Monocyte Ratio Research Articles

Novel predictor of thrombosis after left atrial appendage closure -Neutrophil to Lymphocyte Ratio (NLR), platelet to LymPhocyte Ratio (PLR), and Lymphocyte to Monocyte Ratio (LMR)-

Abstract Background Cardiogenic embolism by left atrial thrombi is one of the most important atrial fibrillation (AF)-related clinical problems. In a previous survey, 91% of nonrheumatic AF-related left atrial thrombi was originated in the left atrial appendage (LAA). The WATCHMAN device was developed as a permanent implantable device to seal off the LAA to prevent cardiogenic embolism. It has been used in Japan since September 2019. The WATCHMAN family is the only left atrial appendage closure (LAAC) device in Japan. After percutaneous left atrial appendage closure (LAAC), DRT is an important issue in some cases. Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), and lymphocyte to monocyte ratio (LMR) are known as cancer prognostic factors and indicators of immune status. There are few reports on the predictor for device related thrombosis (DRT), transient ischemic attack (TIA), and ischemic stroke. Finding novel biomarkers could help clinical decision in antithrombotic therapy post LAAC and follow-up intervals. Purpose To investigate the association of NLR, PLR, and LMR with device related thrombosis, transient ischemic attack, and ischemic stroke in patients with LAAC. Methods Our database of LAAC was respectively analyzed. All LAAC cases were performed between January 2020 and September 2023. Blood cell counts were sampled in three days before LAAC. Postoperative antithrombotic therapy was individualized based on the patient’s background. We examined their background and clinical events. Results A total of 116 consecutive patients underwent LAAC in our institution excepting for one case that could not be performed due to a huge LAA (follow-up period, 610±37 days; age, 75±1 years; male sex, 73%; left ventricular ejection fraction, 58±1%; CHAD2S2-VASc, 4.6±0.1; HAS-BLED, 3.4±0.1). The results are shown in the Figure. Receiver-operating characteristic curve analysis confirmed the best cut-off value of NLR, PLR, and LMR for composite of DRT, TIA, and ischemic stroke (AUC = 0.69; 0.70; 0.67). In the univariate analysis, NLR<1.88, PLR<144, and LMR>3.40 are the independent predictor for the combination of DRT, TIA, and ischemic stroke (p-value = 0.02; 0.04; 0.05, respectively). Conclusion Low NLR, low PLR, and high LMR are the independent predictor for the combination of DRT, TIA, and ischemic stroke. These parameters can be useful in routine use because they can be easily calculated without additional costs.

The Prognostic Value of a Naples Score in Determining in-Hospital Mortality in Patients with Acute Ischemic Stroke Undergoing Endovascular Treatment

Background/Objectives: The Naples prognostic score (NPS), reflecting inflammation and nutritional status, has prognostic value, especially in cancer. This study evaluated its ability to predict in-hospital mortality in acute ischemic stroke (AIS) patients undergoing endovascular treatment (EVT). Methods: We retrospectively studied 244 patients with AIS who were admitted between April 2020 and December 2023. Patients were included if they presented within 6 h of symptom onset with evidence of intracranial proximal arterial occlusion. The EVT was performed using aspiration catheters, stent retrievers, or both. The NPS was calculated based on the neutrophil–lymphocyte ratio, lymphocyte–monocyte ratio, and albumin and total cholesterol levels. Results: We found a significant association between higher NPS scores and in-hospital mortality. Patients with a high NPS (3 or 4) had a mortality rate of 41.6% compared to 21.0% in the low-NPS group (0, 1, or 2). The full model incorporating NPS showed superior predictive ability for in-hospital mortality compared with the baseline model (areas under the curve 0.881 vs. 0.808). A receiver-operating characteristic analysis at a cutoff of >2.5 for the NPS showed a sensitivity of 86.6% and specificity of 41.9%. This study demonstrated that incorporating the NPS into the predictive model improved the accuracy and calibration for predicting in-hospital mortality. A decision curve analysis showed the net benefit of using the full model incorporating NPS over the baseline model, emphasizing its potential clinical application in prognostication. Conclusions: NPS is a reliable predictor of in-hospital mortality in AIS patients undergoing EVT. Incorporating NPS into clinical practice could help to identify high-risk patients and improve outcomes through tailored interventions.

Precision phenotyping from routine laboratory parameters for out of hospital survival prediction in an all comers prospective PCI registry

Out-of-hospital mortality in coronary artery disease (CAD) is particularly high and established adverse event prediction tools are yet to be available. Our study aimed to investigate whether precision phenotyping can be performed using routine laboratory parameters for the prediction of out-of-hospital survival in a CAD population treated by percutaneous coronary intervention (PCI). All patients treated by PCI and discharged alive in a tertiary center between January 2016 – December 2022 that have been included prospectively in the local registry were analyzed. 115 parameters from the PCI registry and 266 parameters derived from routine laboratory testing were used. An extreme gradient-boosted decision tree machine learning (ML) algorithm was trained and used to predict all-cause and cardiovascular-cause survival. A total of 4027 patients with 4981 PCI hospitalizations were randomly included in the 70% training dataset and 1729 patients with 2160 PCI hospitalizations were randomly included in the 30% validation dataset. All-cause and cardiovascular cause mortality was 17.5% and 12.2%. The integrated area under the receiver operator characteristic curve for prediction of all-cause and cardiovascular cause mortality by the ML on the validation dataset was 0.844 and 0.837, respectively (all p < 0.001). Parameters reflecting renal function (first and maximum serum creatinine), hematologic function (mean corpuscular hemoglobin concentration, platelet distribution width), and inflammatory status (lymphocyte per monocyte ratio) were among the most important predictors. Accurate out-of-hospital survival prediction in CAD can be achieved using routine laboratory parameters. ML outperformed clinical risk scores in predicting out-of-hospital mortality in a prospective all-comers PCI population and has the potential to precisely phenotype patients.

