. This multi-marker strategy provides an important complementary diagnostic approach, particularly in CA19-9-negative patients.

Emerging evidence indicates that inflammation plays a crucial role in cancer prognosis. Inflammatory response biomarkers are recognized as promising prognostic factors for mortality in patients with cancer. This study aims to evaluate the prognostic significance of the systemic inflammatory response index (SIRI), systemic immune-inflammation index (SII), platelet-to-lymphocyte ratio (PLR), neutrophil-to-lymphocyte ratio (NLR), inflammatory prognostic index (IPI), and C-reactive protein-albumin-lymphocyte (CALLY) index. Weighted Cox regression analyses, restricted cubic spline models, Kaplan-Meier survival curves, and receiver operating characteristic analyses were performed to assess the predictive value of the 6 inflammatory markers for mortality. Subgroup analyses and sensitivity analyses were conducted to examine associations within specific subpopulations. Cox regression models demonstrated that SIRI, NLR, IPI, and CALLY were significant predictors of all-cause mortality (tertile 3 vs tertile 1; hazard ratio [HR]: SIRI: 1.72, 95% CI 1.29-2.27; NLR: 1.33, 95% CI 1.02-1.74; IPI: 1.48, 95% CI 1.14-1.92; CALLY: 0.66, 95% CI 0.51-0.85). IPI (HR 1.91, 95% CI 1.11-3.27) and CALLY (HR 0.53, 95% CI 0.31-0.90) were significantly associated with cancer-specific mortality, whereas only SIRI was able to predict cardiovascular mortality (P value for trend=.04). Dose-response relationships were observed between the 6 inflammatory markers and mortality outcomes. Kaplan-Meier survival curves further illustrated significant differences between tertile groups (log-rank test, P<.001). The 6 inflammatory indices exhibited moderate predictive ability for all-cause mortality. IPI yielded the highest area under the curve (AUC) for cancer-specific mortality (AUC=0.6338), and SIRI was the most efficient predictor of cardiovascular mortality (AUC=0.687). No significant interactions were observed between the 6 inflammatory markers and most subgroup variables. SIRI, NLR, IPI, and CALLY represent convenient and cost-effective prognostic tools for predicting mortality in patients with cancer. In contrast, SII and PLR may not be reliable prognostic biomarkers.

Differentiating benign from malignant salivary gland tumors (SGTs) preoperatively remains a clinical challenge due to overlapping morphological and radiologic features. Systemic inflammatory biomarkers such as the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) have emerged as potential adjuncts reflecting tumor-associated immune dysregulation. This systematic review and meta-analysis aimed to evaluate the diagnostic accuracy of these biomarkers for SGTs. A systematic search was conducted in PubMed, SCOPUS, EBSCOhost, and Google Scholar up to September 2025 following the PRISMA-DTA guidelines (PROSPERO registration: CRD420251173943). Studies assessing the diagnostic accuracy of inflammatory biomarkers with histopathology as the reference standard were included. Data on sensitivity, specificity, area under the curve (AUC), and diagnostic odds ratio (DOR) were pooled using a random-effects model, and heterogeneity was assessed using Higgins I&#xb2; statistics. Six studies comprising 338 patients met the inclusion criteria. The pooled sensitivity and specificity were 0.71 and 0.81 for NLR, 0.61 and 0.72 for PLR, 0.74 and 0.78 for SII, and 0.71 and 0.73 for SIRI, respectively. Corresponding AUCs ranged from 0.73 to 0.83, indicating moderate-to-excellent diagnostic accuracy. Among the &#xa0;evaluated indices, SIRI showed the highest pooled sensitivity, while SII demonstrated the best discriminative capacity. The integration of SIRI with fine-needle aspiration cytology (FNAC) further improved diagnostic performance (accuracy 81.2%). Heterogeneity across studies was low (I&#xb2; = 0%). Inflammatory biomarkers, particularly SII and SIRI, exhibit promising diagnostic value for diagnosing various SGTs and may complement cytological evaluation in indeterminate cases. Prospective multicentric studies with standardized cut-offs are recommended to validate their clinical application.

