Elevated pretreatment platelet-to-lymphocyte ratio is associated with poor survival in stage IV non-small cell lung cancer with malignant pleural effusion

C-Reactive Protein as an Early Predictor of Efficacy in Advanced Non-Small-Cell Lung Cancer Patients: A Tumor Dynamics-Biomarker Modeling Framework

In oncology, longitudinal biomarkers reflecting the patient's status and disease evolution can offer reliable predictions of the patient's response to treatment and prognosis. By leveraging clinical data in patients with advanced non-small-cell lung cancer receiving first-line chemotherapy, we aimed to develop a framework combining anticancer drug exposure, tumor dynamics (RECIST criteria), and C-reactive protein (CRP) concentrations, using nonlinear mixed-effects models, to evaluate and quantify by means of parametric time-to-event models the significance of early longitudinal predictors of progression-free survival (PFS) and overall survival (OS). Tumor dynamics was characterized by a tumor size (TS) model accounting for anticancer drug exposure and development of drug resistance. CRP concentrations over time were characterized by a turnover model. An x-fold change in TS from baseline linearly affected CRP production. CRP concentration at treatment cycle 3 (day 42) and the difference between CRP concentration at treatment cycles 3 and 2 were the strongest predictors of PFS and OS. Measuring longitudinal CRP allows for the monitoring of inflammatory levels and, along with its reduction across treatment cycles, presents a promising prognostic marker. This framework could be applied to other treatment modalities such as immunotherapies or targeted therapies allowing the timely identification of patients at risk of early progression and/or short survival to spare them unnecessary toxicities and provide alternative treatment decisions.

Pro-Tumorigenic and Thrombotic Activities of Platelets in Lung Cancer

Aside from their key protective roles in hemostasis and innate immunity, platelets are now recognized as having multifaceted, adverse roles in the pathogenesis, progression and outcome of many types of human malignancy. The most consistent and compelling evidence in this context has been derived from the notable association of elevated circulating platelet counts with the onset and prognosis of various human malignancies, particularly lung cancer, which represents the primary focus of the current review. Key topics include an overview of the association of lung cancer with the circulating platelet count, as well as the mechanisms of platelet-mediated, pro-tumorigenic immunosuppression, particularly the role of transforming growth factor beta 1. These issues are followed by a discussion regarding the pro-tumorigenic role of platelet-derived microparticles (PMPs), the most abundant type of microparticles (MPs) in human blood. In this context, the presence of increased levels of PMPs in the blood of lung cancer patients has been associated with tumor growth, invasion, angiogenesis and metastasis, which correlate with disease progression and decreased survival times. The final section of the review addresses, firstly, the role of cancer-related platelet activation and thrombosis in the pathogenesis of secondary cardiovascular disorders and the associated mortality, particularly in lung cancer, which is second only to disease progression; secondly, the review addresses the potential role of antiplatelet agents in the adjunctive therapy of cancer.

Establishment of a prognostic risk prediction modelfor non-small cell lung cancer patients with brainmetastases: a retrospective study

Background

Patients with non-small cell lung cancer (NSCLC) who develop brain metastases (BM) have a poor prognosis. This study aimed to construct a clinical prediction model to determine the overall survival (OS) of NSCLC patients with BM.

Methods

A total of 300 NSCLC patients with BM at the Yunnan Cancer Centre were retrospectively analysed. The prediction model was constructed using the least absolute shrinkage and selection operator-Cox regression. The bootstrap sampling method was employed for internal validation. The performance of our prediction model was compared using recursive partitioning analysis (RPA), graded prognostic assessment (GPA), the update of the graded prognostic assessment for lung cancer using molecular markers (Lung-molGPA), the basic score for BM (BSBM), and tumour-lymph node-metastasis (TNM) staging.

