Correlation between CBC-derived inflammatory indicators and all-cause mortality with rheumatoid arthritis: a population-based study.

Objective: To analyze the comprehensive blood inflammation index of the patients with stage I pneumoconiosis complicated with pulmonary infection, and to explore its value in predicting the patients' disease. Methods: In September 2023, 83 patients with stage I pneumoconiosis who were treated in Tianjin Occupational Diseases Precaution and Therapeutic Hospital from November 2021 to August 2023 were selected and divided into non-infected group (56 cases) and infected group (27 cases) according to whether they were combined with lung infection. Workers with a history of dust exposure but diagnosed without pneumoconiosis during the same period were selected as the control group (65 cases) . By referring to medical records and collecting clinical data such as gender, age, occupational history, past medical history, hematology testing, the differences in the comprehensive blood inflammation indexes among the three groups were compared, ROC curve was drawn, and the relationship between comprehensive blood inflammation indexes and stage I pneumoconiosis and its combined lung infection was analyzed. Results: There were significtant differences in the number of neutrophils (N) , the number of lymphocytes (L) , the number of monocytes (M) , C-reactive protein (CRP) , the neutrophil to lymphocyte ratio (NLR) , the monocyte to lymphocyte ratio (MLR) , the platelet to lymphocyte ratio (PLR) , the systemic immune-inflammatory index (SII) , the systemic inflammation response index (SIRI) , the aggregate index of systemic inflammation (AISI) , the derived neutrophil to lymphocyte ratio (dNLR) , the neutrophil to lymphocyte and platelet ratio (NLPR) , and the C-reactive protein to lymphocyte ratio (CLR) (P<0.05) . Compared with the control group, MLR, SIRI and AISI in the non-infected group were significantly increased (P<0.05) . NLR, MLR, PLR, SII, SIRI, AISI, dNLR, NLPR, CLR were significantly increased (P<0.05) . Compared with the non-infected group, NLR, PLR, SII, SIRI, AISI, dNLR, NLPR and CLR were significantly increased in the infected group (P<0.05) . ROC analysis showed that NLR, MLR, PLR, SII, SIRI and AISI had a certain predictive capability for stage I pneumoconiosis (P<0.05) , among which MLR had the highest efficacy, with an AUC of 0.791 (95% CI: 0.710-0.873) , the cut-off value was 0.18, the sensitivity was 71.4%, and the specificity was 78.5%. NLR, MLR, PLR, SII, SIRI, AISI, dNLR, NLPR and CLR all had a certain predictive capability forstage I pneumoconiosis combined lung infection (P<0.05) , among which CLR had the highest efficacy, with an AUC of 0.904 (95%CI: 0.824~0.985) , the cut-off value was 5.33, sensitivity was 77.8%, specificity was 98.2%. Conclusion: The comprehensive blood inflammation index may be an auxiliary predictor of stage I pneumoconiosis and its combined lung infections.