Complete Blood Count in Children With COVID-19: A Predictor of Disease Severity.

Blood count abnormalities are frequent in patients with severe COVID-19 disease and there is still a lack of information in pediatric complete blood count (CBC) results. Thus, this study aims to correlate the CBC in the emergency room of children with COVID-19 between 0 and 10 years old and the clinical severity of the disease. A retrospective cohort study was performed in children with COVID-19 who collected at the emergency room CBC, C-reactive protein (CRP), platelet to lymphocyte ratio (PLR), neutrophil to lymphocyte ratio (NLR), neutrophil to monocyte ratio (NMR), lymphocyte to neutrophil ratio (LNR), lymphocyte to monocyte ratio (LMR), monocyte to neutrophil ratio (MNR) and monocyte to lymphocyte ratio (MLR). In total, demographic data from 93 children with median age of 19 months (0.3-126), 60.2% males, were included. The main changes in the CBC were atypical lymphocytes (51.6%) and eosinopenia (49.5%). From 69 hospitalized children, 21 were considered severe. There was no association between age, gender, and CRP value with clinical severity. The presence of underlying disease was five times higher (odds ratio [OR] = 5.08) in patients who required hospitalization and a higher NLR value was 54% (OR = 1.54) more likely to occur. Eosinopenia was three times more frequent in inpatients with disease severity criteria (OR = 3.05). In conclusion, children younger than 10 years of age with COVID-19 have changes in the CBC collected in the emergency room, mainly atypical lymphocytes and eosinopenia. The presence of a comorbidity or a higher NLR increases the chance of hospitalization. In addition, eosinopenia was a predictor of severity in inpatient children due to COVID-19.

Predicting the Recurrence of Ovarian Cancer Based on Machine Learning.

Recurrence is the main factor for poor prognosis in ovarian cancer, but few prognostic biomarkers were reported. In this study, we used machine learning methods based on multiple biomarkers to develop a specific prediction model for the recurrence of ovarian cancer. A total of 277 ovarian cancer patients were enrolled in this study and randomly classified into training and testing cohorts. The prediction information was obtained through 47 clinical parameters using six supervised clustering machine learning algorithms, including K-Nearest Neighbor (K-NN), Decision Tree (DT), Random Forest (RF), Adaptive Boosting (AdaBoost), Gradient Boosting Machine (GBM), and Extreme Gradient Boosting (XGBoost). In predicting the recurrence of ovarian cancer, machine learning algorithm was superior to conventional logistic regression analysis. In this study, XGBoost showed the best performance in predicting the recurrence of ovarian cancer, with an accuracy of 0.95. In addition, neoadjuvant chemotherapy, Monocyte ratio (MONO%), Hematocrit (HCT), Prealbumin (PAB), Aspartate aminotransferase (AST), and carbohydrate antigen 125 (CA125) are the most important biomarkers to predict the recurrence of ovarian cancer. The machine learning techniques can achieve a more accurate assessment of the recurrence of ovarian cancer, which can help clinicians make decisions, and develop personalized treatment strategies.

Navigating the gray zone: Machine learning can differentiate malignancy in PI-RADS 3 lesions

IntroductionThe objective of this study is to predict the probability of prostate cancer in PI-RADS 3 lesions using machine learning methods that incorporate clinical and mpMRI parameters. MethodsThe study included patients who had PI-RADS 3 lesions detected on mpMRI and underwent fusion biopsy between January 2020 and January 2024. Radiological parameters (Apparent diffusion coefficient (ADC), tumour ADC/contralateral ADC ratio, Ktrans value, periprostatic adipose tissue thickness, lesion size, prostate volume) and clinical parameters (age, body mass index, total prostate specific antigen, free PSA, PSA density, systemic inflammatory index, neutrophil-lymphocyte ratio [NLR], platelet lymphocyte ratio, lymphocyte monocyte ratio) were documented. The probability of prostate cancer prediction in PI-RADS 3 lesions was calculated using 6 different machine-learning models, with the input parameters being the aforementioned variables. ResultsOf the 235 participants in the trial, 61 had malignant fusion biopsy pathology and 174 had benign pathology. Among 6 different machine learning algorithms, the random forest model had the highest accuracy (0.86±0.04; 95% CI 0.85–0.87), F1 score (0.91±0.03; 95% CI 0.91–0.92) and AUC value (0.92±0.06; 95% CI 0.88–0.90). In SHAP analysis based on random forest model, tumour ADC, tumour ADC/contralateral ADC ratio and PSA density were the 3 most successful parameters in predicting malignancy. On the other hand, systemic inflammatory index and neutrophil lymphocyte ratio showed higher accuracy in predicting malignancy than total PSA, age, free PSA/total PSA and lesion size in SHAP analysis. ConclusionAmong the machine learning models we developed, especially the random forest model can predict malignancy in PI-RADS 3 lesions and prevent unnecessary biopsy. This model can be used in clinical practice with multicentre studies including more patients.

