Biomarkers Of Systemic Inflammatory Response Research Articles

Hyperexpression of Proinflammatory Cytokines in Blood as a Biomarker of Systemic Inflammatory Response in Schizophrenia: Scoping Review

Introduction: An imbalance of the genetically determined cytokine response plays a key role in the etiology of treatment-resistant schizophrenia (TRS). In recent years, an attempt has been made to evaluate the prognostic role of systemic inflammation in the development of TRS. The problem requires a multidisciplinary approach on the part of the specialists in the following clinical disciplines: psychiatry, immunology, experimental medicine and pharmacogenetics. The solution of this problem is possible with the involvement of preventive and personalized medicine. The purpose: Evaluation the prognostic role of genetic polymorphisms of pro-inflammatory cytokines in the development of TRS. Materials and Methods: We conducted a keyword-based analysis of the English and Russian-language articles published within the past 5 years. The following databases were used in the study: PubMed, MedLine, Web of Science Core Collection (Clarivate Analytics), Web Science, Russian Science Citation Index, Scopus, Scientific Research, Google Scholar, Oxford Press, and eLibrary. Results: In a number of the analyzed works, an increased level of pro-inflammatory cytokine production was noted in patients with TRS. Based on this, single nucleotide variants (SNVs), their influence on the expression of pro- and anti-inflammatory cytokine genes, as well as their predictor role in the development of TRS. The most promising SNVs for further studies were identified. Conclusion: The risk of developing TRS is associated with a genetically determined status of the cytokine response and its regulation. Studies of the association of various SNVs of genes encoding pro-inflammatory cytokines in the Russian Federation need to be continued.

Systemic Immune-Inflammation Index Predicts the Prognosis of Traumatic Brain Injury

ObjectiveSystemic inflammation following traumatic brain injury (TBI) has been extensively studied over the past decades, as it contributes significantly to the pathophysiological injury mechanisms and subsequent poor outcomes. Systemic immune-inflammation (SII) index is a novel biomarker of systemic inflammatory response. However, its predictive value regarding TBI prognosis in clinical practice remains insufficiently investigated. MethodsA total of 102 TBI patients admitted to Nanjing Drum Tower Hospital from July 2019 to February 2022 were enrolled. We employed various statistical analyses to evaluate the correlation between inflammatory indicators upon admission and patient prognosis, compared the predictive accuracy of these indicators, and generated ROC analysis to test their prognostic performance. ResultsThe SII index, platelet count (PLT), absolute lymphocyte count (ALC), and neutrophil/lymphocyte ratio (NLR) were capable of distinguishing TBI prognosis according to univariate logistic regression models (P<0.05). Multivariate logistic regression models revealed that increased SII index, PLT, and NLR upon admission were independent predictors of poor TBI prognosis (P<0.05). ROC analysis further demonstrated that the SII index (AUC=0.845, 95% CI 0.769-0.921, P=0.000) exhibited higher predictive ability than the NLR (AUC=0.694, 95% CI 0.591-0.796, P=0.001). ConclusionsOur findings suggested that increased SII index during the early stages of TBI was an independent risk factor for poor prognosis with satisfactory predictive value. The SII index provides a reliable, convenient, and cost-effective prognostic model to evaluate systemic inflammation after TBI and identify patients at risk of poor outcomes, thereby offering valuable guidance for clinical practice.

About the associations of vitamin D deficiency and biomarkers of systemic inflammatory response with all-cause and cause-specific mortality in a general population sample of almost 400,000 UK Biobank participants