BackgroundCardiovascular-kidney-metabolic (CKM) syndrome is a major public health concern associated with increased mortality. Inflammation plays a critical role in CKM progression and outcomes. This study investigates the relationship between inflammatory indices and mortality risk in CKM patients.MethodsA comprehensive analysis of data from 26,265 participants in the National Health and Nutrition Examination Survey (NHANES) database (2007–2016) with CKM syndrome stages 0–4 was conducted. The primary outcomes of the study were all-cause and cardiovascular mortality. The inflammatory indices encompassed the systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), aggregate index of systemic inflammation (AISI), and neutrophil-to-albumin ratio (NAR). Multivariable Cox models, adjusted for demographic and clinical confounders, were employed to examine nonlinearity, alongside restricted cubic splines and threshold analyses. The present study sought to compare the prognostic accuracy of the time-dependent ROC (Receiver Operating Characteristic) at 93 months.ResultsDuring a median follow-up of 93.4 months, 2,292 subjects experienced all-cause mortality and 701 experienced cardiovascular deaths. In the adjusted models, elevated SIRI (all-cause HR 1.11, 95% CI 1.06–1.15; cardiovascular HR 1.18, 1.10–1.27), NLR (all-cause HR 1.08, 1.05–1.12; cardiovascular HR 1.11, 1.05–1.17) and MLR (all-cause HR 2.27, 1.71–3.01; cardiovascular HR 3.37, 2.09–5.44) were independently associated with mortality (all p < 0.0001). Dose–response analyses revealed nonlinear J-shaped relationships: MLR showed marked risk above 0.19 (HR 2.59), NLR risk was greatest below 3 (HR 1.14), and SIRI thresholds differed for all-cause (> 1.74, HR 1.09) versus cardiovascular (> 0.38, HR 1.17) outcomes. At 93 months, MLR demonstrated the highest discriminatory ability (AUC 0.630; C-index 0.667; p < 0.001), outperforming SIRI (AUC 0.611) and NLR (AUC 0.602). PLR, AISI, SII and NAR showed limited predictive value due to imbalanced sensitivity–specificity. The impact of age and the early stages of CKD on the modification of associations was investigated.ConclusionSystemic inflammatory indices demonstrated nonlinear, J-shaped associations with mortality in CKM syndrome, with the MLR showing the strongest association across disease trajectories. MLR, NLR, and SIRI were identified as potential risk indicators, with stronger associations observed in younger patients and those with early-stage CKM syndrome.HighlightsSystemic inflammatory markers (SIRI, NLR, MLR) were significantly associated with increased mortality risk in CKM syndrome.Most inflammation indices exhibited nonlinear, J-shaped associations with mortality.Nonlinear threshold analyses identified specific risk inflection points for SIRI, NLR, and MLR.These associations were stronger in younger patients (≤ 60 years) and those with early CKM stages (1–2).Supplementary InformationThe online version contains supplementary material available at 10.1007/s12026-025-09707-5.

ObjectiveThis investigation intends to clarify the disparities in hematological parameters and ratios among different age groups,providing new insights for the diagnostic of Mycobacterium Avium Complex Pulmonary Disease (MAC-PD).Patients and MethodsA retrospective investigation was undertaken to examine the hematological parameters of elderly (n=88) and non-elderly (n=44) patients diagnosed with MAC-PD at Hebei Chest Hospital between 2020 and 2024. The study involved the calculation of the neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), platelet-to-lymphocyte ratio (PLR), hemoglobin-to-lymphocyte ratio (HLR),hemoglobin-to-platelet ratio (HPR),systemic inflammatory response index (SIRI) and systemic immune-inflammation index (SII). Statistical analyses were executed utilizing SPSS 27.0 and R (4.2.1) software.ResultsThe levels of absolute lymphocyte count (ALC),hemoglobin (Hb) and LMR were lower in Elderly MAC group compared to Non-elderly MAC group. Conversely,the levels of NLR, PLR,HLR,SIRI and SII were higher in Elderly MAC group than in Non-elderly MAC group. There was a certain correlation between the Ct value of MAC nucleic acid and NLR, LMR, SIRI and SII (P<0.05) in Elderly MAC group. In Non-elderly MAC group, the Ct value of MAC nucleic acid was correlated with absolute neutrophil count (ANC), LMR, SIRI and SII (P<0.05). Receiver operating characteristic curve (ROC) analysis indicated that NLR, LMR, SIRI and SII exhibited high diagnostic value in Elderly MAC group,while LMR, SIRI and SII demonstrated high diagnostic value in Non-elderly MAC group. The combined diagnostic value was even more prominent. Nevertheless,no significant diagnostic indicators were identified between Elderly MAC group and Non-elderly MAC group.ConclusionThe combination of NLR, LMR, SIRI and SII may serve as diagnostic markers for Elderly MAC-PD and the combination of LMR, SIRI and SII may serve as diagnostic markers for Non-lderly MAC-PD. But there were no significant diagnostic indicators differentiating Elderly MAC group from Non-elderly MAC group.