Inflammation indices in association with periodontitis and cancer.

Inflammation is a complex physiological process that plays a pivotal role in many if not all pathological conditions, including infectious as well as inflammatory diseases, like periodontitis and autoimmune disorders. Inflammatory response to periodontal biofilms and tissue destruction in periodontitis is associated with the release of inflammatory mediators. Chronic inflammation can promote the development of cancer. Persistence of inflammatory mediators plays a crucial role in this process. Quantification and monitoring of the severity of inflammation in relation to cancer is essential. Periodontitis is mainly quantified based on the severity and extent of attachment loss and/or pocket probing depth, in addition with bleeding on probing. In recent years, studies started to investigate inflammation indices in association with periodontal diseases. To date, only few reviews have been published focusing on the relationship between blood cell count, inflammation indices, and periodontitis. This review presents a comprehensive overview of different systemic inflammation indices, their methods of measurement, and the clinical applications in relation to periodontitis and cancer. This review outlines the physiological basis of inflammation and the underlying cellular and molecular mechanisms of the parameters described. Key inflammation indices are commonly utilized in periodontology such as the neutrophil to lymphocyte ratio. Inflammation indices like the platelet to lymphocyte ratio, platelet distribution width, plateletcrit, red blood cell distribution width, lymphocyte to monocyte ratio, delta neutrophil index, and the systemic immune inflammation index are also used in hospital settings and will be discussed. The clinical roles and limitations, relationship to systemic diseases as well as their association to periodontitis and treatment response are described.

Metabolic Dysfunction-Associated Steatotic Liver Disease: The Associations between Inflammatory Markers, TLR4, and Cytokines IL-17A/F, and Their Connections to the Degree of Steatosis and the Risk of Fibrosis.

Background: The pathogenesis of MASLD (metabolic dysfunction-associated steatotic liver disease) is driven by environmental, genetic, metabolic, immune, and inflammatory factors. IL-17 and TLR4 determine hepatic steatosis, inflammation, and finally fibrosis. Objectives: To explore the associations between the plasma levels of inflammatory markers, TLR4, and the cytokines IL17A/F, as well as their connections with the degree of hepatic steatosis and the risk of hepatic fibrosis (defined by the FIB-4 score) in MASLD patients. Methods: The study cohort included 80 patients diagnosed with MASLD. The IL-17A/F and TLR4 serum concentrations were determined using the ELISA method. Results: We found a significant difference in the CAR levels (C-reactive protein to albumin ratio) when comparing MASLD patients with severe steatosis to those with mild/moderate steatosis (Student's t test, t (71) = 2.32, p = 0.023). The PIV (pan-immune inflammatory value) was positively correlated with the SII (systemic immune inflammation index), (r = 0.86, p < 0.0001) and the CAR (r = 0.41, p = 0.033) in MASLD patients with severe steatosis. In contrast, increased values of the LMR (lymphocyte to monocyte ratio) were significantly associated, with decreased levels of the SII (ρ = -0.38, p = 0.045). We also found a positive correlation between the CAR and the SII (r = 0.41, p = 0.028). In patients with mild/moderate steatosis, a significant positive correlation was observed between the SII and IL17A (r = 0.36, p = 0.010), the PIV and the CAR (r = 0.29, p = 0.011), the PIV and the SII (r = 0.87, p < 0.0001) and the PIV and IL17A (r = 0.3, p = 0.036). A negative correlation was observed between the LMR and the SII (r = -0.55, p < 0.0001) and the CAR and IL17F (r = -0.37, p = 0.011). Regarding the inflammatory markers, the PIV (336.4 vs. 228.63, p = 0.0107), and the SII (438.47 vs. 585.39, p = 0.0238) had significantly lower levels in patients with an intermediate-high risk of hepatic fibrosis as compared with the patients with a low risk of hepatic fibrosis. The PNI (prognostic nutritional index) (47.16 vs. 42.41, p = 0.0392) had significantly different levels in patients with the likelihood of hepatic fibrosis than those with a low risk of hepatic fibrosis. Conclusions: Regarding the inflammatory markers, the PIV and the SII hold promise as biomarkers for discriminating between MASLD patients with an intermediate-high risk and those with a low risk of hepatic fibrosis. Our findings underscore the role of IL-17A and its potential relationship with inflammatory markers in MASLD pathogenesis and the progression to hepatic fibrosis.

Role of lymphocyte-to-monocyte ratio as a predictive marker for diabetic coronary artery disease: A cross-sectional study.

