Comparative prognostic value of inflammation-based biomarkers for predicting in-hospital mortality in severe acute pancreatitis.

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.

The aim of this study was to explore the relationship between functional prognosis and the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), lymphocyte-to-monocyte ratio (LMR) and systemic inflammatory response index (SIRI) in patients with acute ischemic stroke (AIS) at discharge. A total of 861 patients with AIS were enrolled between January 2019 and December 2021. Blood cell counts were collected on admission. Logistic regression analysis was performed to assess the relationship between NLR, PLR, LMR, SIRI and adverse functional outcomes (modified Rankin scale score of 3-6) at discharge. We also used receiver operating characteristic (ROC) curves to estimate the overall ability of NLR, PLR, LMR and SIRI to judge short-term functional outcomes. Associations between NLR, PLR, LMR, and SIRI with length of hospital stay were analyzed by Spearman correlation test. A total of 194 patients (22.5%) had poor functional outcomes at discharge. Multivariate logistic regression analysis showed that NLR (odds ratio [OR], 1.060; 95% confidence interval [CI] 1.004-1.120, P=0.037), PLR (OR, 1.003; 95% CI 1.000-1.005, P=0.018), LMR (OR, 0.872; 95% CI 0.774-0.981, P=0.023) and SIRI (OR, 1.099; 95% CI 1.020-1.184, P=0.013) were independent factors for poor functional outcome. The odds ratios of the highest versus lowest quartiles of NLR, PLR and SIRI were 2.495 (95% CI 1.394-4.466), 1.959 (95% CI 1.138-3.373) and 1.866 (95% CI 1.106-3.146), respectively. The odds ratio of the lowest versus highest quartile of LMR was 2.300 (95% CI 1.331-3.975). The areas under the curve (AUCs) of the NLR, PLR, LMR, and SIRI to discriminate poor functional prognosis were 0.644, 0.587, 0.628, and 0.651, respectively. NLR, LMR, and SIRI were related with the length of hospital stay (P<0.05). NLR, PLR, LMR, and SIRI were associated with functional outcome at discharge in AIS patients. NLR, LMR and SIRI were related to hospitalization days in patients with AIS.

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.

Is to assess the diagnostic and prognostic role of different inflammatory indices in patients with benign and malignant thyroid nodules. The neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), platelet to lymphocyte ratio (PLR), derived NLR (dNLR), systemic inflammation index (SII), neutrophil to lymphocyte, platelet ratio (NLPR), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI) were assessed in150 thyroid cancer (TC) patients, 75 benign nodule patients, compared to 70 healthy controls. There was a significant difference among TC patients and control group regarding the PLR, LMR, SII, NLPR, SIRI, and AISI (p = 0.006, p < 0.001, p = 0.043,p < 0.001 p < 0.001, and p < 0.001; respectively). LMR and SIRI could efficiently differentiate malignant versus benign thyroid nodules at a cutoff of 5.2 and 0.597; respectively. LMR, PLR, SIRI, and AISI were notably associated with high-risk stratification of TC patients (p = 0.011, p = 0.035, p = 0.036, and p = 0.034; respectively). Moreover, PLR was significantly elevated in TC patients with lymph node (LN) metastasis (p = 0.010). The LMR (OR = 0.318, p < 0.001), SIRI (OR = 2.293, p = 0.001), AISI (OR = 2.714, p < 0.001), and FT4 (OR = 0.250, p < 0.001) could differentiate TC against non-TC groups. LMR, SIRI, AISI, and FT4 are independent risk factors for TC (p < 0.001, p = 0.030, p = 0.026, and p < 0.001; respectively). There was no significant impact of the assessed inflammatory indices on the disease-free survival of the patients. LMR, PLR, SII, NLPR, SIRI, and AISI could be potential supportive markers for TC diagnosis. LMR and SIRI could help in differentiating malignant versus benign thyroid nodules.

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.

ObjectivesThis study aimed to evaluate hematological inflammatory indices in patients with knee osteoarthritis and to investigate their association with radiographic disease severity. It also assessed whether these indices may have adjunctive value in distinguishing early-stage from late-stage osteoarthritis.MethodsThis retrospective study included 2176 patients diagnosed with knee osteoarthritis between January 1, 2023, and July 1, 2025. Patients aged 50-90 years with primary knee osteoarthritis and an available complete blood count (CBC) were included. Age, gender, Kellgren-Lawrence (KL) stage, neutrophil, lymphocyte, monocyte, and platelet counts were recorded. Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), systemic immune inflammation index (SII), systemic inflammation response index (SIRI), and pan-immune inflammation value (PIV) were calculated. Receiver operating characteristic (ROC) analysis and multivariable binary logistic regression adjusted for age and gender were performed.ResultsNLR (p < 0.001), MLR (p < 0.001), SII (p < 0.001), SIRI (p < 0.001), and PIV (p < 0.001) were significantly higher in patients with late-stage osteoarthritis, whereas PLR did not differ significantly between groups (p = 0.061). ROC analysis showed that NLR, MLR, SII, SIRI, and PIV had statistically significant but poor to modest discriminatory ability for late-stage osteoarthritis. Although SIRI showed the highest AUC among the evaluated indices, its performance remained within the modest range, and none of the markers demonstrated clinically meaningful discriminatory ability. In multivariable binary logistic regression analysis adjusted for age and gender, NLR, MLR, SII, SIRI, and PIV remained associated after adjustment for age and gender with late-stage osteoarthritis.ConclusionNLR, MLR, SII, SIRI, and PIV were associated with greater radiographic severity in knee osteoarthritis. Among the investigated biomarkers, SIRI, PIV, and SII showed relatively better discriminatory performance than the other indices; however, the overall ability of all markers to distinguish early-stage from late-stage osteoarthritis was limited. These findings suggest that CBC-derived inflammatory indices may serve as inexpensive adjunctive markers of radiographic severity, but they should not be used as stand-alone tools in clinical decision-making.