Background Inflammation and hyperuricemia are closely associated with chronic kidney disease (CKD). The systemic inflammation response index (SIRI), systemic immune-inflammation index (SII), monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), and platelet-to-lymphocyte ratio (PLR) are emerging as novel biomarkers. While, the synergistic effects of these biomarkers with hyperuricemia on CKD remain unclear. Method We analyzed 10,226 participants from 2015–2020 National Health and Nutrition Examination Survey (NHANES). The relationships among inflammatory biomarkers (SIRI, SII, MLR, NLR, and PLR), hyperuricemia and CKD were assessed by multivariate logistic regression models. Restricted cubic splines (RCS) and segmented regression models were used to evaluate the nonlinear relationships. The diagnostic performance was evaluated using receiver operating characteristic (ROC) curve, and incremental predictive value was further calculated by Net Reclassification Improvement (NRI) and Integrated Discrimination Improvement (IDI). The interaction analysis was performed to explore the combined effects. Results SIRI, SII, MLR, and NLR were significantly linked with CKD. MLR exhibited a threshold effect at 0.22 (p-non-linear < 0.05), with significantly stronger association with CKD above this cutoff. SIRI demonstrated the best diagnostic accuracy among these biomarkers. Significant interactions were observed between hyperuricemia and inflammatory biomarkers (SIRI, SII, MLR, NLR), indicating that the association between inflammatory biomarkers and CKD is more pronounced in the presence of hyperuricemia. Conclusion There were significant associations between inflammatory biomarkers (SII, SIRI, NLR, MLR) and CKD, with particularly stronger correlations observed in patients with hyperuricemia.

Inflammation is recognized as a critical component in the pathogenesis of lower extremity peripheral arterial disease (PAD); however, the association between novel immune-inflammatory biomarkers - neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), Systemic Immune-Inflammation Index (SII), Systemic Inflammatory Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI) - and PAD risk in the general population remains unexplored. This study examines the associations between PAD and NLR, PLR, MLR, SII, SIRI, and AISI. This study was a cross-sectional observational study based on the National Health and Nutrition Examination Survey (NHANES) from 1999 to 2004. PAD was diagnosed using an Ankle-Brachial Index (ABI) ≤0.9. Finally, 6314 participants aged ≥40 years with complete information about ABI, blood cell counts, and other covariates were analyzed. Logistic regression analysis was used to examine the associations between inflammatory biomarkers and PAD. The predictive ability of inflammatory biomarkers for PAD was compared using receiver operating characteristic (ROC) curves. Subsequent mediation analysis examined the indirect effects of immune-inflammatory biomarkers on PAD via estimated glomerular filtration rate (eGFR). Finally, we performed propensity score matching (PSM) between PAD and non-PAD participants to verify the robustness of results. In 6314 US adults aged ≥40 years, 548 were diagnosed with PAD. Significant associations were observed between PAD and NLR (odds ratio [OR]: 1.02; 95% confidence interval [CI]: 1.01-1.04), MLR (OR: 1.02; 95% CI: 1.00-1.04), SII (OR: 1.02; 95% CI: 1.00-1.03), SIRI (OR: 1.03; 95% CI: 1.01-1.04), and AISI (OR: 1.02; 95% CI: 1.01-1.03), according to logistic regression. PSM further validated the robustness of primary results. Mediation analysis revealed eGFR mediated portions of the relationship between PAD and NLR, MLR and SIRI (4.69%, 7.11% and 3.69% respectively). Additionally, ROC showed that SIRI exhibited a greater identification of PAD compared with other immune-inflammatory biomarkers. NLR, MLR, SII, SIRI, and AISI demonstrated independent associations with PAD risk, with SIRI showing a stronger association with PAD.

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). 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. 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. 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.

