Inflammatory Indexes as Predictive Biomarkers of Postoperative Complications in Oncological Thoracic Surgery

Evaluation of peripheral blood inflammatory biomarkers in sickle cell disease with and without retinopathy

BACKGROUND

The aim of this study was to evaluate the clinical significance of blood-cell associated inflammation markers in patients with sickle cell disease (SCD) and sickle cell retinopathy (SCR).

METHODS

Neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), monocyte to lymphocyte ratio (MLR), systemic immune inflammation index (SIII), systemic inflammation response index (SIRI), systemic inflammation modulation index (SIMI) and aggregate systemic inflammation index (AISI) were calculated. This study included 45 healthy controls (Group 1) and 100 SCD (Group 2). Patients in Group 2 were then divided into two groups: without SCR (Group 3) and with SCR (Group 4), and patients with SCR (Group 4) were further divided into two groups: non-proliferative sickle cell retinopathy (NPSCR) (Group 5) and proliferative sickle cell retinopathy (PSCR) (Group 6).

RESULTS

The mean values for NLR, PLR, SIII, SIRI, AISI, and SIMI were significantly higher in Group 2 compared to Group 1 (p = 0.011 for NLR, p = 0.004 for SIII, and p < 0.001 for others). Furthermore, AISI and SIMI parameters demonstrated statistically significant discriminatory power to distinguish Group 5 from Group 6 (p = 0.0016 and p = 0.0006, respectively).

CONCLUSION

Given the critical role of inflammatory mechanisms in the pathogenesis of SCD and its related complications, the assessment of blood-cell-associated inflammatory markers may present a pragmatic and advantageous approach to the clinical oversight and therapeutic intervention of SCD.

Risk factor analysis and nomogram prediction model construction of postoperative complications of thoracoscopic non-small cell lung cancer

Background

A series of complications will inevitably occur after thoracoscopic pulmonary resection. How to avoid or reduce postoperative complications is an important research area in the perioperative treatment of thoracic surgery. This study analyzed the risk factors for thoracoscopic postoperative complications of non-small cell lung cancer (NSCLC) and established a nomogram prediction model in order to provide help for clinical decision-making.

Methods

Patients with NSCLC who underwent thoracoscopic surgery from January 2017 to December 2021 were selected as study subjects. The relationship between patient characteristics, surgical factors, and postoperative complications was collected and analyzed. Based on the results of the statistical regression analysis, a nomogram model was constructed, and the predictive performance of the nomogram model was evaluated.

Results

A total of 872 patients who met the study criteria were included in the study. A total of 171 patients had complications after thoracoscopic surgery, accounting for 19.6% of the study population. Logistic regression analysis showed that thoracic adhesion, history of respiratory disease, and lymphocyte-monocyte ratio (LMR) were independent risk factors for complications after thoracoscopic surgery (P<0.05). Variables with P<0.1 in logistic regression analysis were included in the nomogram model. The verification results showed that the area under curve (AUC) of the model was 0.734 [95% confidence interval (CI): 0.693-0.775], and the calibration curve showed that the model had good differentiation. The decision curve analysis (DCA) curve showed that this model has good clinical application value. In subgroup analysis of complications, gender, history of respiratory disease, body mass index (BMI), type of surgical procedure, thoracic adhesion, and Time of operation were identified as significant risk factors for prolonged air leak (PAL) after surgery. Tumor location and forced expiratory volume in the first second (FEV1) were identified as important risk factors for postoperative pulmonary infection. N stage and thoracic adhesion were identified as significant risk factors for postoperative pleural effusion. The AUC for PAL was 0.823 (95% CI: 0.768-0.879). The AUC of postoperative pulmonary infection was 0.714 (95% CI: 0.627-0.801). The AUC of postoperative pleural effusion was 0.757 (95% CI: 0.650-0.864). The calibration curve and DCA curve indicated that the model had good predictive performance and clinical application value.

