A novel predictive model based on preoperative blood neutrophil-to-lymphocyte ratio for survival prognosis in patients with gastric neuroendocrine neoplasms

Last decade of advances in gastric neuroendocrine tumors: Innovations, challenges, and future directions

BACKGROUND

Gastric neuroendocrine tumors (G-NETs) are rare tumors originating from enterochromaffin-like cells, with an incidence of 0.4 per 100000 annually. There are three main types: (1) Type I, linked to chronic atrophic gastritis and hypergastrinemia, makes up 75%–80% of G-NETs; (2) Type II, associated with Zollinger-Ellison syndrome (ZES) and multiple endocrine neoplasia, comprises 5%; and (3) Type III, sporadic tumors with a higher metastatic potential, accounting for 15%–25%. Diagnosis involves endoscopy, biopsy, and histological examination. Additional methods include serum gastrin testing, immunohistochemistry, and imaging techniques such as computer tomography or magnetic resonance imaging for detecting metastasis. Type I treatment usually involves endoscopic resection (ER), with surgical resection for recurrence. Somatostatin analogs (SSAs) can reduce tumor size, and the prognosis is generally excellent. Type II treatment centers on surgical removal of the gastrinoma, with ER for smaller lesions and SSAs for symptom management. Type III requires surgical resection (partial or total gastrectomy) with lymph node dissection, and possibly chemotherapy. This type has a worse prognosis due to its aggressive nature. Emerging treatments like Peptide Receptor Radionuclide Therapy are promising for advanced cases, and ongoing research into immunotherapies is expanding future treatment options. Regular endoscopic follow-up is crucial to monitor for recurrence or metastasis across all types. Our literature review explores the current perspectives on G-NETs and highlights the importance of further research to improve diagnostic precision and treatment, particularly for those associated with less favorable cases.

AIM

To improve diagnostic precision and treatment, particularly for those associated with less favorable cases.

METHODS

A systematic search was conducted in PubMed, Scopus, and Web of Science until September 2024. Two independent reviewers screened titles, abstracts, and full texts for eligibility based on G-NET treatment in adults. Eligible studies included cohort studies, clinical trials, case series, and case reports, while in vitro, pediatric, and non-English studies were excluded. Relevant data were extracted independently, and disagreements were resolved through discussion. Study quality was assessed using appropriate tools.

RESULTS

G-NETs are rare, classified into three types: (1) Type I; (2) Type II; and (3) Type III. Type I G-NETs, often associated with chronic atrophic gastritis, are typically slow-growing and low-grade, with favorable outcomes following surgical resection. Type II G-NETs arise in hypergastrinemia conditions like multiple endocrine neoplasia and ZES, showing moderate malignancy risk. Type III G-NETs, the most aggressive and least common, present with distant metastases and poor prognosis. Diagnosis relies on endoscopy, imaging, and biomarkers like chromogranin A. Treatment varies by type, ranging from ER to aggressive surgery and chemotherapy for advanced cases. Regular follow-up is essential to monitor recurrence, particularly for type III G-NETs.

CONCLUSION

G-NETs require tailored diagnosis and treatment based on type and stage. Types I and II generally have better prognosis, while types III and IV are linked to poorer outcomes due to invasion and metastasis. Treatment strategies vary from ER for type I to extensive surgery for type III. Emerging therapies, like somatostatin analogs and peptide-receptor radionuclide therapies, show promise in advanced cases. Further research is essential to improve early diagnosis and treatment, particularly for high-risk lesions.

Evaluating the prognostic significance of the pre-treatment neutrophil-to-lymphocyte and monocyte-to-lymphocyte ratios in 177Lu-DOTATATE PRRT treated patients with advanced metastatic neuroendocrine tumors

PURPOSE

This study aimed to investigate the role of pre-treatment neutrophil-to-lymphocyte ratio (NLR) and monocyte-to-lymphocyte ratio (MLR) in the prognosis assessment of 177Lu-DOTATATE Peptide Receptor Radionuclide Therapy (PRRT) treated patients with advanced metastatic neuroendocrine tumors (NETs).

METHODS

Eligible PRRT-treated patients (n = 247, 2010-2019) were included. Pre-PRRT NLR and MLR were calculated from complete blood count data. Data on tumor characteristics, response to PRRT, progression-free survival (PFS), and overall survival (OS) were evaluated using COXPH analyses.