It is unknown whether the well-known association between vitamin D deficiency and mortality could be explained by the immune system modulating effects of vitamin D, which may protect from a systemic inflammatory response (SIR) to adverse health conditions. This study aims to investigate the interrelationships of vitamin D deficiency, biomarkers of SIR, and mortality. We used multivariate logistic regression with adjustment for 51 covariates to assess the associations of vitamin D deficiency with disadvantageous levels of nine biomarkers of SIR in the UK Biobank cohort. Furthermore, we tested with Cox regression and mediation analysis whether biomarkers of SIR and vitamin D deficiency were independently associated with mortality. We included 397,737 participants aged 37–73 years. Vitamin D deficiency was associated with disadvantageous levels of all blood cell count-based biomarkers, but not with C-reactive protein (CRP)-based biomarkers after adjustment for body weight. Vitamin D deficiency and all biomarkers of SIR were significantly associated with all-cause mortality and mortality from cancer, cardiovascular and respiratory disease. The strength of these associations was unaltered if vitamin D deficiency and biomarkers of SIR were put in the same model. This finding was further supported by the mediation analyses. This study showed that vitamin D deficiency is associated with disadvantageous levels of blood cell count-based but not CRP-based biomarkers of SIR. Vitamin D deficiency and systemic inflammation were independently and strongly associated with mortality. The potential of clinical interventions against both vitamin D deficiency and underlying causes of systemic inflammation should be explored.

Stratifying Risk for Pancreatic Cancer by Multiplexed Blood Test.

Pancreatic ductal adenocarcinoma (PDAC) is a highly lethal disease, for which mortality closely parallels incidence. So far, the available techniques for PDAC detection are either too invasive or not sensitive enough. To overcome this limitation, here we present a multiplexed point-of-care test that provides a "risk score" for each subject under investigation, by combining systemic inflammatory response biomarkers, standard laboratory tests, and the most recent nanoparticle-enabled blood (NEB) tests. The former parameters are routinely evaluated in clinical practice, whereas NEB tests have been recently proven as promising tools to assist in PDAC diagnosis. Our results revealed that PDAC patients and healthy subjects can be distinguished accurately (i.e., 88.9% specificity, 93.6% sensitivity) by the presented multiplexed point-of-care test, in a quick, non-invasive, and highly cost-efficient way. Furthermore, the test allows for the definition of a "risk threshold", which can help clinicians to trace the optimal diagnostic and therapeutic care pathway for each patient. For these reasons, we envision that this work may accelerate progress in the early detection of PDAC and contribute to the design of screening programs for high-risk populations.

Predictability of Neutrophil to Lymphocyte Ratio in preoperative elderly hip fracture patients for post-operative short-term complications: a retrospective study

PurposeNeutrophil to Lymphocyte Ratio (NLR) is a simple biomarker of systemic inflammatory response. We investigated predictability of NLR for early adverse outcome after surgery for hip fracture in elderly population.MethodsWe reviewed a total of 971 elderly patients with hip fracture who underwent emergency surgery between January 2017 and July 2020 in the Department of Orthopaedics Surgery at the Wollongong Hospital. After considering exclusion criteria, data from a total of 834 patients included in our study. Socio-demographic data, NLR in admission, updated Charlson comorbidity index (uCCI), biochemical markers, mortality rate and 15 short term post-operative complications were collected to determine predictability of NLR for post-operative complications and mortality.ResultsAfter hip surgery, Hospital in-patient case fatality rate was 3.7% (31). In addition, 63.1% (511) of the patients had at least one complication or more. Logistic regression demonstrated that raised NLR (P-value < 0.001, OR 1.05) and uCCI≥4 (P-Value < 0.001, OR 1.75) are associated with post-operative complications. Moreover, decreased haemoglobin was associated with adverse effects (P-value < 0.001, OR 0.97). No association was found for any of these variables with in-patient mortality except for albumin (P-value: 0.03). In addition, despite significant association, ROC analyses showed a low predictability for each of the above variables including NLR (AUC 0.59) for post-operative complications.ConclusionsDespite significant association, NLR was unable to prognosticate early adverse outcomes. However, it can be considered as a risk factor in admission for postoperative complications in combination with other risk factors and clinical context.