Results

The prediction models comprising 15 predictors were constructed. The area under the curve (AUC) values for the 1-year, 3-year, and 5-year time-dependent receiver operating characteristic (curves) were 0.746 (0.678-0.814), 0.819 (0.761-0.877), and 0.865 (0.774-0.957), respectively. The bootstrap-corrected AUC values and Brier scores for the prediction model were 0.811 (0.638-0.950) and 0.123 (0.066-0.188), respectively. The time-dependent C-index indicated that our model exhibited significantly greater discrimination compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging. Similarly, the decision curve analysis demonstrated that our model displayed the widest range of thresholds and yielded the highest net benefit. Furthermore, the net reclassification improvement and integrated discrimination improvement analyses confirmed the enhanced predictive power of our prediction model. Finally, the risk subgroups identified by our prognostic model exhibited superior differentiation of patients' OS.

Conclusion

The clinical prediction model constructed by us shows promise in predicting OS for NSCLC patients with BM. Its predictability is superior compared with RPA, GPA, Lung-molGPA, BSBM, and TNM staging.

Biological Rationale for Peripheral Blood Cell-Derived Inflammatory Indices and Related Prognostic Scores in Patients with Advanced Non-Small-Cell Lung Cancer

PURPOSE OF REVIEW

To describe the biological rationale of peripheral blood cells (PBC)-derived inflammatory indexes and assess the related prognostic scores for patients with advanced non-small cell lung cancer (aNSCLC) treated with immune-checkpoint inhibitors (ICI).

RECENT FINDINGS

Inflammatory indexes based on PBC may indicate a pro-inflammatory condition affecting the immune response to cancer. The lung immune prognostic index (LIPI), consisting of derived neutrophils-to-lymphocyte ratio (NLR) and lactate dehydrogenase, is a validated prognostic tool, especially for pretreated aNSCLC patients, where the combination of NLR and PD-L1 tumour expression might also be predictive of immunotherapy benefit. In untreated high-PD-L1 aNSCLC patients, the Lung-Immune-Prognostic score (LIPS), including NLR, ECOG PS and concomitant steroids, is prognostic, and its modified version might indicate patients with favourable outcomes despite an ECOG PS of 2. NLR times platelets (i.e., SII), included in the NHS-Lung score, might improve the prognostication for combined chemoimmunotherapy. PBC-derived inflammatory indexes and related scores represent accurate, reproducible and non-expensive prognostic tools with clinical and research utility.

Prognostic factors for long-term survival following complete resection by lobectomy in stage I non-small cell lung cancer

BACKGROUND

The aim of this study was to evaluate predictors for long-term overall survival (OS) in patients with stage I non-small cell lung cancer (NSCLC).

METHODS

All patients undergoing complete resection by lobectomy for stage I NSCLC between October 2012 and December 2015 at a single center were included. Univariable and multivariable Cox regression analyses were performed to identify prognostic factors.

RESULTS

A total of 92 patients were included. Univariable and multivariable Cox regression analyses revealed preoperative neutrophil to lymphocyte ratio (NLR, p = 0.005), preoperative diffusion capacity of the lungs for carbon monoxide (DLCO, p = 0.010) and forced expiratory volume in 1 second (FEV1, p = 0.041) as well as male gender (p = 0.026) as independent prognostic factors for OS. Combining the calculated cutoff values for FEV1 (<73.0%) and NLR (>3.49) into one parameter resulted in a highly significant difference in survival times when stratified by this variable.

CONCLUSIONS

Recently, much emphasis has been put on the prognostic importance of blood biomarkers in NSCLC. In our study, NLR was an independent factor for OS, as were baseline characteristics such as DLCO, FEV1, and gender. Further studies on the association of biomarkers for systemic inflammation and lung function parameters with respect to patient survival are warranted.