Conclusions

This study analyzed the risk factors affecting the postoperative complications of NSCLC through thoracoscopic surgery, and the nomogram model built based on the influencing factors has certain significance for the identification and reduction of postoperative complications.

Complete Blood Count Ratios Predict Adverse Events After Total Joint Arthroplasty

INTRODUCTION

Complete blood count-based ratios (CBRs), including neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) are biomarkers associated with the proinflammatory surgical stress response. This study sought to determine whether preoperative CBRs are associated with postoperative complications, protracted hospital length of stay (LOS), and mortality after total joint arthroplasty, as well as establish threshold values for these outcomes for use in future investigations.

METHODS

The Premier Healthcare Database was retrospectively queried for adult patients who underwent primary elective total hip arthroplasty or total knee arthroplasty (TKA). Approximate cut-point values for CBRs were identified by bootstrap simulation using the Youden index. Multivariable adjusted restricted cubic spline models using the predicted cut-point value as the threshold for odds of outcomes were created to identify a final threshold value associated with increased adjusted odds ratio (aOR) of study outcomes.

RESULTS

A total of 32,868 total joint arthroplasties (THA: 12,807, TKA: 20,061) were identified. All measures predicted odds of aggregate postoperative complications (THA: NLR TV: 4.60 [aOR = 2.35], PLR TV: 163.4 [aOR = 1.32], MLR TV: 0.40 [aOR = 2.02], SII TV: 977.00 [aOR = 1.54]; TKA: NLR TV: 3.7 [aOR = 1.69], MLR TV: 0.41 [aOR = 1.62], PLR TV: 205.10 [aOR = 1.43], SII TV: 1,013.10 [aOR = 1.62]; all P < 0.05). A MLR > 0.40 [aOR = 1.54] P < 0.001) was associated with LOS ≥3 days after total hip arthroplasty while an NLR > 13.1 [aOR = 1.38] and an MLR > 0.41[aOR = 1.29] were associated with LOS ≥3 days after total knee arthroplasty (both P < 0.001). No association between inflammatory markers and inpatient mortality was observed.

CONCLUSION

Given CBRs' ability to both predict outcomes and identify patients with a proinflammatory phenotype, the findings of this study provide a framework for future investigations aimed at identifying and treating high-risk patients with immune-modulating therapies. Continued work to validate these findings by applying TVs to interventional clinical trials is needed before wide clinical adoption.

Exploring Inflammatory Parameters in Lung Cancer Patients: A Retrospective Analysis

Inflammation-related parameters serve as pivotal indicators in the prognosis and management of lung cancer. This retrospective investigation aimed to explore the relationship between inflammatory markers and diverse clinical variables in non-small-cell lung cancer patients. A cohort of 187 individuals undergoing elective lobectomy for lung cancer was retrospectively analyzed, spanning an 11-year data collection period. Six inflammation ratios derived from complete peripheral blood counts were assessed. Significantly elevated levels of neutrophil-to-lymphocyte ratio (NLR) (p = 0.005), platelet-to-lymphocyte ratio (PLR) (p = 0.001), Aggregate Index of Systemic Inflammation (AISI) (p = 0.015), Systemic Inflammation Response Index (SIRI) (p = 0.004), and Systemic Immune Inflammation Index (SII) (p = 0.004) were observed in patients with advanced T stages. Significantly, elevated values (p < 0.05) of these parameters were observed in the study's smoker patients compared to non-smokers. A statistically significant correlation was identified between the NLR parameter and tumor size (p = 0.07, r = 0.204), alongside a significant elevation in SIRI (p = 0.041) among patients experiencing postoperative complications. Inflammatory biomarkers emerge as invaluable prognostic indicators for patients with non-small-cell lung cancer, offering potential utility in forecasting their prognosis.