Lymphocyte subset is more suitable than systemic inflammatory response biomarker and immunoglobulin in constructing prognostic nomogram model for advanced gastric cancer

The serum factors of inflammation are known to be useful prognostic indicators of gastric cancer (GC). However, few studies have made comparisons to screen out more suitable biomarkers for the construction of Nomogram models. In this study, 566 patients who underwent radical gastrectomy were randomly selected. We evaluated the prognostic value of markers of systemic inflammation, including WBC, NLR, PLR, circulating total T cells, CD4+T cells, CD8+T cells and CD19+B cells, serum IgA, IgM, IgE and IgG, and compared them with traditional tumor markers (CEA, CA19-9, CA72-4 and CA125). Kaplan‒Meier analysis was used to analyze the correlation between biomarkers and overall survival (OS). We used time-dependent ROC analysis to investigate the prognostic accuracy of each biomarker. The risk of death was evaluated by the Cox regression model, and the Nomogram model was constructed by R software. We found that circulating total T cells, CD8+T cells, CEA, and CA125 had statistical significance in predicting advanced GC prognosis. Circulating CD8+T cells and CA125 were continuously superior to circulating total T cells and CEA in the prediction of 5-year OS. Cox regression found that CA125, circulating CD8+T cells, sex, and lymph node metastasis rate were independent risk factors for advanced GC. Furthermore, we combined all these predictors to construct a nomogram, which can supplement the AJCC 8th system. According to the comparison with commonly used serum immune biomarkers, circulating CD8+T cells is more sensitive to advanced GC. The prediction function of the Nomogram will supplement the traditional AJCC system, which contributes to individual survival prediction.

INFLUENCE OF IL-6 VARIANTS TO BLOOD-TRANSFUSION NUMBERS IN HEART DISEASES

Investigate a possible association between SNVs of IL6 and IL-6 serum levels with clinical and laboratory data in adults with cardiovascular disease followed at the Hospital Universitário Francisca Mendes (HUFM) in Manaus ‒ Amazonas. This study, a cross-sectional design, was carried out between March/2018 and October/2020. 159 patients with diagnosis, surgical intervention and treatment to some cardiomyopathies were included. Patients answered a questionnaire and provided blood sample. Hematological and biochemical data was obtained from the medical records. DNA extraction was performed by Brazol method (LGC Biotecnologia, SP Brazil). Analysis of SNVs was performed by real-time PCR (qPCR), TaqMan® system, and analyzed by QuantStudio™6 Flex Real-Time PCR System (Applied Biosystems) platform to the following IL-6 probes: rs2069832, rs2069835, rs2069845, rs2069849, rs1524107, rs1800795; at the Laboratório de Análise Especializada em Biologia Molecular (LAEBM) of the Universidade Federal do Amazonas (UFAM). High IL-6 levels were observed among the patients. Furthermore, carriers of variant allele of each analyzed probe revealed slightly higher mean level of IL-6. The highest IL-6 serum levels were found in patients diagnosed with Angina Pectoris (25.65±3.2 pg/mL), followed by Aortic Aneurysm (22.48±3.86 pg/mL; p=0.034) and Acute Infarction of the Myocardium (23.03±2.51 pg/mL; p=0.017). The AB blood group presented higher levels of IL-6 (p=0.027) in comparison with other groups. Patients that presented the variant allele “G”(rs2069832) had a higher prevalence ratio for blood transfusion; red blood cell transfusion (RR=4.41; 95% CI 1.65‒11.75; p=0.002); platelet transfusion (RR=4.29; 95% CI 1.74‒10.22; p<0.001); fresh plasma transfusion (RR=4.05; 95% CI 1.67‒9.18; p<0.001) and cryoprecipitate transfusion (RR=4.23; 95% CI 1.69‒10.57; p<0.001). In the last 5 years, new technologies and GWAS studies have identified several changes related to cardiovascular diseases, with possible involvement of the ABO locus to acute myocardial infarction and possible cardiovascular biomarkers. The use of blood transfusions is a quality indicator in cardiac surgery, although no analyzed variant was associated with hospitalization and/or surgery success. The IL-6 levels were elevated in all studied patients, although slightly higher in those carriers of the mutant genotypes of each analyzed variant. High levels of IL-6 are reported in patients undergoing cardiac surgery and are recognized as an early biomarker of systemic inflammatory response after surgery. We found that IL-6 levels were elevated in all patients in the study, although higher in carriers of the variant genotype, although, no significant association between genotypes and IL-6 levels was found. The “AB” blood group presented the highest levels of IL-6. The presence of the variant allele “G” (rs2069832) was associated with an increased risk to blood transfusion.