The Pan-Immune-Inflammation Value predicts the survival of patients with anaplastic lymphoma kinase-positive non-small cell lung cancer treated with first-line ALK inhibitor

BACKGROUND

Anaplastic lymphoma kinase (ALK) tyrosine kinase inhibitors (TKIs) have significantly improved the clinical outcomes of patients with ALK-positive non-small cell lung cancer (NSCLC). However, reliable biomarkers to predict the prognostic role of this treatment are lacking. The Pan-Immune-Inflammation Value (PIV) has recently been demonstrated as a novel comprehensive biomarker to predict survival of patients with solid tumors. Our study aimed to evaluate the prognostic power of PIV in this group of patients.

PATIENTS AND METHODS

94 patients with advanced ALK-positive NSCLC who received first-line ALK inhibitors were enrolled in this study. PIV was calculated as the product of peripheral blood neutrophil, monocyte, and platelet counts divided by lymphocyte count. Kaplan-Meier method and Cox hazard regression models were used for survival analyses.

RESULTS

The 1-year progression-free survival (PFS) was 63.5%, and the 5-year overall survival (OS) rate was 55.1%. Patients with higher PIV, neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), and systemic immune inflammation index (SII) had worse PFS in univariate analysis, but only the PIV (hazard ratio [HR] = 2.90, 95% confidence interval [CI]: 1.79-4.70, p < 0.001) was an independent prognostic factor in multivariate analysis. Similarly, patients with higher PIV, NLR, PLR, and SII had a worse OS in the univariate analysis, but only the PIV (HR = 4.70, 95% CI: 2.00-11.02, p < 0.001) was significantly associated with worse OS in multivariate analysis.

CONCLUSION

PIV is a comprehensive and convenient predictor of both PFS and OS in patients with ALK-positive advanced NSCLC who received first-line ALK TKIs. Prospective clinical trials are required to validate the value of this new parameter.

Overall Survival Prediction of Advanced Cancer Patients by Selection of the Most Significant Baseline Serum Biomarker Combination

Introduction: Consistent association between elevated baseline serum values and C-reactive protein (CRP), cross-linked fibrin degradation products (D-dimer), lactate dehydrogenase (LDH), decreased baseline serum albumin, absolute lymphocyte count to absolute monocyte count ratio (LMR), elevated absolute neutrophil count to absolute lymphocyte count ratio (NLR), elevated platelet count to absolute lymphocyte count ratio (PLR), and between some combinations of these biomarkers and the short overall survival of patients with malignant diseases has already been reported. These biomarkers are independent prognostic factors for cancer. Here, the most significant biomarker combination of these values was searched and studied in real-life advanced cancer patients of a single center.

Methods: The authors retrospectively analyzed the association of the aforementioned biomarkers and their combination and OS of 75 consecutive cancer patients with locally advanced, recurrent, or metastatic diseases. Validated cut-off determination was used.

Results: CRP, albumin, and PLR showed marked association with OS. Cut-off values for significant shorter OS were 30.65 mg/L (p &lt; 0.001), 44.35 g/L (p &lt; 0.001), and 168.20 (p &lt; 0.001), respectively. Based on assessed biomarker cut-offs, four patient groups were created to determine whether biomarker values were out of range (ORV) compared to cut-off: 1) No ORV biomarkers (n = 24; OS = 26.07 months); 2) one ORV biomarker (n = 21; OS = 13.50 months); 3) two ORV biomarkers (n = 20; OS = 7.97 months), and 4) three ORV biomarkers (n = 10; OS = 3.91 months). Significant differences in OS were detected between the groups: For 1. vs. 2. hazard ratio (HR) = 3.0 (95% CI: 1.5–6.2), p = 0.003; for 1. vs. 3. HR = 4.1 (95% CI: 2.0–8.3), p &lt; 0.001; and for 1. vs. 4. HR = 10.2 (95% CI: 4.2–24.6), p &lt; 0.001.

Conclusion: Based on our analysis, we can confirm that the complex monitoring of CRP, albumin, and PLR would provide a good estimation of OS. Large scale prospective studies are warranted to explore this and other useful combinations of prognostic biomarkers and their relationship to the well-established prognostic systems in real-life.