Thoracic delirium index for predicting postoperative delirium in elderly patients following thoracic surgery: A retrospective case-control study

BACKGROUND

Postoperative delirium (POD) is an acute neurological complication in the elderly undergoing thoracic surgery and can result in serious adverse consequences.

AIMS

This study aimed to identify the related risk factors for POD following thoracic surgery, primarily focusing on preoperative serum biomarkers, and further to establish a novel delirium index to better predict POD.

METHODS

A total of 279 patients aged ≥60 years who underwent elective thoracic surgery from August 2021 to August 2022 were enrolled in this observational study. The platelet-to-white blood cell ratio (PWR) was calculated as number the of platelets divided by the number of white blood cells. POD was defined by the confusion assessment method twice daily during the postoperative first 3 days. Multivariate regression analysis was performed to identify all potential variables for POD. Moreover, a novel thoracic delirium index (TDI) was developed based on the related risk factors. The accuracy of TDI and its component factors in predicting POD was determined by the curve of receiver operating characteristic (ROC).

RESULTS

In total, 25 of 279 patients developed POD (8.96%). Age, PWR, and average pain scores within the first 3 days after surgery were regarded as the independent risk factors for POD. Moreover, the ROC analysis showed the TDI, including age, PWR, and average pain scores within the first 3 days after surgery, can more accurately predict POD with the largest area under the curve of 0.790 and the optimal cutoff value of 9.072, respectively.

CONCLUSION

The TDI can scientifically and effectively predict POD to provide optimal clinical guidance for older patients after thoracic surgery.

Neutrophil-lymphocyte ratio and platelet-lymphocyte ratio as potential predictive markers of treatment response in cancer patients treated with immune checkpoint inhibitors: a systematic review and meta-analysis

Background

The role of platelet-lymphocyte ratio (PLR) and neutrophil-lymphocyte ratio (NLR) as independent prognostic markers in different tumors is well established. However, there is a limited review of the potential of NLR and PLR as predictors of treatment outcomes from immune checkpoint inhibitors (ICIs).

Objective

To establish a correlation between NLR and PLR and the potential of clinical benefit from ICIs.

Methods

The literature search was performed for studies that reported the association between NLR, PLR, and treatment outcomes among cancer patients treated with ICIs. The outcomes of interest were objective response rate (ORR), disease control rate (DCR), and progressive disease (PD). ORR was the summation of patients who achieved complete response and partial response. DCR included patients who achieved stable disease. PD was the proportion of patients who progressed, relapsed, or discontinued the treatment. Statistical analysis was performed using the STATA 12.0 package. Heterogeneity was determined by the I2 value. Quality assessment was performed using the Newcastle-Ottawa Scale. Egger's test was used to establish publication bias and sensitivity analysis.

Results

A total of 40 papers that met the inclusion criteria were included in the systematic review. However, only 17 studies were used in the meta-analysis to determine the correlation between NLR, PLR, and treatment response. We found that treatment with ICIs and monitoring of outcomes and adverse events using PLR and NLR parameters have been studied in different tumors. Our analysis showed that low NLR correlated with higher ORR (OR = 0.62 (95% CI 0.47-0.81, p = 0.001) and higher DCR (OR = 0.23, 95% CI 0.14-0.36, p < 0.001). Higher NLR predicted a higher probability of PD (OR = 3.12, 95% CI 1.44, 6.77, p = 0.004). Similarly, low PLR correlated with higher ORR (OR = 0.69, 95% CI 0.5, 0.95, p = 0.025). Generally, patients with low NLR and PLR were more likely to achieve clinical benefit and better response (p-value < 0.001). Meanwhile, patients with high ratios were more likely to progress (p-value < 0.005), although there was significant heterogeneity among studies. There was no significant publication bias observed.

Conclusion

The study showed that high NLR and PLR either at baseline or during treatment is associated with poorer treatment outcome. Therefore, these ratios can be utilized in clinical practice with other markers to determine treatment efficacy from immunotherapy.