Effects of Sarcopenia, Myosteatosis, and the Prognostic Nutritional Index on Survival in Stage 2 and 3 Gastric Cancer Patients

Background We aimed to evaluate the relationship between sarcopenia, myosteatosis, and systemic inflammatory response biomarkers and their prognostic role in stage 2 and 3 gastric cancer patients. Methods This study included 84 patients with stage 2 or 3 gastric cancer who underwent a gastrectomy. Computed tomography scans were used to determine the skeletal muscle index (SMI) at the third lumbar vertebra level for sarcopenia and myosteatosis. Results Based on the Asian Working Group of Sarcopenia (AWGS2019) criteria, the sarcopenia incidence was 36.9% and that of myosteatosis 46.4%. Univariate analysis showed that sarcopenia (48 vs. 14 mo, p < 0.001), myosteatosis (45 vs. 16 mo, p = 0.016), a low prognostic nutritional index (60 vs. 15 mo, p = 0.003), stage 3 (104 vs. 21 mo, p = 0.013), and old age (45 vs. 16 mo, p = 0.015) were poor prognostic markers. Multivariate analysis revealed that sarcopenia (AWGS2019), age, and stage significantly affected overall survival (hazard ratio: 3.31, 95% CI: 1.85–5.1; 1.96, 95% CI: 1.06–6.63; 2.5, 95% CI: 1.2–5.1, respectively). Conclusion We showed that sarcopenia directly affects overall gastric cancer survival.

Selection and evaluation of preoperative systemic inflammatory response biomarkers model prior to cytoreductive nephrectomy using a machine-learning approach

IntroductionThis study aimed to determine the prognostic value of a panel of SIR-biomarkers, relative to standard clinicopathological variables, to improve mRCC patient selection for cytoreductive nephrectomy (CN).Material and methodsA panel of preoperative SIR-biomarkers, including the albumin–globulin ratio (AGR), De Ritis ratio (DRR), and systemic immune-inflammation index (SII), was assessed in 613 patients treated with CN for mRCC. Patients were randomly divided into training and testing cohorts (65/35%). A machine learning-based variable selection approach (LASSO regression) was used for the fitting of the most informative, yet parsimonious multivariable models with respect to prognosis of cancer-specific survival (CSS). The discriminatory ability of the model was quantified using the C-index. After validation and calibration of the model, a nomogram was created, and decision curve analysis (DCA) was used to evaluate the clinical net benefit.ResultsSIR-biomarkers were selected by the machine-learning process to be of high discriminatory power during the fitting of the model. Low AGR remained significantly associated with CSS in both training (HR 1.40, 95% CI 1.07–1.82, p = 0.01) and testing (HR 1.78, 95% CI 1.26–2.51, p = 0.01) cohorts. High levels of SII (HR 1.51, 95% CI 1.10–2.08, p = 0.01) and DRR (HR 1.41, 95% CI 1.01–1.96, p = 0.04) were associated with CSS only in the testing cohort. The exclusion of the SIR-biomarkers for the prognosis of CSS did not result in a significant decrease in C-index (− 0.9%) for the training cohort, while the exclusion of SIR-biomarkers led to a reduction in C-index in the testing cohort (− 5.8%). However, SIR-biomarkers only marginally increased the discriminatory ability of the respective model in comparison to the standard model.ConclusionDespite the high discriminatory ability during the fitting of the model with machine-learning approach, the panel of readily available blood-based SIR-biomarkers failed to add a clinical benefit beyond the standard model.

The utility of pretreatment systemic inflammatory response biomarkers on overall survival of cervical cancer patients stratified by clinical staging