Elevated Pretreatment Fibrinogen-to-Lymphocyte Percentage Ratio Predict Tumor Staging and Poor Survival in Non-Small Cell Lung Cancer Patients with Chemotherapy or Surgery Combined with Chemotherapy

Purpose

The objective of our study was to assess the association between lymphocyte percentage (LY%), fibrinogen (FIB), fibrinogen-to-lymphocyte percentage ratio (FLR) and the tumor staging and the clinical outcome role in non-small cell lung cancer (NSCLC) patients with chemotherapy or surgery combined with chemotherapy.

Patients and Methods

Between August 2013 and October 2020, 375 patients initially diagnosed with NSCLC and 201 healthy subjects were enrolled in the retrospective study. The concentrations of LY%, FIB, and FLR were compared between the case group and the control group by using the Mann–Whitney U-test or Kruskal–Wallis test, and then these biomarkers were compared in terms of the tumor category and PTNM stage of the test group, etc. The cutoffs of LY%, FIB, and FLR were determined using X-tile software. The prognostic roles of LY%, FIB, and FLR were identified by the Kaplan–Meier curve and Cox regression model. The biological markers on overall survival (OS) were analyzed.

Results

The study showed that the concentration levels of LY%, FIB, and FLR in the stage III–IV group were significant difference from those in the stage I–II group (P<0.001), indicating that three biomarkers (LY%, FIB, and FLR) were significantly correlated with tumor staging. Pretreatment high FIB and FLR and low LY% indicated an increased risk of death in NSCLC patients. Also, it was found that the clinical outcome of low FLR patients with chemotherapy or chemotherapy combined with surgery was superior to high FLR patients.

Conclusion

Our findings demonstrated that FLR could be used to predict NSCLC staging and was an independent prognosis factor within NSCLC patients receiving chemotherapy or chemotherapy combined with surgery.

Clinical Characteristics and Outcome of Pathologic N0 Non-small Cell Lung Cancer Patients With False Positive Mediastinal Lymph Node Metastasis on FDG PET-CT

BACKGROUND/AIM

Preoperative fluorine-18 fluorodeoxyglucose positron emission tomography/computed tomography (FDG PET-CT) is a non-invasive and useful diagnostic tool to evaluate mediastinal lymph node (LN) metastasis in lung cancer. However, there are often false-positive LN cases in FDG PET-CT. This study aimed to explore the clinical characteristics and outcome of pathologic N0 non-small cell lung cancer patients with false-positive mediastinal LN on FDG PET-CT.

PATIENTS AND METHODS

We enrolled 147 patients who underwent preoperative FDG PET-CT scan and mediastinal LN dissection. These patients were re-evaluated for post-operative pathologic nodal metastasis and divided into a false-positive group and a group of others.

RESULTS

Among 40 patients diagnosed with clinical N1-3 on FDG PET-CT, 19 (47.5%) patients were pathologic N0, meaning false-positive LN by PET-CT. Preoperative absolute platelet count and platelet-lymphocyte ratio were significantly higher in patients with pathologic N0. The presence of lymphatic invasion was significantly lower in patients with pathologic N0 than in the group of others. Recurrence-free survival was significantly shorter in patients with false positive LN than in patients with true positive LN or true negative LN at the same pathologic stage.

CONCLUSION

Higher absolute platelet count and PLR, lower proportion of lymphatic invasion and shorter recurrence-free survival were associated with false positive mediastinal LN on preoperative FDG PET-CT.