RESULTS

In NET patients, median values of NLR and MLR were 2.21 (IQR = 1.66-3.00) and 0.14 (IQR = 0.06-0.24), respectively. NLR showed significant positive association with G3 tumors (median = 3.64, IQR = 2.1-4.26, p = 0.022) and high 18F-FDG avidity (SUVmax>5) (median = 2.5, IQR = 1.82-3.56, p = 0.003). MLR was significantly associated with high disease burden (median = 0.18, IQR = 0.08-0.29, p = 0.0083). MLR distinguished between the PRRT non-responders with progressive disease and responders with complete/partial response (median 0.19 versus 0.12, p = 0.043) or responders with stable disease (median 0.19 versus 0.14, p = 0.045). The ratios independently correlated with disease progression and OS. Patients in NLRhigh (>3.5) group displayed significantly shorter median PFS and OS (48 and 58 months) compared to NLRlow (≤3.5) group (108 and 96 months) (p < 0.01). Patients in MLRhigh (>0.25) group displayed significantly shorter median PFS and OS (40 and 52 months) compared to MLRlow (≤0.25) group (108 and 102 months) (p < 0.01).

CONCLUSION

Pre-treatment NLR and MLR had an independent prognostic impact on disease progression and OS in PRRT-treated NET patients. This routine, inexpensive CBC-based test in the standard pre-PRRT workup demonstrates the prognostic value and may aid clinicians in the risk stratification of NET patients.

A blood-based liquid biopsy analyzing soluble immune checkpoints and cytokines identifies distinct neuroendocrine tumors

BACKGROUND

Neuroendocrine neoplasms (NENs) comprise a group of rare tumors originating from neuroendocrine cells, which are present in both endocrine glands and scattered throughout the body. Due to their scarcity and absence of specific markers, diagnosing NENs remains a complex challenge. Therefore, new biomarkers are required, ideally, in easy-to-obtain blood samples.

METHODS

A panel of blood soluble immune checkpoints (sPD-L1, sPD-L2, sPD-1, sCD25, sTIM3, sLAG3, Galectin-9, sCD27, sB7.2 and sSIGLEC5) and cytokines (IL4, IL6, IP10 and MCP1) was quantified in a cohort of 139 NENs, including 29 pituitary NENs, 46 pheochromocytomas and paragangliomas, and 67 gastroenteropancreatic and pulmonary (GEPP) NENs, as well as in 64 healthy volunteers (HVs). The potential of these circulating immunological parameters to distinguish NENs from HVs, differentiate among various NENs subtypes, and predict their prognosis was evaluated using mathematical regression models. These immunological factors-based models generated scores that were evaluated by Receiver Operating Characteristic (ROC) and Area Under the Curve (AUC) analyses. Correlations between these scores and clinical data were performed. From these analyses, a minimal signature emerged, comprising the five shared immunological factors across the models: sCD25, sPD-L2, sTIM3, sLAG3, and Galectin-9. This refined signature was evaluated, validated, and checked for specificity against non-neuroendocrine tumors, demonstrating its potential as a clinically relevant tool for identifying distinct NENs.

RESULTS

Most of the immunological factors analyzed showed specific expression patterns among different NENs. Scores based on signatures of these factors identified NENs with high efficiency, showing AUCs ranging between 0.948 and 0.993 depending on the comparison, and accuracies between 92.52% and 95.74%. These scores illustrated biological features of NENs including the similarity between pheochromocytomas and paragangliomas, the divergence between gastrointestinal and pulmonary NENs, and correlated with clinical features. Furthermore, the models demonstrated strong performance in distinguishing metastatic and exitus GEPP NENs, achieving sensitivities and specificities ranging from 80.95% to 88.89%. Additionally, an easy-to-implement minimal signature successfully identified all analyzed NENs with AUC values exceeding 0.900, and accuracies between 84.11% and 93.12%, which was internally validated by a discovery and validation randomization strategy. These findings highlight the effectiveness of the models and minimal signature in accurately diagnosing and differentiating NENs.