Background and Objectives: Neoadjuvant dual HER2 blockade combined with chemotherapy is the standard treatment approach for patients with high-risk early-stage or locally advanced HER2-positive breast cancer. However, the optimal chemotherapy backbone and the predictive value of systemic inflammatory biomarkers remain subjects of ongoing investigation. This study aimed to compare pathologic complete response (pCR) rates between neoadjuvant dose-dense doxorubicin/cyclophosphamide followed by paclitaxel plus trastuzumab and pertuzumab (ddAC+THP) and docetaxel, carboplatin, trastuzumab, and pertuzumab (TCHP), and to evaluate the predictive performance of pretreatment inflammatory biomarkers. Materials and Methods: In this multicenter retrospective study, patients with HER2-positive breast cancer treated with neoadjuvant ddAC+THP or TCHP between 2019 and 2025 at three tertiary centers were evaluated. Pretreatment inflammatory biomarkers, including neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and hemoglobin, albumin, lymphocyte, and platelet (HALP) score, were calculated from baseline laboratory parameters. Receiver operating characteristic analyses were performed to determine optimal cutoff values, and logistic regression analyses were used to identify predictors of pCR. Results: A total of 197 patients were included, of whom 138 received ddAC+THP and 59 received TCHP. Overall, 125 patients (63.5%) achieved pCR. The pCR rate was numerically higher in the ddAC+THP group than in the TCHP group (65.2% vs. 59.3%), although the difference was not statistically significant (p = 0.431). Among the evaluated biomarkers, SIRI demonstrated the highest discriminatory performance for predicting pCR (AUC: 0.725, 95% CI: 0.652-0.797), followed by NLR (AUC: 0.673, 95% CI: 0.595-0.750). In multivariable analysis, hormone receptor positivity (OR: 0.291, 95% CI: 0.131-0.645; p = 0.002) and elevated SIRI (>0.845) (OR: 0.088, 95% CI: 0.036-0.216; p < 0.001) were independently associated with lower odds of achieving pCR. No significant difference in pCR was observed between treatment regimens across predefined subgroup analyses. Conclusions: Neoadjuvant ddAC+THP and TCHP achieved comparable pCR outcomes in patients with HER2-positive breast cancer. SIRI was independently associated with a lower likelihood of achieving pCR and showed acceptable discriminatory performance. These findings suggest that SIRI may represent an exploratory, readily available inflammatory biomarker for pCR risk stratification; however, prospective validation is required before clinical application.

Spinal cord injury (SCI) is a devastating condition characterized by variability in injury mechanisms and neurologic recovery. Complex reactive cellular responses and the release of cytokines, which may be clinical biomarkers and therapeutic targets, occur immediately after SCI. In the present study, we aimed to determine alterations in the systemic inflammatory response index (SIRI) and the levels of HMGB1 and IL-33 in patients with traumatic SCI (tSCI) and investigate their associations with 1-year outcomes. Forty patients were admitted to the intensive care unit after tSCI due to traffic accidents, falls, or sports-related injuries. Blood samples were collected within 24&#xa0;h and 7&#xa0;days after SCI. Twenty age- and sex-matched healthy volunteers were included as controls. Neurologic and functional status were evaluated via the American Spinal Injury Association Impairment Scale (AIS) grade at admission, at discharge, and 6&#xa0;months after SCI. Serum levels of HMGB1, IL-33, IL-1&#x3b2;, and TNF-&#x3b1; were determined via ELISA. The discriminative ability of those indicators in predicting the AIS grade at 6&#xa0;months was determined by receiver operating characteristic (ROC) analysis. Compared with those of the controls, the HMGB1, IL-33, IL-1&#x3b2;, and TNF-&#x3b1; levels, as well as the SIRI and neutrophil-lymphocyte ratio (NLR), were significantly elevated within 24&#xa0;h and 7&#xa0;days after SCI. These indicators peaked within 24&#xa0;h and then decreased at 7&#xa0;days post-SCI. Among the 40 patients with tSCI, 23 (57.5%) were categorized into the neurologically complete tSCI group (AIS A-B). SIRI, HMGB1, IL-33, and IL-1&#x3b2; levels and the NLR were greater in patients in the neurologically complete tSCI group and poor outcome group than in those in the neurologically incomplete tSCI group or good outcome group. ROC analysis revealed that the levels of the SIRI (AUC&#xa0;=&#xa0;0.884) and IL-33 (AUC&#xa0;=&#xa0;0.822) at 24&#xa0;h and the levels of HMGB1 (AUC&#xa0;=&#xa0;0.922) and IL-33 (AUC&#xa0;=&#xa0;0.816) on day 7 demonstrated excellent predictive value for poor neurological outcomes (AIS A-C) at 6&#xa0;months. Elevated levels of SIRI, HMGB1, and IL-33 are strongly associated with more severe initial injury and are significant predictors of poor 6-month neurological outcomes after tSCI.