Frontiers in Pharmacology: Review Manuscript Targeting of the Neutrophil as an Adjunctive Strategy in Non-Small Cell Lung Cancer

Lung cancer remains the leading cause of cancer mortality in the United States, with non-small cell lung cancer (NSCLC) accounting for around 85% of cases. Of particular concern is the poor responsiveness of this malignancy to therapy, resulting in a very low 5-year survival rate (17.4%) and a prominent tendency to progress to metastatic disease. A number of very recent studies, both pre-clinical and clinical, have implicated the neutrophil in both the pathogenesis and unsatisfactory response to therapy of NSCLC. In this context, movement of neutrophils into the tumor microenvironment (TME) is a common feature of NSCLC. Indeed neutrophils are the dominant type of immune cell in the NSCLC TME, creating a highly immunosuppressive milieu that is not only conducive to tumor growth and spread, but also represents a significant obstacle to the success of anti-tumor therapy, especially novel immunotherapies. The clinically relevant adverse impact of a neutrophil predominance both systemically and in the TME of patients with NSCLC is underscored by the negative prognostic value of both a persistent neutrophilia and, in particular, a high (≥5) neutrophil:lymphocyte ratio. On a more positive note, however, recognition of the involvement of the neutrophil in both the pathophysiology of NSCLC and treatment failure has enabled identification of neutrophil-targeted strategies that have the potential to serve as adjuncts to standard anti-cancer therapies, including immunotherapy. These strategies together with a consideration of the immunosuppressive, pro-tumorigenic properties of the neutrophil represent the major thrusts of this review.

Machine learning applied to near-infrared spectra for clinical pleural effusion classification

Lung cancer patients with malignant pleural effusions (MPE) have a particular poor prognosis. It is crucial to distinguish MPE from benign pleural effusion (BPE). The present study aims to develop a rapid, convenient and economical diagnostic method based on FTIR near-infrared spectroscopy (NIRS) combined with machine learning strategy for clinical pleural effusion classification. NIRS spectra were recorded for 47 MPE samples and 35 BPE samples. The sample data were randomly divided into train set (n = 62) and test set (n = 20). Partial least squares, random forest, support vector machine (SVM), and gradient boosting machine models were trained, and subsequent predictive performance were predicted on the test set. Besides the whole spectra used in modeling, selected features using SVM recursive feature elimination algorithm were also investigated in modeling. Among those models, NIRS combined with SVM showed the best predictive performance (accuracy: 1.0, kappa: 1.0, and AUC_ROC: 1.0). SVM with the top 50 feature wavenumbers also displayed a high predictive performance (accuracy: 0.95, kappa: 0.89, AUC_ROC: 0.99). Our study revealed that the combination of NIRS and machine learning is an innovative, rapid, and convenient method for clinical pleural effusion classification, and worth further evaluation.

Impact of Combined Chronic Obstructive Pulmonary Disease Status and Systemic Inflammation on Outcome of Advanced NSCLC: Multicenter Retrospective Cohort Study

Background

In patients with non-small cell lung cancer (NSCLC), both chronic obstructive pulmonary disease (COPD) and systemic inflammatory biomarkers, such as neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR), have significant association with prognosis. NLR and PLR also predict mortality in patients with COPD alone. A combination of the two parameters may be helpful in a more individualized approach for predicting prognosis in NSCLC.

Methods

Medical records of patients with stage IIIB and IV NSCLC from January 2012 to January 2018 in seven university hospitals were reviewed. Patients were categorized into four subgroups based on pulmonary function test results and cutoffs for NLR or PLR.

Results

A total of 277 patients were evaluated and categorized into non-COPD and COPD groups; 194 patients were in the non-COPD group and 83 patients were in the COPD group. The non-COPD group showed significantly longer overall survival (OS) compared with the COPD group (P = 0.019). Median survival was significantly different between high/low PLR groups (P < 0.001), between high/low NLR groups (P = 0.001), and between high/low c-reactive protein (CRP) groups (P < 0.001). PLR, NLR and CRP showed significant correlations with each other. PLR showed a significant negative linear correlation with FVC (absolute) (r = −0.149, P = 0.015), FVC (%) (r = −0.192, P = 0.002), DLCO (absolute) (r = −0.271, P < 0.001), DLCO (%) (r = −0.139, P = 0.032), and NLR (r = 0.718, P < 0.001). In the multivariate analysis, the high PLR, COPD sub-group showed significantly higher risk for mortality (HR 2.066 (1.175–3.633), P = 0.012) compared with the low-PLR non-COPD group. However, COPD-NLR subtype was not an independent predictor for OS.