The lymphocyte to monocyte ratio (LMR) is considered a marker of systemic inflammation in cardiovascular disease and acts as predictor of mortality in coronary artery disease. To investigate the predictive role of LMR in diabetic coronary artery disease patients. This cross-sectional study was conducted at tertiary care super-specialty hospital at New Delhi, India. A total of 200 angiography-proven coronary artery disease (CAD) patients were enrolled and grouped into two categories: Group I [CAD patients with type 2 diabetes mellitus (T2DM) and glycated hemoglobin (HbA1c) levels ≥ 6.5%], and Group II (CAD patients without T2DM and HbA1c levels < 6.5%). Serum lipoproteins, HbA1c, and complete blood count of enrolled patients were analyzed using fully automatic analyzers. The logistic regression analysis showed an odds ratio of 1.48 (95%CI: 1.28-1.72, P < 0.05) for diabetic coronary artery disease patients (Group I) in unadjusted model. After adjusting for age, gender, diet, smoking, and hypertension history, the odds ratio increased to 1.49 (95%CI: 1.29-1.74, P < 0.01) in close association with LMR. Further adjustment for high cholesterol and triglycerides yielded the same odds ratio of 1.49 (95%CI: 1.27-1.75, P < 0.01). Receiver operating characteristic curve analysis revealed 74% sensitivity, 64% specificity, and 0.74 area under the curve (95%CI: 0.67-0.80, P < 0.001), suggesting moderate predictive accuracy for diabetic CAD patients. LMR showed positive association with diabetic coronary artery disease, with moderate predictive accuracy. These findings have implications for improving CAD management in diabetics, necessitating further research and targeted interventions.

The Analysis of Neutrophil to Lymphocyte Ratio (NLR), Lymphocyte to Monocyte Ratio (LMR), and Platelet to Lymphocyte Ratio (PLR) in Patients with Adenoidectomy and Tonsillectomy.

Background/Objectives: Adenoidectomy and tonsillectomy are among the most commonly performed procedures in ENT practice. The neutrophil-to-lymphocyte ratio (NLR), lymphocyte-to-monocyte ratio (LMR), and platelet-to-lymphocyte ratio (PLR) are recognized inflammatory markers. This study aims to evaluate the changes in NLR, PLR, and LMR in patients undergoing adenoidectomy and tonsillectomy. Methods: The study group consisted of 980 patients who underwent adenoidectomy and/or tonsillectomy. Preoperative and postoperative inflammatory markers were measured in all patients. The NLR, LMR, and PLR values were then calculated and analyzed. Results: In patients undergoing adenoidectomy and/or tonsillectomy, the postoperative NLR was significantly lower than the preoperative NLR. Similarly, the postoperative LMR was significantly higher, and the postoperative PLR was significantly lower compared to their preoperative values. Conclusions: The significant changes in NLR, LMR, and PLR following adenoidectomy and/or tonsillectomy suggest a reduction in systemic inflammation post-surgery. These findings indicate that these procedures may contribute to the improvement of inflammatory status in patients, highlighting the potential role of these markers in monitoring surgical outcomes.

FP3.2 - Pre-Treatment Neutrophil–Lymphocyte/ Lymphocyte-Monocyte Ratios: Are They Useful Prognostic Biomarkers In Locally Advanced Rectal Cancers?

Abstract Aim Examining the relationship &amp; outcome between pre operative Neutrophil:Lymphocyte Ratio, Neutrophil:Monocyte Ratio &amp; Lymphocyte:Monocyte Ratio in a cohort of locally advanced complex pelvic tumours, involving the rectum, where the patients underwent resection with curative intent. Methods The retrospective data collected from 2013 to 2022. Cases where rectum resection was not involved were excluded. The Kaplan-Meier curve was employed to estimate the survival function, with overall survival defined as the duration from the date of the first surgery to the date of death from any cause. The final data input point was last attendance at the hospital or the date of death. Disease-free survival was calculated and disease recurrence was determined based on a combination of radiological, histopathological, and/or endoscopic results. Results The data encompassed 72 cases. The male-to-female ratio was 1:0.85. Kaplan-Meier curves were used to calculate over-all disease free survival. Our results from Neut:Lymph ratio did not show any significant correlation in overall survival and disease free survival. For Neut:Monocytes ratio, all cases in our cohort had high ratio but this comparison was not published elsewhere for our comparison. Finally, for Lymph:Monocytes, when compared to Gawiński’s data, our disease free survival was found to be significant at p&amp;lt;0.0425 suggesting that the likelihood of recurrence is high. Our overall survival did not have any significant findings. Conclusions In all cancer cases, the neutrophil-to-monocyte ratio consistently showed high averages, raising the question of whether this ratio could potentially serve as a more effective biomarker. The analysis remains a work in progress with further variables to compare.

The diagnostic value of neutrophil to lymphocyte ratio, albumin to fibrinogen ratio, and lymphocyte to monocyte ratio in Parkinson's disease: a retrospective study.