BackgroundThe inflammatory burden index (IBI) is a comprehensive indicator that integrates multiple hematological parameters to reflect systemic inflammatory status, and has demonstrated good predictive ability in various diseases. However, systematic research on the application of IBI in asthma remains lacking. This study aims to evaluate the association between IBI and the prevalence of adult asthma as well as all-cause mortality, while comparing IBI and other inflammatory indicators in predictive ability in the prevalence and mortality of adult asthma.MethodsThis study utilized data from the National Health and Nutrition Examination Survey (NHANES), a nationally representative cross-sectional survey based on the general population of the United States. Weighted logistic regression models were employed to examine the association between IBI and asthma prevalence, while weighted Cox proportional hazards models were used to analyze the relationship between IBI and all-cause mortality in asthma patients. Restricted cubic splines (RCS) were used to analyze the nonlinear relationships between IBI and asthma prevalence, as well as all-cause mortality. Receiver operating characteristic (ROC) curves were constructed to compare the predictive value of IBI with that of the systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and monocyte-to-lymphocyte ratio (MLR) for asthma prevalence and mortality outcomes. Additionally, stratified subgroup analyses and multiple sensitivity analyses were conducted to validate the robustness of the findings.ResultsThis study included a total of 23,758 participants. After multivariate adjustment for confounders, higher IBI levels showed a significantly positive association with asthma risk [odds ratio (OR) =1.21, 95% confidence interval (CI): 1.04–1.41]. In survival analysis, during a median follow-up of 13.92 (13.67–14.17) years, 577 all-cause death events were recorded among asthma patients. Cox proportional hazards models revealed that compared with the low IBI group, the high IBI group had significantly increased all-cause mortality risk [hazard ratio (HR) =2.50, 95% CI: 1.79–3.50]. ROC analysis demonstrated that IBI achieved an area under the curve (AUC) of 0.541 (95% CI: 0.529–0.552) for asthma prevalence, showing superior predictive ability compared to other inflammatory markers (SII, SIRI, NLR, PLR, MLR) (P<0.05). Time-dependent ROC curve analysis evaluating inflammatory markers’ predictive performance for all-cause mortality showed that IBI’s AUC was 0.701 in the 1-year follow-up interval, though its predictive efficacy gradually declined over time. Notably, for long-term follow-up times (16.17 years), IBI maintained better predictive ability for all-cause mortality than SII, NLR and PLR (P<0.01).ConclusionsElevated IBI levels are significantly associated with increased asthma prevalence and all-cause mortality. The IBI demonstrates clinically meaningful predictive value for asthma-related mortality, with particularly good short-term predictive performance. Further research should investigate its potential utility paired with integrated biomarker-based diagnostic frameworks.

Introduction The inflammatory response following an Acute Myocardial Infarction (AMI) has been extensively studied in recent years and plays a crucial role in post-infarction outcomes. Inflammation contributes to infarct size expansion, is directly linked to ischemia-reperfusion injury, and can lead to adverse left ventricular remodelling, resulting in a larger infarct size and worse prognosis. Therefore, quantifying inflammation may serve as an important prognostic marker in AMI patients. Objective The INFINITY study (INFlammatIoN amI sTudY) investigates the role of selected inflammatory biomarkers in predicting long-term outcomes after AMI. This sub-study evaluates the prognostic value of five inflammatory indexes: Systemic Immune Inflammation Index (SII), Neutrophil-to-Lymphocyte Ratio (NLR), Lymphocyte-to-Monocyte Ratio (LMR), Platelet-to-Lymphocyte Ratio (PLR), Systemic Inflammation Response Index (SIRI). The study focuses on their association with short-term (in-hospital, M0) and long-term (1-month, M1 and 6-month, M6) Major Adverse Cardiovascular Events (MACEs), including cardiac death, non-fatal MI, unplanned revascularization, development of heart failure, angina or recurrent ACS requiring rehospitalization, and major bleeding. Methods A total of 103 patients with AMI (67 STEMI, 36 NSTEMI) were included in the study. Statistical analysis was performed using Cox proportional hazards models to assess the relationship between inflammatory indexes and clinical endpoints. The models were adjusted for age, sex, comorbidities, infarct size, and treatment strategy to account for potential confounders. Results The inflammatory indices SII, NLR, LMR, PLR, and SIRI showed a significant association with MACEs at 6 months. SII was strongly associated with MACEs both in-hospital (M0: p = 0.013) and at 1 month (M1: p = 0.007). SIRI and NLR demonstrated high predictive value for post-infarction MACEs (M1: p = 0.049, p = 0.020, respectively). LMR appeared to have a protective role, as higher values were associated with a lower risk of MACEs (M0: p = 0.234, M1: p = 0.106, M6: p = 0.236). PLR had moderate diagnostic value (M0: p = 0.080, M1: p = 0.024, M6: p = 0.306) but was influenced by other clinical factors. Cox regression models confirmed that SII and SIRI are independent predictors of MACEs, whereas LMR may act as a protective factor. Conclusions Inflammatory markers SII, NLR, SIRI, LMR, and PLR appear to have prognostic significance in AMI patients. Among them, SII and SIRI demonstrated the strongest association with major adverse cardiovascular events (MACEs) and heart failure development. Conversely, LMR may play a protective role. These inflammatory indexes could contribute to improved risk stratification and personalized post-infarction patient monitoring.Table 1 Figure 1