Aggregate Index of Systemic Inflammation (AISI), Disease Severity, and Mortality in COVID-19: A Systematic Review and Meta-Analysis

Combined indices of different haematological cell types appear to be particularly promising for investigating the link between systemic inflammation and coronavirus disease 2019 (COVID-19). We conducted a systematic review and meta-analysis to assess the aggregate index of systemic inflammation (AISI), an emerging index derived from neutrophil, monocyte, platelet, and lymphocyte counts, in hospitalized COVID-19 patients with different disease severity and survival status. We searched electronic databases between the 1st of December 2019 and the 10th of June 2023 and assessed the risk of bias and the certainty of evidence. In 13 studies, severe disease/death was associated with significantly higher AISI values on admission vs. non-severe disease/survival (standard mean difference (SMD) = 0.68, 95% CI 0.38 to 0.97, p < 0.001). The AISI was also significantly associated with severe disease/death in five studies reporting odds ratios (4.39, 95% CI 2.12 to 9.06, p ˂ 0.001), but not in three studies reporting hazard ratios (HR = 1.000, 95% CI 0.999 to 1.002, p = 0.39). The pooled sensitivity, specificity, and area under the curve values for severe disease/death were 0.66 (95% CI 0.58 to 0.73), 0.78 (95% CI 0.73 to 0.83), and 0.79 (95% CI 0.76 to 0.83), respectively. Our study has shown that the AISI on admission can effectively discriminate between patients with different disease severity and survival outcome (PROSPERO registration number: CRD42023438025).

Prognostic role of preoperative inflammatory markers in postoperative patients with colorectal cancer

Background

Inflammatory response markers are prognostic factors for several cancers, but their role in postoperative colorectal cancer (CRC) is unclear. The purpose was to evaluate the role of preoperative Neutrophil-to-Lymphocyte ratio (NLR), Platelet-to-Lymphocyte-ratio (PLR), and Lymphocyte-to-Monocyte ratio (LMR) in the prognosis of postoperative CRC patients.

Methods

We retrospectively reviewed 448 CRC patients who had undergone surgical resection from December 2015 to December 2017 in our hospital. The plasma NLR, PLR, LMR, CEA, and CA19-9 were collected within 2 weeks before the operation. We recorded the clinical characteristics and survival data by reviewing medical records and phone calls. We analyzed preoperative inflammatory markers and clinical features using Pearson chi-squared tests or Fisher’s tests. Uni- and multivariate Cox regression analyses were performed, and overall survival (OS) was estimated with the Kaplan–Meier method.

Results

High NLR and PLR were associated with worse overall survival in postoperative CRC (HR = 2.140, 95%CI = (1.488-3.078), P &lt; 0.001; HR =1.820, 95%CI = (1.271-2.605), P = 0.001). High LMR was associated with improved overall survival in postoperative CRC (HR = 0.341, 95%CI = (0.188-0.618), P &lt; 0.001). In the multivariate regression analysis, the increase of NLR resulted in an increase in the risk of death (HR = 1.678, 95%CI = (1.114-2.527), P = 0.013), and for the LMR, a reduction of the risk of death (HR = 0.480, 95%CI = (0.256 - 0.902), P = 0.023). Moreover, TNM stage, CA-199, CEA, nerve or vascular invasion (NVI) and adjuvant chemotherapy after surgery also were associated with worse overall survival in postoperative CRC.

Conclusion

Current evidence indicates that preoperative inflammatory markers NLR, LMR, and PLR are associated with overall survival in postoperative patients with colorectal cancer. NLR is an independent risk factor, and LMR is an independent protective factor in CRC patients after surgery.