Parkinson's disease (PD) is a prevalent disorder of the central nervous system, marked by the degeneration of dopamine (DA) neurons in the ventral midbrain. In the pathogenesis of PD, inflammation hypothesis has been concerned. This study aims to investigate clinical indicators of peripheral inflammation in PD patients and to explore the diagnostic value of neutrophil-to-lymphocyte ratio (NLR), albumin-to-fibrinogen ratio (AFR), and lymphocyte-to-monocyte ratio (LMR) in assessing PD risk. This study included 186 patients with PD and 201 matched healthy controls (HC) with baseline data. Firstly, the differences of hematological indicators between PD group and healthy participants were compared and analyzed. Univariate and multivariate regression analyses were then conducted. Smooth curve fitting was applied to further validate the relationships between NLR, LMR, AFR, and PD. Subsequently, subgroup analysis was conducted in PD group according to different duration of disease and Hoehn and Yahr (H&Y) stage, comparing differences in clinical indicators. Finally, the receiver operating characteristic (ROC) curve was employed to assess the diagnostic value of NLR, LMR, and AFR in PD. Compared to the HC group, the PD group showed significantly higher levels of hypertension, diabetes, neutrophil count, monocyte count, CRP, homocysteine, fibrinogen, and NLR. Conversely, levels of LMR, AFR, lymphocyte count, HDL, LDL, TG, TC, uric acid, and albumin were significantly lower. The multivariate regression model indicated that NLR (OR = 1.79, 95% CI: 1.39-2.31, p < 0.001), LMR (OR = 0.75, 95% CI: 0.66-0.85, p < 0.001), and AFR (OR = 0.79, 95% CI: 0.73-0.85, p < 0.001) were significant factors associated with PD. Smooth curve fitting revealed that NLR was positively linked to PD risk, whereas AFR and LMR were inversely associated with it. In ROC curve analysis, the AUC of AFR was 0.7290, the sensitivity was 63.98%, and the specificity was 76.00%. The AUC of NLR was 0.6200, the sensitivity was 50.54%, and the specificity was 71.50%. The AUC of LMR was 0.6253, the sensitivity was 48.39%, and the specificity was 73.00%. The AUC of the combination was 0.7498, the sensitivity was 74.19%, and the specificity was 64.00%. Our findings indicate that NLR, LMR, and AFR are significantly associated with Parkinson's disease and may serve as diagnostic markers.

Association between Hematological Parameters and Severity of Covid-19 Infections.

This study aimed to determine the relationships between hematological parameters- hemoglobin, Total Leucocyte Counts (TLC), platelet counts, Absolute Neutrophil Counts (ANC), Absolute Lymphocyte Counts (ALC), Neutrophil Lymphocyte Ratio (NLR), Systemic Immune Inflammatory Index (SII), Neutrophil Monocyte Ratio (NMR), Platelet Lymphocyte Ratio (PLR) and the severity of COVID 19 infections and their use in predicting severity of COVID-19 infections. This was a prospective, observational, single-center study of 573 symptomatic adult inpatients of COVID 19 admitted to our tertiary care center. The above-mentioned hematological parameter levels were noted and compared between the two categories of COVID-19 infection, namely non-severe and severe COVID-19 using logistic regression methods. Their cut-off values were detected using the ROC curve. The median TLC, ANC, NLR, SII, NMR, PLR were notably higher in patients with severe COVID-19 than in those with non-severe COVID-19. Logistic regression analysis showed that NMR (OR=1.029, p=0.006) and ALC (OR=0.999, p=0.002) were statistically significant independent predictors of COVID-19 severity. The hematological parameters mentioned, can be used for predicting severe COVID-19 infections at admission. ALC and NMR levels could be used as hematological markers to predict severity of COVID-19 in adult patients with their cut off values being < 1105 cells/cubic millimeter and > 10.434 respectively.

Value analysis of preoperative peripheral blood LMR in predicting prognosis of serous papillary ovarian adenocarcinoma

ObjectiveTo analyze the predictive effect of preoperative peripheral blood leukocyte related inflammatory indicators on the prognosis of patients with serous papillary ovarian adenocarcinoma.MethodsA retrospective analysis was conducted on the case data of 83 patients with ovarian cancer undergoing tumor cell reduction surgery admitted to our hospital from January 2017 to December 2020. Pathological findings confirmed serous papillary ovarian adenocarcinoma. Kaplan–Meier method was used to analyze the relationship between lymphocyte to monocyte ratio (LMR) and the patients survival prognosis. Analyzing factors affecting patient prognosis which using a multivariable Cox risk.ResultsThe overall survival (OS) of the patients with serous papillary ovarian adenocarcinoma in high LMR group was higher than that in the low LMR group preoperative. The disease free survival (DFS) of ovarian adenocarcinoma patients in the high LMR group was higher than that in the low LMR group preoperative. That was the low LMR indicating a poor prognosis. Single factor analysis showed that age of onset was correlated with OS and DFS, and the body mass index (BMI) was only correlated with OS. Multivariable analysis showed that the age of onset (HR = 2.571, 95% CI 1.199–5.512, P = 0.015) and BMI (HR = 0.337, 95% CI 0.158–0.718, P = 0.005) were independent risk factors for OS.ConclusionsAlthough the serous papillary ovarian adenocarcinoma patients with preoperative peripheral blood LMR reduction have poor prognosis, the correlation between LMR values and prognosis is not significant. Therefore, it is not recommended to use preoperative peripheral leukocyte related inflammatory indicators as prognostic markers for serous papillary ovarian adenocarcinoma.