ObjectiveInflammation plays a crucial role in the initiation and progression of many cancers. This study aimed to investigate the utility of pretreatmentneutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), derived neutrophil–lymphocyte ratio (dNLR), and a combination of PLR and NLR in predicting the risk of death according to clinical staging in cervical cancer (CC) patients. MethodsA cohort study of women with CC, diagnosed and treated at a single cancer referral center in Brazil, from 2006 to 2009. A multivariate Cox regression analysis and ROC curve analysis accessed the predictive value of inflammatory response biomarkers in overall survival (OS). The median values of the biomarkers were used as cut-off points. ResultsA total of 1,266 patients were included in the study, 76.0% with locally advanced disease. After adjusting for clinical variables, NLR > 2.57, PLR ≥ 146.70, dNLR ≥ 1.778 and PLR + NLR in combination had equivalent performance in predicting worse OS, but only among patients with locally advanced disease (adjusted Hazard Ratio [aHR] = 1.453, 95% Confidence Interval [CI] = 1.227–1.722; p < 0.001; aHR = 1.429; 95% CI = 1.209–1.688; p < 0.001; aHR = 1.486, 95% CI = 1.257–1.756, p < 0.001, aHR = 1.731; 95% CI = 1.411–2.123; p < 0.001, respectively). ConclusionIn conclusion, PLR, NLR, dNLR and PLR + NLR in combination presented equivalent performance in predicting OS in locally advanced CC patients. They are simple and readily available from routine blood tests, not entailing additional costs. PLR, NLR, dNLR and PLR + NLR in combination are strong prognostic biomarkers candidates in locally advanced CC and should be further explored in prospective trials.

P0641 - Evaluation of a panel of preoperative blood-based systemic inflammatory response biomarkers for outcome prediction in patients treated with cytoreductive nephrectomy for metastatic renal cell carcinoma

P0641 - Evaluation of a panel of preoperative blood-based systemic inflammatory response biomarkers for outcome prediction in patients treated with cytoreductive nephrectomy for metastatic renal cell carcinoma

P47 Evaluating the Relationship of Pre-Assessment Host Systemic Inflammatory Response Biomarkers (Neutrophil Lymphocyte Ratio) to Post-Operative Infective Complication Risk in Colorectal Cancer Resection

IntroductionThe host systemic inflammatory response (SIR) is prognostic in a wide variety of solid tumours, with a greater degree of inflammation being associated with a worse clinical outcome. Neutrophil Lymphocyte Ratio (NLR) is an established way to measure SIR in vivo. We aimed to establish whether preoperative NLR correlates with infective complications in patients undergoing colorectal cancer (CRC) resection.MethodsData was extracted retrospectively for all CRC resections over a 2 year period (2016-2018) at a single district general hospital. NLR was measured for each patient from bloods at the time of pre-operative assessment. Post-operative complications were recorded using the Clavien-Dindo classification and subsequently classified as infective and non-infective. A Two-tailed Mann-Whitney U test was used to evaluate the data from an online resource.ResultsOf the 131 patients, 49 had complications of which 20 were infective. Of total complications 58% were male and 35% were aged 75 years or older. Current or ex-smokers constituted 43% and 41 of the total patients had a BMI >30 kg/m2. Pre-assessment mean NLR was 2.3 in those without complications and 4.7 in those with any complication. A mean NLR of 5.4 was present in those with infective complications, p-value 0.026.ConclusionThis study found that a raised NLR was present preoperatively in those who developed infective complications following CRC resection. This is a simple, readily available and cost-effective method of identifying patients at risk of complication. This ultimately may be useful in highlighting patients who would benefit from enhanced pre-operative optimisation. Further research to validate these findings in larger studies would seem warranted.

A panel of systemic inflammatory response biomarkers for outcome prediction in patients treated with radical cystectomy for urothelial carcinoma