A Systematic Review of the Prognostic Significance of the Body Mass Index in Idiopathic Pulmonary Fibrosis

The identification of novel prognostic biomarkers might enhance individualized management strategies in patients with idiopathic pulmonary fibrosis (IPF). Although several patient characteristics are currently used to predict outcomes, the prognostic significance of the body mass index (BMI), a surrogate measure of excess fat mass, has not been specifically investigated until recently. We systematically searched PubMed, Web of Science, and Scopus, from inception to July 2022, for studies investigating associations between the BMI and clinical endpoints in IPF. The Joanna Briggs Institute Critical Appraisal Checklist was used to assess the risk of bias. The PRISMA 2020 statement on the reporting of systematic reviews was followed. Thirty-six studies were identified (9958 IPF patients, low risk of bias in 20), of which 26 were published over the last five years. Significant associations between lower BMI values and adverse outcomes were reported in 10 out of 21 studies on mortality, four out of six studies on disease progression or hospitalization, and two out of three studies on nintedanib tolerability. In contrast, 10 out of 11 studies did not report any significant association between the BMI and disease exacerbation. Our systematic review suggests that the BMI might be useful to predict mortality, disease progression, hospitalization, and treatment-related toxicity in IPF (PROSPERO registration number: CRD42022353363).

Predictive role of blood-based indicators in neuromyelitis optica spectrum disorders

Introduction

This study aimed to assess the predictive role of blood markers in neuromyelitis optica spectrum disorders (NMOSD).

Methods

Data from patients with NMOSD, multiple sclerosis (MS), and healthy individuals were retrospectively collected in a 1:1:1 ratio. The expanded disability status scale (EDSS) score was used to assess the severity of the NMOSD upon admission. Receiver operating characteristic (ROC) curve analysis was used to distinguish NMOSD patients from healthy individuals, and active NMOSD from remitting NMOSD patients. Binary logistic regression analysis was used to evaluate risk factors that could be used to predict disease recurrence. Finally, Wilcoxon signed-rank test or matched-sample t-test was used to analyze the differences between the indicators in the remission and active phases in the same NMOSD patient.

Results

Among the 54 NMOSD patients, neutrophil count, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII) (platelet × NLR) were significantly higher than those of MS patients and healthy individuals and positively correlated with the EDSS score of NMOSD patients at admission. PLR can be used to simultaneously distinguish between NMOSD patients in the active and remission phase. Eleven (20.4%) of the 54 patients had recurrence within 12 months. We found that monocyte-to-lymphocyte ratio (MLR) (AUC = 0.76, cut-off value = 0.34) could effectively predict NMOSD recurrence. Binary logistic regression analysis showed that a higher MLR at first admission was the only risk factor for recurrence (p = 0.027; OR = 1.173; 95% CI = 1.018-1.351). In patients in the relapsing phase, no significant changes in monocyte and lymphocyte count was observed from the first admission, whereas patients in remission had significantly higher levels than when they were first admitted.

Conclusion

High PLR is a characteristic marker of active NMOSD, while high MLR is a risk factor for disease recurrence. These inexpensive indicators should be widely used in the diagnosis, prognosis, and judgment of treatment efficacy in NMOSD.

Prognostic Nutritional Index, Controlling Nutritional Status (CONUT) Score, and Inflammatory Biomarkers as Predictors of Deep Vein Thrombosis, Acute Pulmonary Embolism, and Mortality in COVID-19 Patients