Addictive disorders are associated with systemic and central nervous system inflammation, which may be important for the onset and development of these diseases. Although lymphocyte-related parameters have recently been studied in alcohol use disorder (AUD), systemic immune-inflammation index (SII) and systemic inflammatory response index (SIRI) haven’t. Lymphocyte-related ratios, SII and SIRI levels were evaluated between AUD and healthy controls (HC) in this study. It was a retrospective and cross-sectional study. This study included 72 patients with AUD and 184 individuals in the HC group. Lymphocyte related ratios such as neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR) and platelet to lymphocyte ratio (PLR), SII and SIRI values were compared. Compared to HC group, NLR (p < 0.001), MLR (p < 0.001), and SIRI (p < 0.001) levels were significantly higher in AUD group. There was also a significant relationship between NLR and AST/ALT ratio in the AUD group (p = 0.022). The results of this study support that AUD is a chronic inflammatory psychiatric disorder. In addition, it may be useful to evaluate these markers in relation to liver enzymes in patients with AUD, as alcohol consumption causes liver damage. These markers may also be used in future studies to assess treatment response and disease severity.

PurposeStroke is a disease associated with high mortality. Many inflammatory indicators such as neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte to monocyte ratio (LMR) and red blood cell distribution width (RDW) have been documented to predict stroke prognosis, their predictive power is limited. A novel inflammatory indicator called systemic inflammatory response index (SIRI) has been advocated to have an essential role in the prognostic assessment of cancer and infectious diseases. In this study, we attempted to assess the prognosis of stroke by SIRI. Moreover, we compared SIRI with other clinical parameters, including NLR, PLR, LMR and RDW.MethodsThis was a retrospective cohort study. We obtained data of 2450 stroke patients from the Multiparametric Intelligent Monitoring in Intensive Care III database. We used the Cox proportional hazards models to evaluate the relationship between SIRI and all-cause mortality and sepsis. Receiver operating curve (ROC) analysis was used to assess the predictive power of SIRI compared to NLR, PLR, LMR and RDW for the prognosis of stroke. We collected data of 180 patients from the First Affiliated Hospital of Wenzhou Medical University, which used the Pearson’s correlation coefficient to assess the relationship between SIRI and the National Institute of Health stroke scale (NIHSS).ResultsAfter adjusting multiple covariates, we found that SIRI was associated with all-cause mortality in stroke patients. Rising SIRI accompanied by rising mortality. Besides, ROC analysis showed that the area under the curve of SIRI was significantly greater than for NLR, PLR, LMR and RDW. Besides, Pearson’s correlation test confirmed a significant positive correlation between SIRI and NIHSS.ConclusionElevated SIRI was associated with higher risk of mortality and sepsis and higher stroke severity. Therefore, SIRI is a promising low-grade inflammatory factor for predicting stroke prognosis that outperformed NLR, PLR, LMR, and RDW in predictive power.

Objectives:To uncover the predictive value of systemic immune-inflammatory index (SII) and systemic inflammatory response index (SIRI) on early pregnancy loss.Methods:A total of 535 individuals were enrolled in this retrospective analysis. The early pregnancy losses (EPL) group included patients between 18-35 years old who experienced EPL. The control group comprised healthy pregnant women who gave birth at ≥37 weeks.Results:The EPL group had significantly lower plateletcrit (p=0.04), platelet distribution width (PDW, p<0.0001), and RDW (p<0.0001) and higher monocyte (p<0.0001) and SIRI (p<0.0001) values than the control group. The hemoglobin, white blood cells, platelet count, neutrophil count, lymphocyte count, mean platelet volume, neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and SII values were not significantly different between the EPL and control groups (p>0.05). The cut-off value for the SIRI that offers the best sensitivity/specificity balance was 1.48 (sensitivity of 63%; specificity of 63%) in the receiver operating characteristics curve. Among the inflammatory parameters for predicting EPL, PDW had highest specificity (84%), and RDW had the highest sensitivity (80%).Conclusion:This study provides compelling evidence that various inflammatory pathways may significantly contribute to EPL pathogenesis. Moreover, our findings suggest that SIRI could be a more effective marker than NLR, PLR, MLR, and SII in predicting EPL in an ongoing pregnancy, thereby potentially revolutionizing early pregnancy loss diagnostics.