ObjectivesTo determine the predictive and prognostic value of a panel of systemic inflammatory response (SIR) biomarkers relative to established clinicopathological variables in order to improve patient selection and facilitate more efficient delivery of peri‐operative systemic therapy.Materials and MethodsThe preoperative serum levels of a panel of SIR biomarkers, including albumin–globulin ratio, neutrophil–lymphocyte ratio, De Ritis ratio, monocyte–lymphocyte ratio and modified Glasgow prognostic score were assessed in 4199 patients treated with radical cystectomy for clinically non‐metastatic urothelial carcinoma of the bladder. Patients were randomly divided into a training and a testing cohort. A machine‐learning‐based variable selection approach (least absolute shrinkage and selection operator regression) was used for the fitting of several multivariable predictive and prognostic models. The outcomes of interest included prediction of upstaging to carcinoma invading bladder muscle (MIBC), lymph node involvement, pT3/4 disease, cancer‐specific survival (CSS) and recurrence‐free survival (RFS). The discriminatory ability of each model was either quantified by area under the receiver‐operating curves or by the C‐index. After validation and calibration of each model, a nomogram was created and decision‐curve analysis was used to evaluate the clinical net benefit.ResultsFor all outcome variables, at least one SIR biomarker was selected by the machine‐learning process to be of high discriminative power during the fitting of the models. In the testing cohort, model performance evaluation for preoperative prediction of lymph node metastasis, ≥pT3 disease and upstaging to MIBC showed a 200‐fold bootstrap‐corrected area under the curve of 67.3%, 73% and 65.8%, respectively. For postoperative prognosis of CSS and RFS, a 200‐fold bootstrap corrected C‐index of 73.3% and 72.2%, respectively, was found. However, even the most predictive combinations of SIR biomarkers only marginally increased the discriminative ability of the respective model in comparison to established clinicopathological variables.ConclusionWhile our machine‐learning approach for fitting of the models with the highest discriminative ability incorporated several previously validated SIR biomarkers, these failed to improve the discriminative ability of the models to a clinically meaningful degree. While the prognostic and predictive value of such cheap and readily available biomarkers warrants further evaluation in the age of immunotherapy, additional novel biomarkers are still needed to improve risk stratification.

Neutrophil-to-Lymphocyte Ratio Is Independently Associated With Severe Psychopathology in Schizophrenia and Is Changed by Antipsychotic Administration: A Large-Scale Cross-Sectional Retrospective Study.

Background: Immunological and inflammatory mechanisms play an important role in schizophrenia. The neutrophil-to-lymphocyte ratio (NLR) is a value obtained by dividing the absolute number of neutrophils by the absolute lymphocyte count and represents a biomarker of systemic inflammatory response. There are studies investigating NLR association with psychopathology. However, the relationship has been only studied in small numbers of patients with schizophrenia, which leads to conflicting results and makes the meta-analytic data difficult to interpret. The aim of this study is to perform large-scale cross-sectional analysis on the potential correlation between NLR and disease severity in schizophrenic patients with or without medication.Methods: This cross-sectional retrospective study was conducted in Nanjing Medical University Affiliated Brain Hospital. We identified inpatients with schizophrenia between July 12, 2018 and March 27, 2019 and collected data of NLR, the Clinical Global Impression Severity scale (CGI-S) score and the Brief Psychiatric Rating Scale (BPRS) score.Results: The records of 1,144 identified patients (10.8% drug-free patients) were analyzed. We found that NLR was significantly decreased in schizophrenic patients after antipsychotic administration and there was the discrepant correlation between NLR and psychiatric symptoms in patients with or without antipsychotic medication. The results of multivariate logistic regressions showed that NLR was positively associated with the severity of disease (i.e., the CGI-S score and the BPRS total score) in drug-free patients, and it was negatively associated with the BPRS negative symptoms (i.e., the BPRS negative symptoms score) in drug-therapy patients.Conclusion: The study is the first to confirm the hypothesis that NLR is independently associated with severe psychopathology in schizophrenia and is changed by antipsychotic administration.

Metabolic parameters with different thresholds for evaluating tumor recurrence and their correlations with hematological parameters in locally advanced squamous cell cervical carcinoma: an observational 18F-FDG PET/CT study.