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.

The Pretreatment Systemic Inflammation Response Index as a Useful Prognostic Factor is Better Than Lymphocyte to Monocyte Ratio in Breast Cancer Patients Receiving Neoadjuvant Chemotherapy

BACKGROUNDAcute kidney injury (AKI) is a prevalent and common complication in critically ill patients with septic shock, associated with increased morbidity, mortality, and healthcare resource utilization in the intensive care unit (ICU). While inflammatory indices derived from standard laboratory tests – such as the neutrophil-to-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), neutrophil percentage to albumin ratio (NPAR) and aggregate index of systemic inflammation (AISI) – have emerged as promising biomarkers for systemic immune activation in critical illness, their direct value as predictors of AKI in large ICU cohorts remains uncertain.AIMTo evaluate the predictive value of inflammatory indices derived from standard laboratory tests as predictors of AKI in ICU patients with septic shock.METHODSThis retrospective cohort study utilized the eICU Collaborative Research Database, including adult patients with septic shock admitted to over 200 ICUs across the United States from 2014 to 2015. Patients with pre-existing end-stage renal disease, death within 24 hours, or insufficient data for inflammatory indices were excluded. Inflammatory markers (NLR, PLR, MLR, NPAR, SII, SIRI, AISI) and clinical variables were analyzed. Multivariable logistic regression, principal component analysis, and multilayer perceptron neural network modeling were employed to identify independent predictors of AKI, defined by Kidney Disease Global Outcomes criteria.RESULTSAmong 12660 septic shock patients, 6552 (51.7%) developed AKI during their ICU stay. Patients with AKI were older, had higher body mass index and Sequential Organ Failure Assessment scores, and a greater burden of comorbidities such as chronic kidney disease and diabetes. Univariate analysis showed significantly higher levels of NLR, MLR, SII, NPAR, SIRI, and AISI in the AKI group, suggesting an association between systemic inflammation and kidney injury. However, these indices displayed strong multicollinearity with other clinical and laboratory variables. In logistic regression, traditional predictors such as baseline serum creatinine, blood urea nitrogen, Sequential Organ Failure Assessment score, chronic kidney disease, vasopressor use, and selected comorbidities remained independently associated with AKI, while most individual inflammatory indices did not retain independent significance due to multicollinearity. To address this, principal component analysis employed, which identified three major components – an inflammatory/hematological component, a metabolic/renal/inflammatory component, and an electrolyte/age component. Incorporating these composite dimensions into predictive models significantly improved discrimination for AKI risk. Neural network models further expounded the contribution of both clinical factors and the combined inflammatory/metabolic dimension to accurate AKI prediction, capturing complex interactions and non-linear relationships not evident in traditional regression models.CONCLUSIONIn ICU patients with septic shock, composite inflammatory indices are elevated in those who develop AKI and may serve as important markers of risk. However, after accounting for multicollinearity and confounding, these markers alone offer limited incremental predictive value over traditional clinical and laboratory risk factors.

We investigated the relationship between inflammatory indicators derived from complete blood cell (CBC) counts and all-cause mortality in individuals with rheumatoid arthritis (RA). Data were collected from the National Health and Nutrition Examination Survey (NHANES) database from 2007 to 2018, with a median follow-up duration of 78 months. The inflammatory indicators derived from CBC included several types: the systemic inflammatory response index (SIRI), the systemic immune-inflammation index (SII), the neutrophil-to-lymphocyte ratio (NLR), the platelet-to-lymphocyte ratio (PLR), and the monocyte-to-lymphocyte ratio (MLR). The multiple COX regression models were used to estimate adjusted hazard ratios (HRs) and 95% CIs concerning all-cause mortality of participants with RA, which focused on CBC-derived inflammatory indicators. Additionally, restricted cubic spline (RCS) curve was utilized to investigate non-linear associations. The research comprised a cohort of 1,314 individuals, among whom 246 with RA succumbed during a median follow-up duration of 78 months. After adjusting for key covariates, the mortality rate in patients with RA who had high SIRI, NLR, and MLR levels was considerably higher than in those with medium or low SIRI, NLR, and MLR levels. Compared with the lowest tertile, the highest tertiles of SIRI (HR 1.87, 95% CI: 1.12-3.13), NLR (HR 1.79, 95% CI: 1.10-2.92), and MLR (HR 1.88, 95% CI: 1.17-3.02) were associated with an increased risk of all-cause mortality. The Kaplan-Meier analysis indicated a significant decrease in the survival probability among individuals with elevated SIRI, NLR, and MLR levels. The RCS analysis revealed a linear association between SIRI, NLR, MLR, and RA-related all-cause mortality, whereas a non-linear relationship was identified between the SII, PLR, and mortality. This investigation revealed that the SIRI, NLR, and MLR are novel, valuable, and convenient inflammatory indicators. In the United States adults with RA, higher SIRI, NLR, and MLR were independently associated with an increased long-term mortality risk. These findings not only assist in uncovering the potential utility of predicting RA outcomes but also provide rheumatologists valuable guidance for disease management.