Complete Blood Count-Based Biomarkers as Predictors of Clinical Outcomes in Advanced Non-Small Cell Lung Cancer Patients with PD-L1 < 50% Treated with First-Line Chemoimmunotherapy.

Background: The aim of the study was to investigate a series of complete blood cell count-based biomarkers of systemic inflammation as predictors of clinical outcomes in patients who underwent first-line chemoimmunotherapy for advanced NSCLC. Methods: Consecutive patients with pathologically diagnosed stage III/IV NSCLC and PD-L1 < 50% who underwent first-line chemoimmunotherapy were retrospectively enrolled. The clinical outcomes used for biomarker evaluation were Objective Response Rate (ORR) and Overall Survival (OS). Results: Non-responders had significantly higher values of neutrophil to lymphocyte ratio (NLR, median: 5.36; IQR: 2.78-10.82 vs. 3.31; IQR: 2.15-4.12, p = 0.019), neutrophil to monocyte ratio (NMR, median: 14.00; IQR: 8.82-21.20 vs. 9.20; IQR: 7.45-11.20, p = 0.013), and systemic inflammation index (SII, median: 1395; IQR: 929-3334 vs. 945; IQR: 552-1373, p = 0.025), but only NLR and NMR remained independently associated with clinical response in multivariate logistic regression. In the univariate analysis, white blood cells (OR:1.2202; 95% CI: 1.0339-1.4400, p = 0.019), neutrophils (OR:1.2916; 95% CI: 1.0692-1.5604, p = 0.008), NLR (OR:1.3601: 95% CI: 1.0949-1.6896, p = 0.005) and NMR (OR:1.2159; 95% CI: 1.00396-1.4221, p = 0.015) were significantly associated with survival; Cox regression models confirmed that neutrophils, NLR, and MLR were independently associated with survival; NLR, at a cut-off value of 4.0, showed the better AUC (0.749) in predicting OS. Conclusions: Baseline complete blood cell count biomarkers, especially the NLR, can predict clinical outcomes in patients with advanced NSCLC treated with first-line chemoimmunotherapy.

Systemic inflammation and changes in physical well-being in patients with breast cancer: a longitudinal study in community oncology settings.

Chemotherapy adversely affects physical well-being and inflammation may be related to changes in physical well-being. We evaluated the association of systemic inflammation with changes in physical well-being. In a prospective study of 580 patients with stages I-III breast cancer we assessed immune cell counts, neutrophil:lymphocyte ratio (NLR), lymphocyte:monocyte ratio (LMR), and platelet:lymphocyte ratio (PLR) within 7 days before chemotherapy (pre-chemotherapy). Physical well-being was assessed using the Functional Assessment of Cancer Therapy: General-Physical Well-being subscale (FACT-PWB) pre-chemotherapy and 1 month and 6 months post-chemotherapy. Clinically meaningful decline in physical well-being was determined as decreasing FACT-PWB by more than one point from pre-chemotherapy level, and non-resilience defined as having decline post-chemotherapy and not returning to within one-point of pre-chemotherapy FACT-PWB by 6 months post-chemotherapy. Multivariable logistic regressions examined the association between inflammation and changes in physical well-being, adjusting for sociodemographic and clinical characteristics. Fifty-nine percent (310/529) and 36% (178/501) of participants had physical well-being decline post-chemotherapy and 6 months post-chemotherapy, respectively. Fifty percent (147/294) were non-resilient. Low NLR and PLR were associated with 1.78 (P = .01) and 1.66 (P = .02) fold greater odds of having a decline in physical well-being 6 months post-chemotherapy compared to those with high NLR and PLR, respectively. Low NLR and PLR were associated with 1.92 (P = .02) and 2.09 (P = 0.01) fold greater odds of being non-resilient 6 months post-chemotherapy compared to those with high NLR and PLR, respectively. Low NLR and PLR were associated with chemotherapy-induced changes in physical well-being independent of sociodemographic and clinical risk factors.

Prognostic Value of Dynamic Segmented Neutrophil to Monocyte (SeMo) Ratio Changes in Patients with Moderate to Severe Traumatic Brain Injury.

Traumatic brain injury (TBI) is a leading cause of morbidity and mortality in trauma patients, necessitating reliable prognostic tools. The segmented neutrophil-to-monocyte (SeMo) ratio, indicative of the inflammatory response, has emerged as a valuable biomarker. This study evaluates the prognostic value of dynamic changes in the SeMo ratio in predicting outcomes for patients with moderate to severe TBI. A retrospective analysis was conducted on data from 1118 TBI patients admitted to the surgical intensive care unit at a level I trauma center between January 2009 and December 2020. Patients were selected based on an Abbreviated Injury Scale (AIS) score ≥ 3 in the head region. Initial and follow-up SeMo ratios were calculated upon admission and 48-72 h later, respectively. The dynamic SeMo ratio was defined as the difference between the second and initial SeMo ratios. Statistical analyses included receiver operating characteristic (ROC) curve analysis to determine the optimal threshold for mortality prediction, and comparative analysis of clinical outcomes. The study cohort included 121 deceased and 997 surviving patients. Deceased patients had significantly higher second SeMo ratios (20.9 ± 16.1 vs. 15.8 ± 17.2, p = 0.001) and dynamic SeMo ratios (2.4 ± 19.8 vs. -2.1 ± 19.5, p = 0.019) than those survival patients. In the multivariate analysis, the dynamic SeMo is a significant independent risk factor for in-hospital mortality (OR 1.01, 95%CI: 1.01-1.03, p = 0.031). The optimal cut-off for the dynamic SeMo ratio was 5.96, above which patients exhibited higher mortality (21.4% vs. 8.5%, p < 0.001), higher adjusted mortality (adjusted odds ratio: 2.98; 95% confidence interval: 1.95-4.56; p = 0.005), and longer hospital stays (23.6 days vs. 19.7 days, p = 0.005). Dynamic SeMo ratio changes serve as a prognostic marker for in-hospital mortality and hospital stay duration in moderate to severe TBI patients. A higher dynamic SeMo ratio indicates increased risk, highlighting the importance of early monitoring and intervention. Future prospective studies should validate these findings and explore integration with other biomarkers for enhanced prognostication.