Conclusion

A combination of COPD status and PLR may be a cost-effective and readily available prognostic marker in patients with advanced NSCLC.

Pre-radiosurgery leucocyte ratios and modified glasgow prognostic score predict survival in non-small cell lung cancer brain metastases patients

INTRODUCTION

The predictive value of the pre-radiosurgery Neutrophil-to-Lymphocyte Ratio (NLR), Platelet-to-Lymphocyte Ratio (PLR), Lymphocyte-to-Monocyte Ratio (LMR) and the modified Glasgow Prognostic Score (mGPS) was assessed for the first time in a homogenous group of NSCLC brain metastaes (BM) patients.

METHODS

We retrospectively evaluated 185 NSCLC-BM patients, who were treated with Gamma Knife Radiosurgery (GKRS). Patients with immunotherapy or targeted therapy were excluded. Routine laboratory parameters were reviewed within 14 days before GKRS1.

RESULTS

Median survival after GKRS1 was significantly longer in patients with NLR < 5 (p < 0.001), PLR < 180 (p = 0.003) and LMR ≥ 4 (p = 0.023). The Cox regression model for the continuous metric values revealed that each increase in the NLR of 1 equaled an increase of 4.3% in risk of death (HR: 1.043; 95%CI = 1.020-1.067, p < 0.001); each increase in the PLR of 10 caused an increase of 1.3% in risk of death (HR: 1.013; 95%CI = 1.004-1.021; p = 0.003) and each increase in the LMR of 1 equaled a decrease of 20.5% in risk of death (HR: 0.795; 95%CI = 0.697-0.907; p = 0.001). Moreover, the mGPS group was a highly significant predictor for survival after GKRS1 (p < 0.001) with a HR of 2.501 (95%CI = 1.582-3.954; p < 0.001). NLR, PLR, LMR values and mGPS groups were validated as independent prognostic factors for risk of death after adjusting for sex, KPS, age and presence of extracranial metastases.

CONCLUSION

NLR, PLR, LMR and mGPS represent effective and simple tools to predict survival in NSCLC patients prior to radiosurgery for brain metastases.

The prognostic significance of inflammation-based scores in patients with ampullary carcinoma after pancreaticoduodenectomy

Background

Growing evidence indicates that the systemic inflammatory response plays an important role in cancer development and progression. Several inflammatory markers have been reported to be associated with clinical outcomes in patients with various types of cancer. This study was designed to evaluate the prognostic value of inflammatory indexes in patients with ampullary cancer (AC) who underwent pancreaticoduodenectomy (PD).

Methods

We retrospectively reviewed the data of 358 patients with AC who underwent PD between 2009 and 2018. R software was used to compare the area under the time-dependent receiver operating characteristic (ROC) curves (AUROCs) of the inflammation-based indexes, including the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), modified Glasgow Prognostic Score (mGPS), prognostic nutritional index (PNI) and prognostic index (PI), in terms of their predictive value for survival. The survival differences of these indexes were compared by the Kaplan-Meier method and univariate and multivariate analyses were performed to determine the prognostic factors of disease-free survival (DFS) and overall survival (OS).

Results

The estimated 1-, 2-, and 3-year OS and DFS rates were 83.9, 65.8, and 55.2% and 58.0, 42.8, and 37.8%, respectively, for the entire cohort. The survival differences were significant in terms of OS and DFS when patients were stratified by these inflammation-based indexes. The comparisons of the AUROCs of these inflammation-based indexes illustrated that NLR and PI displayed the highest prognostic value, compared to the other indexes. When NLR and PI were combined, NLR-PI showed even higher AUROC values and was identified as a significant prognostic factor for OS and DFS.