CONCLUSIONS

The analysis of soluble immunological factors in blood presents a promising liquid biopsy approach for identifying NENs, delivering critical insights for both prognosis and diagnosis. This study serves as a proof-of-concept for an innovative clinical tool that holds the potential to transform the management of these rare malignancies, providing a non-invasive and effective method for early detection and disease monitoring.

Random survival forest algorithm for risk stratification and survival prediction in gastric neuroendocrine neoplasms

This study aimed to construct and assess a machine-learning algorithm designed to forecast survival rates and risk stratification for patients with gastric neuroendocrine neoplasms (gNENs) after diagnosis. Data on patients with gNENs were extracted and randomly divided into training and validation sets using the Surveillance, Epidemiology, and End Results database. We developed a prediction model using 10 machine learning algorithms across 101 combinations to forecast cancer-related mortality in patients with gNENs, selecting the best model using the highest mean over a sequence of time-dependent area under the receiver operating characteristic (ROC) curve (AUC). The performance of the final model was assessed through time-dependent ROC curves for discrimination and calibration curves for calibration. The maximum selection rank method was used to determine the best prognostic risk score threshold for classifying patients into high- and low-risk groups. Afterward, Kaplan-Meier analysis and log-rank test were used to compare survival rates among these groups. Our study examined 775 patients with gNENs, dividing them into training and validation sets. A training set comprised 543 patients, with a median follow-up of 42 months and cumulative mortality rates of 40.0% at 1 year, 48.6% at 3 years, and 54.0% at 5 years. A validation set comprised 232 patients, with cumulative mortality rates of 29.1% at 1 year, 43.5% at 3 years, and 53.2% at 5 years. The optimal random survival forest (RSF) model (mtry = 4, node size = 5) achieved an AUC of 0.839 for survival prediction in the training set. Comprising 11 variables such as demographics, treatment details, tumor characteristics, T staging, N staging, and M staging, the RSF model revealed high predictive accuracy with AUCs of 0.92, 0.96, and 0.96 for 1-, 3-, and 5-year survival, respectively, which was consistently reflected in the validation set with AUCs of 0.88, 0.92, and 0.89, respectively. Moreover, patients were risk-stratified. Although our RSF model effectively stratified patients into different prognostic groups, it needs external validation to confirm its utility for noninvasive prognostic prediction and risk stratification in gNENs. Further research is required to verify its broader clinical applicability.

Correlation between Neurotransmitters (Dopamine, Epinephrine, Norepinephrine, Serotonin), Prognostic Nutritional Index, Glasgow Prognostic Score, Systemic Inflammatory Response Markers, and TNM Staging in a Cohort of Colorectal Neuroendocrine Tumor Patients

Neuroendocrine tumors are uncommon in the gastrointestinal system but can develop in the majority of the body's epithelial organs. Our goal was to examine the presence and clinical application of serum dopamine (DA), serotonin (ST), norepinephrine (NE), and epinephrine (EPI), in addition to determining the significance of the Prognostic Nutritional Index (PNI), Glasgow Prognostic Score (GPS), and systemic inflammatory response (SIR) markers as a prognostic factor for patients with colorectal neuroendocrine tumors (CR-NETs), in various tumor-node-metastasis (TNM) stages. We also wanted to identify the possible connection between them. This study included 25 consecutive patients who were diagnosed with CR-NETs and a control group consisting of 60 patients with newly diagnosed colorectal cancer (CRC). We used the Enzyme-Linked Immunosorbent Assay (ELISA) technique. This study revealed that CR-NET patients showed significantly higher serum levels of DA compared to CRC patients. We showed that serum DA was present in the early stages of CR-NETs, with increasing levels as we advanced through the TNM stages. Moreover, we found a close relationship between the levels of DA and the inflammation and nutritional status of the CR-NET patients in this study. CR-NET patients from the PNI < 47.00 subgroup had a higher level of DA than those from the PNI ≥ 47.00 subgroup. Pearson's correlation analysis revealed correlations between DA, PNI, and the neutrophil/lymphocyte ratio (NLR) and the platelet/lymphocyte ratio (PLR). Both hematological indices were negatively correlated with albumin (ALB). Our investigation's findings relating to the PNI, GPS, SIR, and DA indicate that these tools can be markers of nutritional and systemic inflammatory status, are simple to use, and are repeatable. Further research on this topic could provide valuable insights into which biomarkers to incorporate into clinical practice for the management of CR-NET patients.