To analyze the correlation between systemic inflammatory indicators and severe pneumonia severity, and evaluate their prognostic value for 28-day mortality. This retrospective study included 75 severe pneumonia patients treated at The First People's Hospital of Lin'an District from October 2022 to December 2023. Systemic inflammation indices - Systemic Immune-Inflammation Index (SII), Systemic Inflammatory Response Index (SIRI), Neutrophil-to-HDL-C ratio (NHR), Lymphocyte-to-HDL-C ratio (LHR), and Monocyte-to-HDL-C ratio (MHR) - were calculated from routine blood and biochemical tests. Spearman correlation analyzed relationships with APACHE II scores. Prognostic value was assessed using ROC curve analysis. Kaplan-Meier survival analysis was performed based on predefined thresholds, and sensitivity analysis evaluated model robustness. SII, SIRI, NHR, LHR, and MHR levels were significantly higher in the group that died versus the group that survived (P < 0.001). Spearman analysis showed significant positive correlations of SIRI, NHR, and MHR with APACHE II scores (P < 0.001), with MHR exhibiting the strongest correlation (r = 0.556). Multivariate logistic regression, adjusted for procalcitonin (PCT) and neutrophil count (NEU), identified all five markers as independent factors for 28-day mortality. ROC analysis showed AUC values of 0.719, 0.688, 0.758, 0.810, and 0.802 for SII, SIRI, NHR, LHR, and MHR, respectively, with a combined AUC of 0.896. Survival analysis revealed elevated SII, LHR, and MHR associated with reduced survival (P < 0.001). Sensitivity analysis confirmed marker stability as mortality predictors. Systemic inflammatory indices (SII, SIRI, NHR, LHR, and MHR) in severe pneumonia patients significantly correlated with poor prognosis, and their combination exhibited excellent predictive value for adverse outcome.

Given the established association between chronic kidney disease (CKD) and systemic inflammation, this study examined the relationships between complete blood count (CBC)-derived inflammatory markers and prevalent CKD. Two data sets (Chinese clinical data, n = 4,518; NHANES 2017-2020, n = 7,724) are analyzed. Seven CBC&#x2011;derived inflammatory indices were calculated: SII, SIRI, NLR, dNLR, NMLR, MLR, and PLR. Each index was categorized into quartiles (Q1-Q4). Weighted logistic regression (for NHANES) and unweighted logistic regression (for the Chinese clinical data) were applied to estimate associations with CKD, with sequential adjustment for demographics, body mass index, and comorbidities. To control for multiple comparisons, false discovery rate (FDR) correction was applied. Furthermore, subgroup analysis, restricted cubic spline analysis and sensitivity analysis were also performed in this study. In the two fully adjusted models, the highest quartile (Q4) of SIRI, NLR, and NMLR was significantly associated with higher odds of prevalent CKD compared with Q1. After FDR correction, these associations remained significant in both cohorts: in the Chinese cohort, all padj < 0.001; in NHANES, padj = 0.028 for SIRI, 0.040 for NLR, and 0.041 for NMLR. Sensitivity analyses consistently supported the primary findings: excluding outliers, log2 transformation, and the alternative CKD definition yielded similar effect directions and significance levels. Heterogeneity was observed across subgroups, and restricted cubic splines revealed nonlinear dose&#x2011;response relationships (p for nonlinearity <0.05). Elevated SIRI, NLR, and NMLR are associated with prevalent CKD, suggesting systemic inflammation may play a role, yet prospective studies are required to establish temporality and causality.