Background: Numerous tools, including nutritional and inflammatory markers, have been evaluated as the predictors of poor outcomes in COVID-19 patients. This study aims to verify the predictive role of the prognostic nutritional index (PNI), CONUT Score, and inflammatory markers (monocyte to lymphocyte ratio (MLR), neutrophil to lymphocyte ratio (NLR), platelet to lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in cases of deep vein thrombosis (DVT) and acute pulmonary embolism (APE) risk, as well as mortality, in COVID-19 patients. Methods: The present study was designed as an observational, analytical, retrospective cohort study, and included 899 patients over the age of 18 who had a COVID-19 infection, confirmed through real time-polymerase chain reaction (RT-PCR), and were admitted to the County Emergency Clinical Hospital and Modular Intensive Care Unit of UMFST “George Emil Palade” of Targu Mures, Romania between January 2020 and March 20212. Results: Non-Surviving patients were associated with a higher incidence of chronic kidney disease (p = 0.01), cardiovascular disease (atrial fibrillation (AF) p = 0.01; myocardial infarction (MI) p = 0.02; peripheral arterial disease (PAD) p = 0.0003), malignancy (p = 0.0001), tobacco (p = 0.0001), obesity (p = 0.01), dyslipidemia (p = 0.004), and malnutrition (p < 0.0001). Multivariate analysis showed that both nutritional and inflammatory markers had a high baseline value and were all independent predictors of adverse outcomes for all enrolled patients (for all p < 0.0001). The presence of PAD, malignancy, and tobacco, were also independent predictors of all outcomes. Conclusions: According to our findings, higher MLR, NLR, PLR, SII, SIRI, AISI, CONUT Score, and lower PNI values at admission strongly predict DVT risk, APE risk, and mortality in COVID-19 patients. Moreover, PAD, malignancy, and tobacco, all predicted all outcomes, while CKD predicts APE risk and mortality, but not the DVT risk.

Carotid Plaque Features and Inflammatory Biomarkers as Predictors of Restenosis and Mortality Following Carotid Endarterectomy

BACKGROUND

Carotid endarterectomy (CEA) is the first-line surgical intervention for cases of severe carotid stenoses. Unfortunately, the restenosis rate is high after CEA. This study aims to demonstrate the predictive role of carotid plaque features and inflammatory biomarkers (monocyte-to-lymphocyte ratio (MLR), neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), systemic inflammatory index (SII), Systemic Inflammation Response Index (SIRI), and Aggregate Index of Systemic Inflammation (AISI)) in carotid restenosis and mortality at 12 months following CEA.

METHODS

The present study was designed as an observational, analytical, retrospective cohort study and included all patients over 18 years of age with a minimum of 70% carotid stenosis and surgical indications for CEA admitted to the Vascular Surgery Clinic, Emergency County Hospital of Targu Mures, Romania between 2018 and 2021.

RESULTS

According to our results, the high pre-operative values of inflammatory biomarkers-MLR (OR: 10.37 and OR: 6.11; p < 0.001), NLR (OR: 34.22 and OR: 37.62; p < 0.001), PLR (OR: 12.02 and OR: 16.06; p < 0.001), SII (OR: 18.11 and OR: 31.70; p < 0.001), SIRI (OR: 16.64 and OR: 9.89; p < 0.001), and AISI (OR: 16.80 and OR: 8.24; p < 0.001)-are strong independent factors predicting the risk of 12-month restenosis and mortality following CEA. Moreover, unstable plaque (OR: 2.83, p < 0.001 and OR: 2.40, p = 0.04) and MI (OR: 3.16, p < 0.001 and OR: 2.83, p = 0.005) were independent predictors of all outcomes. Furthermore, AH (OR: 2.30; p = 0.006), AF (OR: 1.74; p = 0.02), tobacco (OR: 2.25; p < 0.001), obesity (OR: 1.90; p = 0.02), and thrombotic plaques (OR: 2.77; p < 0.001) were all independent predictors of restenosis, but not for mortality in all patients. In contrast, antiplatelet (OR: 0.46; p = 0.004), statin (OR: 0.59; p = 0.04), and ezetimibe (OR:0.45; p = 0.03) therapy were protective factors against restenosis, but not for mortality.

CONCLUSIONS

Our data revealed that higher preoperative inflammatory biomarker values highly predict 12-month restenosis and mortality following CEA. Furthermore, age above 70, unstable plaque, cardiovascular disease, and dyslipidemia were risk factors for all outcomes. Additionally, AH, AF, smoking, and obesity were all independent predictors of restenosis but not of mortality in all patients. Antiplatelet and statin medication, on the other hand, were protective against restenosis but not against mortality.