Conclusion

Specific inflammatory indexes, such as NLR, PLR and dNLR, were found to be able to predict the OS or DFS of patients. As a novel inflammatory index, the level of NLR-PI, which can be regarded as a more useful prognostic index, exhibited strong predictive power for predicting the prognosis of patients with AC after the PD procedure.

Prognostic factors of recurrence of malignant pleural effusion: what is the role of neoplasia progression?

BACKGROUND

It is known that malignant pleural effusion (MPE) recurs rapidly, in a considerable number of patients. However, some patients do not have MPE recurrence. Since MPE is associated with an average survival of 4-7 months, accurate prediction of prognosis may help recognize patients at higher risk of pleural recurrence, aiming to individualize more intensive treatment strategies.

METHODS

A prospectively assembled database of cases with pleural effusion treated at a single institution analyzed a subset of patients with symptomatic MPE. Prognostic factors for pleural recurrence were identified by univariable analysis using Kaplan-Meier method and the log-rank test was used for the comparison between the curves. Univariate and multiple Cox regression models were used to evaluate the risk (HR) of recurrence. Receiver operating characteristics (ROC) analysis determined the cutoff points for continuous variables.

RESULTS

A total of 288 patients were included in the analysis. Recurrence-free survival was of 76.6% at 6 months and 73.3% at 12 months. Univariable analysis regarding factors affecting postoperative recurrence was: lymphocytes, platelets, pleural procedure, chemotherapy lines and number of metastases. The independent factors for recurrence-free survival were pleural procedure and chemotherapy lines. Patients who were submitted to pleurodesis had a protective factor for recurrence, with an HR =0.34 (95% CI, 0.15-0.74, P=0.007). On the other hand, patients submitted to the 1st and 2nd line of palliative CT had, respectively, an HR risk = 2.81 (95% CI, 1.10-7.28, P=0.034) and HR =3.23 (95% CI, 1.33-7.84, P=0.010).

CONCLUSIONS

patients receiving the first or second line of systemic treatment have a higher risk of MPE recurrence when compared to patients who underwent MPE treatment before starting the systemic treatment. The definitive treatment of MPE, such as pleurodesis, was associated with a lower risk of MPE recurrence.

Relationship between Neutrophil-to-Lymphocyte Ratio and Systemic Lupus Erythematosus: A Meta-analysis

Systemic lupus erythematosus (SLE) is a chronic systematic autoimmune disease. Current methods of diagnosing SLE or evaluating its activity are complex and expensive. Numerous studies have suggested that neutrophil-to-lymphocyte ratio (NLR) is closely correlated with the presence of SLE and its activity, suggesting that it may serve as a diagnostic and monitoring indicator for SLE. Therefore, we performed a meta-analysis to systematically assess the association between NLR and SLE. We performed a literature search until 12 April 2019 in the PubMed, Web of Science, and China National Knowledge Infrastructure databases. Cross-sectional studies comparing the NLR of SLE patients versus those of healthy controls, of active versus inactive SLE patients, and of SLE patients with versus without lupus nephritis were considered for inclusion. Mean intergroup NLR differences were estimated using standardized mean differences and their 95% confidence intervals. Study quality was assessed using the Agency for Healthcare Research and Quality instrument for cross-sectional studies. Fourteen studies with 1,781 SLE patients and 1,330 healthy controls were included in this meta-analysis. The pooled results showed that the NLR was significantly higher in SLE patients than in healthy controls, in active SLE patients than in inactive SLE patients, and in SLE patients with lupus nephritis than in those without lupus nephritis. NLR may be an indicator for monitoring disease activity and reflecting renal involvement in SLE patients. Nevertheless, more high-quality studies are warranted to further validate our findings.