To investigate the predictive value of various inflammatory biomarkers in patients with acute ischemic stroke (AIS) and evaluate the relationship between stroke-associated pneumonia (SAP) and the best predictive index. We calculated the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), prognostic nutritional index (PNI), systemic inflammation response index (SIRI), systemic immune inflammation index (SII), Glasgow prognostic score (GPS), modified Glasgow prognostic score (mGPS), and prognostic index (PI). Variables were selectively included in the logistic regression analysis to explore the associations of NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI with SAP. We assessed the predictive performance of biomarkers by analyzing receiver operating characteristic (ROC) curves. We further used restricted cubic splines (RCS) to investigate the association. Next, we conducted subgroup analyses to investigate whether specific populations were more susceptible to NLR. NLR, PLR, MLR, SIRI, SII, GPS, mGPS, and PI increased significantly in SAP patients, and PNI was significantly decreased. After adjustment for potential confounders, the association of inflammatory biomarkers with SAP persisted. NLR showed the most favorable discriminative performance and was an independent risk factor predicting SAP. The RCS showed an increasing nonlinear trend of SAP risk with increasing NLR. The AUC of the combined indicator of NLR and C-reactive protein (CRP) was significantly higher than those of NLR and CRP alone (DeLong test, P<0.001). Subgroup analyses suggested good generalizability of the predictive effect. NLR, PLR, MLR, PNI, SIRI, SII, GPS, mGPS, and PI can predict the occurrence of SAP. Among the indices, the NLR was the best predictor of SAP occurrence. It can therefore be used for the early identification of SAP.

BackgroundRheumatoid arthritis (RA) is an autoimmune disease for which better biomarkers are needed, especially in seronegative cases. This study evaluates complete blood count (CBC)-derived inflammatory indices – neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), and systemic inflammation response index (SIRI) – for RA diagnosis and disease activity assessment, with comparisons between seropositive and seronegative RA.MethodsWe conducted a retrospective case–control study of 230 RA patients and 115 age- and sex-matched healthy controls. CBC-derived indices were calculated from routine blood counts. Diagnostic performance was evaluated using receiver operating characteristic (ROC) curves (area under the curve, AUC) for RA versus controls overall and stratified by serostatus. Associations with disease activity (DAS28-CRP, SDAI, CDAI) were assessed via correlations and ROC analysis for active (moderate/high) versus inactive (remission/low) RA.ResultsAll five indices were significantly elevated in RA patients compared to controls (all P < 0.001). MLR showed the highest diagnostic accuracy (AUC = 0.771), followed by SIRI (0.72) and PLR (0.70); NLR and SII were more modest (≈0.69–0.68). In seronegative RA, diagnostic discrimination declined (best AUC = 0.707 for MLR; SII and SIRI AUCs ~0.56–0.59). NLR, SII, and SIRI correlated moderately with CRP, ESR, and composite scores (Spearman ρ ~0.3–0.4, P < 0.001), and were higher in active RA (DAS28-CRP AUCs 0.668–0.700). SII and SIRI provided the top discrimination of active disease (AUC ~0.70). PLR showed minimal correlation with activity and no significant difference between active and inactive RA.ConclusionCBC-derived inflammatory indices are elevated in RA and reflect systemic inflammation. MLR is the most robust index for distinguishing RA from healthy individuals, while SII, SIRI, and NLR are useful for gauging disease activity. In seronegative RA, diagnostic performance was attenuated overall, with MLR retaining fair discrimination while SII/SIRI/NLR showed limited utility.