To characterize longitudinal changes in routine blood count-derived inflammatory indices throughout pregnancy and the early postpartum period in women with diet-controlled gestational diabetes mellitus (GDM A1) compared with normoglycemic controls. This retrospective cohort study included 366 pregnant women, comprising 170 women with GDM A1 and 196 normoglycemic controls, who received antenatal care at Beijing Friendship Hospital. Routine complete blood count parameters were collected at seven clinically relevant time windows: 8-12, 16-20, 24-28, 28-32, and 36&#xa0;weeks of gestation, immediately before delivery, and postpartum. The aggregate index of systemic inflammation (AISI), systemic inflammation response index (SIRI), systemic immune-inflammation index (SII), lymphocyte-to-monocyte ratio (LMR), monocyte-to-lymphocyte ratio (MLR), and platelet-to-lymphocyte ratio (PLR) were calculated. Exploratory unadjusted between-group comparisons were performed using Mann-Whitney U-tests. Adjusted linear mixed-effects models were used to evaluate group-by-time interactions while accounting for within-subject correlation and baseline covariates. Women with GDM A1 were older and had higher early-pregnancy BMI than normoglycemic controls. After adjustment for maternal age, early-pregnancy BMI, gravidity, parity, and history of macrosomia, significant group-by-time interactions were observed for all six inflammatory indices, including AISI (P < 0.001), SIRI (P < 0.001), SII (P = 0.017), LMR (P = 0.011), MLR (P = 0.011), and PLR (P = 0.022). In Holm-adjusted post hoc comparisons, SIRI was higher in the GDM A1 group during the postpartum period (adjusted ratio = 1.204, 95% CI: 1.066-1.360, P = 0.020), and PLR was higher immediately before delivery (adjusted ratio = 1.123, 95% CI: 1.036-1.217, P = 0.032). Women with GDM A1 showed altered longitudinal trajectories of CBC-derived inflammatory indices, with the most robust adjusted time-specific differences involving postpartum SIRI and pre-delivery PLR. These indices may provide accessible research markers for characterizing stage-specific inflammatory patterns in diet-controlled GDM, but prospective studies incorporating direct inflammatory and metabolic measurements are required to establish clinical utility.

Inflammation plays a pivotal role in tumor progression and prognosis. In nasopharyngeal carcinoma (NPC), several hematologic markers derived from systemic inflammation have emerged as potential prognostic indicators. This study aims to evaluate the prognostic value of inflammation-based indices in NPC systematically. A systematic review and meta-analysis were conducted according to PRISMA 2020 and MOOSE guidelines. A comprehensive search of PubMed, Embase, Scopus, and Web of Science was performed to identify eligible studies from January 2015 to December 2025. Nine studies involving 2, 986 NPC patients were included. Biomarkers assessed included the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), and pan-immune-inflammation value (PIV). Pooled hazard ratios (HRs) with 95% confidence intervals (CIs) were calculated for overall survival (OS) and progression-free survival (PFS). Elevated inflammation-based markers were significantly associated with poor prognosis in NPC. The pooled HR for OS was 1.86 (95% CI: 1.42-2.43), and for PFS was 1.74 (95% CI: 1.31-2.30). Among individual markers, SII and SIRI showed the strongest associations with poor outcomes (HR&#xa0;=&#xa0;2.01 and 1.93, respectively). In contrast, a higher LMR was associated with better prognosis (HR&#xa0;=&#xa0;0.72, 95% CI: 0.53-0.98). Sensitivity and subgroup analyses confirmed the robustness and consistency of findings. No significant publication bias was detected. Systemic inflammation-based biomarkers, particularly SII and SIRI, are strong, independent predictors of survival in NPC. Their integration into clinical practice may enhance prognostic stratification and inform treatment decisions. Future prospective studies are warranted to validate these findings and standardize biomarker thresholds.