Positron emission tomography (PET) parameters for a combination of the primary tumor and suspicious metastatic lymph nodes (SMLNs) appear to be more potential than those for the primary tumor alone for evaluating tumor recurrence in locally advanced cervical carcinoma (LACC), while the optimal threshold has not been determined. This study investigated the optimal PET parameters and percentage of SUVmax (%SUVmax) thresholds for tumor recurrence evaluation, and the relationship with hematological parameters in patients with LACC treated with concurrent chemoradiotherapy (CCRT). Eighty-nine patients with advanced squamous cell cervical carcinoma (SCCC) scheduled for CCRT underwent pretreatment whole body PET/CT scans. We analyzed PET parameters including maximum standardized uptake value (SUVmax), metabolic tumor volume (MTV), and total lesion glycolysis (TLG) of the primary tumor (SUVmax-P, MTV-P, TLG-P) and the combination of the primary tumor and SMLNs (SUVmax-C, MTV-C, TLG-C). The association between PET parameters with different %SUVmax threshold and recurrence-free survival (RFS), and the correlations between PET parameters and hematological parameters including squamous cell carcinoma antigen (SCC-ag), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR) and hemoglobin (Hb) were evaluated. The optimal threshold for evaluating tumor recurrence was 50%SUVmax, and the optimal PET parameter was MTV-C with the 50%SUVmax threshold (MTV-C50%) (c-index =0.752). Multivariate analysis indicated that MTV-C50% [hazard ratio (HR), 1.065; P<0.001], NLR (HR, 1.195; P=0.045) and SMLNs (HR, 2.225; P=0.003) were independent risk factors for RFS. MTV and TLG with most of %SUVmax thresholds had slight-to-moderate correlations with SCC-ag, NLR and PLR. For SCC-ag, MTV-C55% (r=0.500; P<0.001) had the highest correlation coefficient among all parameters. For NLR and PLR, MTV-C50% (r=0.637 and r=0.515, respectively; P<0.001 for both correlations) received the highest correlation coefficient. The MTV-C estimated by using a 50%SUVmax threshold, which is related to systemic inflammatory response biomarker (NLR and PLR), can be used as an optimal PET parameter associated with tumor recurrence of LACC.

Roles of the systemic inflammatory response biomarkers in the diagnosis of cancer patients with solid tumors

Aim: Cancer is still considered as one of the leading causes of mortality worldwide. Various tumor factors have been used for the diagnosis and follow-up of solid tumors; however, their clinical features remains controversial in terms of their diagnostic, prognostic, and predictive values. In this study, we aimed to investigate the use of the systemic inflammatory response biomarkers, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and lymphocyte-to-monocyte ratio (LMR), in the diagnosis of solid tumors. Method: We retrospectively analyzed the records of 256 patients with solid tumors, including lung, breast, liver, and pancreatic cancers, who were diagnosed at the outpatient clinics of our institution between January 2017 and July 2018. The neutrophil, lymphocyte, monocyte, and platelet counts were measured using a hematology analyzer and the results were analyzed statistically. Results: The results of the receiver operating characteristic analysis showed that the NLR and LMR could be statistically reliable biomarkers, with area under the curve (AUC) values of 0.574 (p = 0.017) and 0.596 (p = 0.002). However, the PLR statistically failed to discriminate the patients and the control subjects, with AUC values of 0.545 (p = 0.148). Conclusions: Certain systemic inflammatory response biomarkers, such as the NLR and LMR, can play roles in the clinical diagnosis of patients with solid tumors.

Pretreatment neutrophil-lymphocyte and platelet-lymphocyte ratio predict clinical outcome and prognosis for cervical Cancer

Variations in systemic inflammatory response biomarker levels have been associated with adverse clinical outcome in various malignancies. In this study, we aimed to evaluate the predictive and prognostic role of the pretreatment neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in cervical cancer. We retrospectively investigated 616 patients who underwent initial radical hysterectomy with pelvic lymphadenectomy for cervical cancer between July 2012 and December 2014 in China. Their clinical and histopathological markers and complete blood counts were obtained and analyzed. Then we chose the group of 339 of the total 616 patients who were not combined preoperative radiotherapy or chemotherapy for the survival analysis. Prognostic factors were assessed by univariate and multivariate analyses. The ROC curve revealed NLR and PLR had significant ability to predict parametrial involvement, and the cutoff values for NLR and PLR were 2.5 and 138.8 respectively. Clinicopathologic analysis showed that NLR was linked to age, parametrial involvement, tumor-invasion depth and histologic grade, and PLR was related to age, parametrial involvement, tumor-invasion depth and FIGO stage. Univariate analysis identified high PLR as a significant poor predictor for progression-free survival (PFS) and overall survival (OS), and NLR exhibited no predict power on OS or PFS. Multivariable analysis showed that PLR was an independent predictor of PFS, but not OS. NLR and PLR were associated with the clinical characteristics of cervical cancer. Additionally, PLR had independence prognostic value for PFS in patients with cervical cancer receiving radical hysterectomy with pelvic lymphadenectomy.