Importance of biomarkers in streptococcal acute tonsillitis & peritonsillar abscess.

Background & objectives Acute tonsillitis is a disease that can often be cured with medical treatment. However, complications may occur during this disease process. One of these complications is peritonsillar abscess. In recent years, biomarkers have been frequently used in the diagnosis of diseases. The aim of the study was to reveal whether peritonsillar abscess develops after acute tonsillitis, and acute tonsillitis can be differentiated using biomarkers and which biomarker has higher predictive value for this differentiation. Methods The control group consisted of individuals who were operated for septoplasty in the otolaryngology clinic, and the acute tonsillitis group consisted of individuals diagnosed with acute tonsillitis in the same clinic. Both groups were statistically compared in terms of mean platelet volume (MPV), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic immune inflammation index (SII), infection discrimination index (IDI), plateletcrit (PCT) and lymphocyte to monocyte ratio (LMR) biomarkers. Statistically, significant biomarker values were compared between the subgroups in the tonsillitis group of those who had only acute tonsillitis and those who had peritonsillar abscess due to acute tonsillitis. Receiver operating characteristics (ROC) curve analysis was performed on biomarkers for their ability to predict the presence of peritonsillar abscess. Results When the individuals who had only acute tonsillitis and those who had acute tonsillitis with peritonsillar abscess were compared in terms of biomarkers, there was a statistically significant difference between the mean MPV, SII and PCT (P=0.010, 0.021, 0.023, respectively). ROC analysis was performed to calculate the sensitivity and specificity of MPV, PCT and SII for the diagnosis of acute tonsillitis with peritonsillar abscess (sensitivity-specificity for MPV 51.9-72.7%, for SII 94.2-32.7%, for PCT 71.2-50.9%, respectively). Interpretation & conclusions MPV, SII and PCT biomarkers may be useful to help clinicians predict peritonsillar abscess due to acute tonsillitis.

Ratio of immune indices in women of the semi-arid region

Environmental and climatic factors have a significant impact on the immune system, shaping its composition and functions. The semiarid region of Aleppo, characterized by hot, dry summers and moderate, wet and cold winters, is also characterized by environmental pollution such as air pollutants and industrial chemicals. The interaction of these environmental and climatic factors can impair immune function by causing inflammatory responses, compromising the integrity of immune cells, and impairing the body’s ability to mount an effective immune response. To date, the physiological characteristics of the parameters of the human blood system and the development of physiological reactions of adaptive immune homeostasis depending on the territory of residence have not been sufficiently studied. In this work, we studied the state of immune indices in women living in the semi-arid region. Thirty women aged from 20 to 60 years without chronic and acute diseases were examined. Immunocompetence was assessed using white blood cell count, lymphocyte subset analysis and calculation of immune indices including neutrophil to lymphocyte ratio (NLR), lymphocyte to monocyte ratio (LMR), systemic inflammatory response index (SIRI), immunoregulatory index (CD4+/ CD8+) and lymphoproliferation ratio and apoptosis (CD10+/CD95+ and CD71+/CD95+). The results of the analysis showed that the median NLR was 2.18 (1.50-2.90), LMR 6.66 (5.47-8.87), SIRI 0.64 (0.45-0.98), immunoregulatory index 0.99 (0.84-1.27) and the ratio of lymphoproliferation processes to apoptosis (CD10+/ CD95+ and CD71+/CD95+) 0.95 (0.65-1.29) and 0.94 (0.78-1.11), respectively, which indicates a stressful state of immune homeostasis and signs of premature aging of the immune system. Neutrophil-lymphocyte ratio (NLR), lymphocyte-monocyte ratio (LMR), systemic inflammatory response index (SIRI), immunoregulatory index (CD4+/CD8+) and lymphoproliferation-apoptosis ratio were determined. (CD10+/ CD95+ and CD71+/ CD95+) in the examined women of the semiarid climate zone of residence, emphasizes the stressful level of immune homeostasis. The results obtained highlight the need for systematic individual biomedical monitoring to maintain immune homeostasis in populations inhabiting similar environmental conditions.