Background: Early childhood caries (ECC) is a biofilm-mediated and sugar-driven disease associated with local and systemic inflammatory responses. This study evaluated serum Interleukin-6 (IL-6) and IL-10 concentrations, hematologic inflammatory indices, and oral inflammatory parameters in children with ECC compared with caries-free sibling controls. Methods: This sibling-controlled case-control study included 155 children aged 2.5-6 years, comprising 120 children with active ECC and 35 caries-free siblings. Serum IL-6 and IL-10 concentrations were measured using enzyme-linked immunosorbent assay (ELISA). Complete blood count parameters and derived inflammatory indices, including neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), aggregate index of systemic inflammation (AISI), cumulative inflammatory index (IIC), and mean corpuscular volume-to-lymphocyte ratio (MCVL), were calculated. Plaque Index (PI) and Gingival Index (GI) were recorded in children with ECC. Group comparisons, correlation analyses, ROC analysis, and multivariable logistic regression were performed. Results: Children with ECC exhibited significantly higher serum IL-6 and IL-10 concentrations than sibling controls. MCVL values were significantly lower in the ECC group, whereas several inflammatory indices indicated an increased systemic inflammatory burden. Stratification by PI tertiles showed progressively higher values for WBC, NEU, NLR, SII, SIRI, AISI, and IIC as plaque accumulation increased (all p < 0.05). PI was strongly correlated with GI (r = 0.811, p < 0.001) and moderately correlated with NLR (r = 0.536), SII (r = 0.536), SIRI (r = 0.654), AISI (r = 0.648), and IIC (r = 0.546) (all p < 0.01). Serum IL-6 and IL-10 were strongly correlated (r = 0.804, p < 0.001) but not with PI or GI. ROC analysis demonstrated moderate discriminatory performance for IL-6 (AUC = 0.701) and IL-10 (AUC = 0.696). Age- and sex-adjusted multivariable logistic regression demonstrated that elevated IL-6 concentrations (adjusted OR = 1.36; 95% CI, 1.10-1.68; p = 0.005) remained independently associated with ECC, whereas increasing MCVL values (adjusted OR = 0.92; 95% CI, 0.86-0.98; p = 0.010) were associated with reduced odds of ECC. Conclusions: ECC is associated with systemic cytokine alterations and increased hematologic inflammatory burden. While IL-6 and IL-10 distinguish children with ECC from sibling controls, plaque accumulation severity is better reflected by composite hematologic inflammatory indices than by isolated cytokine concentrations. IL-6 and MCVL may be promising adjunctive biomarkers for ECC.

Vagus Nerve Stimulation (VNS) is an established treatment for drug-resistant epilepsy (DRE) in children, but response rates vary significantly (50%-60%). Given that neuroinflammation is implicated in epilepsy and VNS may modulate systemic inflammation, this study explored associative links between routine blood inflammatory indices and VNS treatment response in pediatric DRE. We retrospectively analyzed 108 pediatric DRE patients who received VNS. Six peripheral inflammatory indices, namely 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), and pan-immune-inflammation value (PIV), were calculated at preoperative and post-titration 12&#xa0;months. We used Multivariable Regression and Latent Change Score Models (LCSM) to assess the impact of baseline status and dynamic postoperative changes. Multivariable analyses revealed associations between inflammatory indices and VNS outcomes. The LCSM demonstrated that the associative roles of these indices were temporally distinct: VNS response showed significant correlations with the magnitude of postoperative change in Lymphocyte count (beta&#x2009;=&#x2009;&#x2009;-&#x2009;0.73, p&#x2009;<&#x2009;0.01), NLR (beta&#x2009;=&#x2009;0.69, p&#x2009;<&#x2009;0.01), and SIRI (beta&#x2009;=&#x2009;0.75, p&#x2009;<&#x2009;0.01), independent of baseline status. Conversely, the associative patterns of PIV and SII were primarily related to their initial baseline levels. &#xa0;The efficacy of VNS in pediatric DRE is associated with systemic inflammatory dynamics. Postoperative changes in these inflammatory indices are associated with VNS treatment outcomes and may serve as a potential prognostic indicator for clinical response. &#x2022; Vagus nerve stimulation (VNS) is an effective therapy for pediatric drug-resistant epilepsy (DRE), yet treatment response varies markedly across individuals. &#x2022; Neuroinflammation is involved in epileptogenesis, and VNS may exert antiseizure effects via modulating systemic inflammation. &#x2022; Peripheral inflammatory indices are easily accessible but their associative links with VNS response remain unclear. &#x2022; This study first demonstrates that preoperative and postoperative dynamic changes in peripheral inflammatory biomarkers independently associate with VNS efficacy in children. &#x2022; Latent change score modeling reveals that postoperative reductions in neutrophil-to-lymphocyte ratio (NLR) and systemic inflammatory response index (SIRI) correlate with favorable seizure outcomes, while baseline systemic immune-inflammation index (SII) and pan-immune-inflammation value (PIV) levels help identify favorable candidates. &#x2022; These low-cost peripheral indices display correlative links with treatment outcomes and may provide preliminary reference information for auxiliary stratification and serial follow-up monitoring.