Neutrophil/lymphocyte ratio is a more sensitive systemic inflammatory response biomarker than platelet/lymphocyte ratio in the prognosis evaluation of unresectable pancreatic cancer.

Multiple cancers arise from sites of infection, chronic irritation, and inflammation. It has been widely accepted that pancreatic cancer is an inflammation-driven cancer. In this study, we investigated the application value of systemic inflammatory markers, neutrophil to lymphocyte ratio (NLR) and platelet to lymphocyte ratio (PLR), in the prediction of chemotherapy response and prognosis in patients with late pancreatic cancer. 122 patients with inoperable pancreatic cancers were included and separated into two groups according to median values of NLR or PLR (NLR low:<3.81 or NLR high:≥3.81, and PLR low:<142.14 or PLR high≥142.14, respectively). Baseline NLR and PLR levels were significantly higher in pancreatic cancer patients compared with the healthy subjects. Neither of the baseline NLR or PLR levels could predict outcomes. Patients with low baseline level of NLR, but not PLR, had better responses to chemotherapy. Changes in NLR, but not PLR levels, were associated with the therapeutic efficacy. Patients who stayed in or dropped into the low NLR level subgroup after first-line chemotherapy had better responses, comparing to those stayed in or jumped into the high NLR level group. No similar results could be observed when the PLR level was investigated. Therefore, NLR is a more sensitive biomarker than PLR in the prediction of chemotherapy response of patients.

Evaluation of Complete Blood Count Indices (NLR, PLR, MPV/PLT, and PLCRi) in Healthy Dogs, Dogs With Periodontitis, and Dogs With Oropharyngeal Tumors as Potential Biomarkers of Systemic Inflammatory Response.

The aim of the study was to retrospectively assess complete blood count (CBC) indices of dogs with periodontitis (PD; n = 73) and dogs with oropharyngeal tumors (OT; n = 92) in comparison to CBC indices of healthy dogs (HD; n = 71). Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio, mean platelet volume to platelet ratio, and platelet large cell ratio index (PLCRi) were evaluated as biomarkers of systemic inflammatory response provoked by PD and OT. Results of multivariable polytomous logistic regression analysis indicated no significant associations between CBC indices and PD. Both NLR and PLCRi were significantly higher in dogs with OT when compared to HD and dogs with PD and could, therefore, indicate a tumor-associated systemic inflammatory response. Additional studies of CBC indices, along with other biomarkers of systemic inflammatory response, are recommended to validate them as reliable indicators of clinical disease activity.

Procalcitonin as a Diagnostic and Prognostic Marker of Sepsis in Critically Ill Patients in Intensive Care Unit

Background: Sepsis is a leading cause of mortality in critically ill patients. However, differentiating sepsis from non-infectious triggers of the systemic inflammatory response syndrome (SIRS) is difficult. Procalcitonin is useful biomarker of systemic inflammatory response to infection. Its level rises in response to a proinflammatory stimulus, especially of bacterial origin and not rise significantly with viral or non infectious inflammation. Objectives: The aim of this study was to determine the relation of procalcitonin (PCT) level with the development of organ failure and mortality in critically ill septic ICU patients Patients and Methods: The current study was conducted on 60critically ill adult septic patients aged between 18-60 years old of both sex with anticipated stay of >48 hours. All patients were assessed clinically with haemodynamic and full laboratory monitoring, CRP, a PCT level and SOFA score were calculated in the1st and the 4th day of admission.Results: There was significant increase in PCT level between three groups and no significant difference between groups as regard CRP. According to SOFA score there was significant difference between three groups. There was a positive correlation between PCT level and SOFA Score (r = 0.924, P = 0.001) while there was no correlation between CRP and SOFA score (r = -0.233, P = 0.091). Conclusion: PCT is a good diagnostic and prognostic marker of sepsis. PCT shows a closer correlation than that of CRP with the severity of infection and organ dysfunction.