Objective: To discuss and analyze the effects of routine therapy combined with fenethisterone on serum systemic immune inflammation index (SII), platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), neutrophil to high density lipoprotein ratio io, NHR) and Systemic Inflammation Response Index (SIRI). Methods: 60 patients with type 2 diabetes nephropathy admitted to our hospital from April to August 2020 were studied, including 20 patients with normal urinary protein, 20 patients with microalbuminuria and 20 patients with massive proteinuria. Patients with different proteinuria conditions were randomly divided into a control group and an experimental group, with 10 cases in each group. The control group received conventional therapy, while the experimental group received combined treatment with non nifedipine. Analyze and compare the changes in SII, PLR, NLR, MLR, NHR, and SIRI indicators between two groups of patients after intervention. Results: The serum SII, PLR, NLR, MLR, NHR, SIRI in patients with type 2 diabetes nephropathy with normal urinary protein, microalbumin and large proteinuria who were treated with fenelidone were significantly reduced, p &lt; 0.05, The difference is significant. Conclusion: The combination of conventional therapy and fenelidone can effectively improve the immune function of patients with type 2 diabetes nephropathy and reduce the inflammatory reaction of the body. It is an effective therapeutic drug and can be used in such patients.

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.

Thrombosis is a leading cause of mortality in polycythemia vera (PV), yet little is known about early predictors of thrombosis progression. Emerging evidence links systemic inflammation to thrombosis risk. This study assessed hematological inflammatory parameters, including the neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), platelet-to-lymphocyte ratio (PLR), systemic immune-inflammation index (SII), systemic inflammatory response index (SIRI), and aggregate index of systemic inflammation (AISI), for their utility in predicting thrombosis progression in PV. This retrospective study analyzed 102 PV patients (2008-2024) and 115 healthy controls. Clinical and laboratory data, including thrombotic events, were examined. Patients were stratified into low-and high-risk groups, further categorized by thrombosis progression. Inflammatory biomarkers were derived from baseline blood counts. Median follow-up was 51 months, the 10-year thrombotic events-free survival rate was 84.30%, and 21 patients (20.59%) showed thrombosis progression. PV patients had higher NLR, MLR, PLR, SII, SIRI, and AISI than controls. NLR, MLR, SIRI, and AISI were associated with an increased risk of thrombosis compared to the low-risk group. In the progression group, high monocytes, NLR, MLR, SIRI, AISI, and previous thrombosis were notably correlated. ROC analysis showed that MLR (AUC = 0.739), SIRI (AUC = 0.714), AISI (AUC = 0.670), and NLR (AUC = 0.649) had the highest predictive ability for thrombosis progression. Multivariate analysis identified MLR (HR = 6.979) and previous thrombosis (HR = 4.494) as independent risk factors. These findings support recent reports linking systemic inflammation to thrombosis risk in PV patients and highlight for the first time that MLR may serve as a valuable prognostic biomarker for thrombotic events.

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.

The neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), systemic immune-inflammatory index (SII), systemic inflammation response index (SIRI), and Onodera's prognostic nutritional index (OPNI) have been reported as prognostic markers for various cancers. We evaluated the prognostic value of the NLR, PLR, MLR, SII, SIRI, and OPNI for poorly-to moderately-differentiated cervical squamous cell carcinoma (CSCC). We retrospectively analyzed the cases of 109 patients with early-stage poorly-to moderately-differentiated CSCC who underwent radical surgery at our institution in 2014-2017. The optimal cutoff points for the NLR, PLR, MLR, SII, SIRI, and OPNI were determined by receiver operating characteristic curves. Overall survival was analyzed by the Kaplan-Meier method. We performed a multivariate analysis using the Cox proportional hazard regression model to determine the independent prognostic indicators for early-stage poorly-to moderately-differentiated CSCC. The appropriate cutoff points were: NLR, 1.72; PLR, 111.96; MLR, .24; SII, 566.23; SIRI, 1.38; and OPNI, 52.68. The OS of the patients with a high OPNI (P = .04), low SII (P = .03), or low SIRI (P = .01) was significantly better. The uni- and multivariate analyses identified only the OPNI as an independent prognostic marker for early-stage poorly-to moderately-differentiated CSCC (P = .04 and P = .02). The OPNI is an independent prognostic marker for early-stage poorly-to moderately-differentiated CSCC; the NLR, PLR, MLR, SII, and SIRI are not.