Erectile dysfunction(ED), a prevalent condition within the male genitourinary system, significantly impairs the quality of life for affected men. Although certain inflammatory indicators, such as the neutrophil-to-lymphocyte ratio(NLR), systemic inflammatory response index (SIRI), and systemic immune-inflammation index(SII), have been linked to ED, the correlation with other markers and their impact on survival outcomes in ED patients remain largely unexplored. This research aims to investigate the correlation between inflammatory biomarkers derived from a complete blood cell count(CBC) and the occurrence of ED. Data regarding ED were extracted from the 2001–2004 National Health and Nutrition Examination Survey(NHANES), and mortality events were ascertained through the National Death Index up to December 2019. The CBC-derived inflammatory indicators assessed in this study included the NLR, derived neutrophil-to-lymphocyte ratio(dNLR), monocyte-to-lymphocyte ratio(MLR), neutrophil-monocyte to lymphocyte ratio (NMLR), SIRI, and SII. The prognostic significance of these CBC-derived inflammatory indicators was evaluated using random survival forests(RSF) analysis. Our study encompassed a cohort of 3,639 individuals, among whom 1,031 were diagnosed with ED. Among individuals with ED, 610 experienced all-cause mortality. Following adjustment for all confounding variables, it was observed that elevated levels of NLR(OR = 1.09, 95%CI 1.00–1.19, p = 0.021), MLR (OR = 2.97, 95% CI 1.18–7.50, p = 0.01), NMLR(OR = 1.10, 95% CI 1.01–1.11, p = 0.006), and SIRI(OR = 1.11, 95% CI 1.01–1.22, p = 0.017) were associated with an increased prevalence of ED. Among participants with ED, those in the highest quartile of NLR(HR = 1.06, 95% CI 1.00–1.11, p = 0.032), MLR(HR = 2.00, 95% CI 1.33–3.01, p < 0.001), NMLR (HR = 1.06, 95% CI 1.01–1.11, p = 0.024), and SII(HR = 1.00, 95% CI 1.00–1.00, p = 0.015) exhibited an elevated risk of all-cause mortality compared to those in the lower levels of inflammation-derived indicators. Our research suggests that, compared with other inflammatory markers derived from complete blood cell count, MLR has the highest predictive power for the prevalence of ED and all-cause mortality in these populations.

Apart from being a primary cause of morbidity and mortality globally, gastrointestinal (GI) disorders also contribute significantly to the cost of healthcare. In patients with GI diseases, the systemic inflammatory response index (SIRI) is not often used as a marker of systemic immune inflammation to assess mortality-associated risk from malignant neoplasms or all causes. Therefore, the objective of this study was to elaborate on the link between SIRI and all causes and malignant neoplasm mortality in patients with GI disorders. Retrospective analysis was performed using National Health and Nutrition Examination Survey (NHANES) data from 1999 to 2018. Restricted cubic spline (RCS) plots and multivariate Cox proportional hazards regression were used to examine the relationship between SIRI and GI patient mortality from malignant neoplasms and all causes. Data on survival were shown using Kaplan-Meier (KM) survival curves, and these correlations were further explored by subgroup and interaction analyses. Receiver operating characteristic (ROC) curves were generated to evaluate the specificity and sensitivity of SIRI in predicting mortality among patients with GI diseases. This study included 4,137 GI patients who were followed comprehensively over 20 years, during which 165 malignant neoplasm mortality and 713 all-cause mortalities were recorded. A nonlinear association between all-cause mortality and SIRI was observed, whereas in GI patients, a linear relationship was identified between SIRI and cancer-related death. The hazard ratio (HR) was 1 at a SIRI level of 1.114, indicating the low-to-high mortality risk change. Participants in the highest quartile (Q4) in the fully adjusted model (model 3) showed a significantly greater likelihood of death from both malignant neoplasms and all-cause relative to those in the lowest quartile (Q1). The mortality HR for malignant neoplasms was 1.74 [95% confidence interval (CI): 1.08-2.82], whereas the HR for all-cause mortality was 2.50 (95% CI: 1.95-3.20). Furthermore, subgroup analysis revealed that higher SIRI was linked with a higher malignant neoplasm mortality risk among male, low-income, smoking, and drinking GI patients. Comparing SIRI to the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII), the ROC curve analysis showed that SIRI had better diagnostic effectiveness. Interaction study verified that SIRI is an independent variable that significantly increases the probability of death from both all-cause and malignant neoplasms. The nonlinear positive correlation between the SIRI and the mortality from malignant neoplasms and all-cause in GI patients is highlighted by this study. Elevated SIRI levels were significantly linked to a higher mortality rate from GI disorders, including malignant neoplasms and all-cause. Thus, in GI patients, SIRI can be used as a prognostic marker for mortality and long-term health outcomes prediction.