ROLE OF HAEMATOLOGY BIOMARKERS IN URINARY BLADDER AND RENAL CELL CANCER PATIENTS TREATED WITH IMMUNE-ONCOLOGICAL DRUGS

Background: Urinary bladder (UB) and Renal Cell Cancer (RCC) are common in men than women with poor outcome. The novel immunotherapy drugs like Immune Check Point Inhibitors (ICIs) are effective but expensive. However, a cost-effective and reliable biomarker to predict response and clinical outcomes is lacking. Objective: To study the association of pre-treatment haematological parameters with clinical outcome in urinary bladder and renal cell cancer patients treated with ICIs. Method: In a retrospective study, we included 52 patients with urinary bladder and RCC treated with ICIs from Jan 2008 to Dec 2019. Clinical evaluation and laboratory investigations were performed as a part of standard protocol. CBC parameters such as WBC, TLC, DLC, Hb, Platelet, Neutrophil:Lymplocyte Ratio(NLR), Platelet:Lymphocyte Ratio (PLR), Lymphocyte:Monocyte Ratio(LMR) were studied at the time of TMC enrolment(first) and before the start (pre-treatment) of the ICIs therapy(io). Results: Amongst the CBC parameters, WBC count, when categorized based on cut off from ROC at the time of TMC enrolment(first) and the pre-treatment of the ICIs therapy(io) were found to be significantly associated with progression of disease with p- value 0.012 with Hazard Ratio (HR) - 2.52 (95% C.I. - 1.2-5.31) &amp; p- value 0.060 with Hazard Ratio (HR) – 1.99 (95% C.I. – 0.96-4.12) respectively. The ROC - based cut off for WBC at the time of TMC enrolment(first) and the pre-treatment of the ICIs therapy(io) were found to be 7.16 X10e3/µL (AUC of 72%) with 71% sensitivity and 72% specificity and 6.48 X10e3/µL (AUC of 74%) with 67% sensitivity and 72% specificity respectively to predict progressed cases with respect to non-progressed cases. Along with WBC, the pre-treatment Absolute Neutrophil Count (ANC) (&gt;3.67)&amp; Absolute Monocyte count (AMC)(&gt;0.42) pre-treatment of the ICIs therapy(io)) showed a significance with Hazard Ratio (HR) – 3.09(95% C.I.– 1.26-7.6) with p-value 0.010, Hazard Ratio (HR) – 3.48(95% C.I. - 1.6-7.57)and p-value &lt;0.001 respectively. The ROC- based cut off for ANC at the pre-treatment of the ICIs therapy(io) were found to be 3.67 X10e3/µL (AUC of 68.4%) with 82.4% sensitivity and 50% specificity. Similarly The ROC- based cut off for AEC at the time of TMC enrolment(first) and AMC at the pre- treatment of the ICIs therapy(io) were found to be 0.22 X10e3/µL (AUC of 69.6%) with 55.9% sensitivity and 82.3% specificity and 0.42 X10e3/µL (AUC of 74.7%) with 72.7% sensitivity and 72.2% specificity respectively to predict progressed cases compared to non-progressed cases. Of 52 patients, 34 (65.4%) had progression. The median (m) PFS was 8.67 months (95% CI 2.26 - 15.09).The one year PFS rate was 46.5 (95% CI 31.2 -60.5). The mPFS in WBC &lt;=7.16 was 26.48 months (95% CI 0 - 53.08) higher than the mPFS of 5.75 (95% CI 0.21 - 11.29) in WBC &gt;7.16 with P value 0.012 at the time of TMC enrolment. Similarly, the mPFS in WBC pre- treatment of the ICIs therapy(io))&lt;=6.48 was13.11 months (95% CI 0 – 28.95) higher than the mPFS of 6.18 (95% CI 2.67-9.68) in WBC &gt;6.48 with P value 0.060.Along with WBC, the mPFS in ANC at the pre- treatment of the ICIs therapy(io)&lt;=3.67 was 27.4(95% CI 0-55.21) higher than the mPFS of 6.18(95% CI 1.47-10.88)in ANC &gt;3.67 with p value 0.010. The mPFS in AMC at the pre-treatment of the ICIs therapy(io)&lt; =0.415 was 27.4 (95% CI 9.41-45.39) higher than the mPFS of 3.91 (95% CI 0.06-7.76) in AMC &gt;0.415with p- value &lt;0.001.We observed mPFS in immunotherapy cycles &gt;=6 to be 15.9 (95% CI 6.98-24.82) was higher than the mPFS of 2.23 (95% CI 0.99-3.481) in immunotherapy cycles&lt;6 with p value 0.025. The patients were followed for a period of 40.35 months (95% CI 26.98 - 53.71). Of 52 patients, 32(61.5%) patients deceased with median OS of 18.46 months (95% CI 10.12 - 26.80) and the one year OS rate was 57.6 (95% CI 41.6 - 70.6). Conclusion: Simple, routinely available and cost effective WBC (TLC), Absolute Neutrophil Count (ANC) ,Absolute Monocyte Count (AMC) and Absolute Eosinophil Count (AEC) from CBC test has a great potential to be used as a biomarker to predict response and clinical outcomes in patients with urinary bladder cancer and RCC patients treated with ICIs.