The association between Behçet disease activity and elevated systemic immune-inflammation index: A retrospective observational study in a tertiary care hospital

Background The systemic immune-inflammation index (SII) is a novel marker for predicting the prognosis in patients with various diseases and cancers. We aimed to investigate the relationship between SII and disease activity in patients with Behçet disease (BD). Methods Our retrospective study included 513 patients with BD aged ≥18 years. The patients were classified into an active group (n=355) and an inactive group (n=158). Pearson correlation analysis was performed to elucidate correlations between the SII and other markers. Binary logistic regression analysis was used to determine BD-related risk factors. Receiver operating characteristic (ROC) curves were computed to assess cut-offs for the predictive value of the SII and other markers. Results Patients with active BD had a significantly higher SII (p<0.001) than those in the inactive group. ROC analysis revealed that the optimal SII cut-off value to identify BD activity was 526.23, with 70.4% sensitivity and 70.3% specificity. Pearson correlation coefficient (r) demonstrated a significant positive correlation between SII, and the C-reactive protein level (r=0.427, p<0.001), erythrocyte sedimentation rate (r=0.422, p<0.001), platelet- lymphocyte ratio (r=0.711, p<0.001), and neutrophil- lymphocyte ratio (r=0.672, p<0.001). According to binary logistic regression analysis, the SII (odds ratio [OR] 1.003; 95% confidence interval [CI] 1.001-1.004; p=0.002) was an independent risk factor for active BD. Conclusion The SII can be considered a novel predictor of BD activity.

Defining the impact of platelet-to-lymphocyte ratio on patient survival with gastric neuroendocrine neoplasm: a retrospective cohort analysis

Background

Gastric neuroendocrine neoplasm (g-NEN) is a rare but heterogeneous neoplasm, with an increasing incidence yearly. Conventional prognostic markers of g-NEN remain limited which could only be detected after surgery. There is an urgent need to explore new prognostic markers for g-NEN patients. This study aimed to investigate the prognostic value of platelet-to-lymphocyte, ratio (PLR) and the association between PLR and body mass index (BMI) in patients with gastric neuroendocrine neoplasms (g-NEN).

Methods

A retrospective cohort of patients with g-NEN from January 2001 through June 2016 was examined. The prognostic significance of PLR was determined by multiple regression analysis in different models. Stratified analysis was performed to examine the prognostic value of PLR at different BMI levels.

Results

In total, 238 patients were enrolled. Those with higher PLRs tended to undergo open surgery, had larger tumor sizes, were diagnosed more frequently with neuroendocrine carcinoma, and had higher tumor grades. PLR was significantly associated with the survival of patients with g-NEN. With PLR increased per standard deviation, the all-cause mortality risk of patients with g-NEN increased by 67%, 63%, and 54% in the crude (HR = 1.67, 95% CI 1.32–2.12, P < 0.001), minimally adjusted (HR = 1.63, 95% CI 1.28–2.08, P < 0.001), and fully adjusted (HR = 1.54, 95% CI 1.202–1.98, P = 0.001) models, respectively. Patients with higher PLR (quartile 4, ≥ 187) had a 1.8-fold increase in all-cause mortality risk compared with those with lower PLR (quartile 1–3, < 187). Furthermore, there was a significant interaction effect between BMI subgroups and PLR in predicting the survival of patients with g-NEN (PLR regarded as a continuous variable: all P for interaction < 0.05 in the crude, minimally adjusted, and fully adjusted models; PLR regarded as a categorical variable: P for interaction < 0.05 in the fully adjusted model). Patients with g-NEN with the characteristics of higher PLR (quartile 4, ≥ 187) and non-obesity (BMI < 25 kg/m2) had worse survival than others (P < 0.05).

Conclusion

The inflammation marker PLR has an independent prognostic value for patients with g-NENs, and high PLR combined with non-obesity increases the mortality risk of these patients.

Radical Resection in Entero-Pancreatic Neuroendocrine Tumors: Recurrence-Free Survival Rate and Definition of a Risk Score for Recurrence

BACKGROUND

Surgery with radical intent is the only potentially curative option for entero-pancreatic neuroendocrine tumors (EP-NETs) but many patients develop recurrence even after many years. The subset of patients at high risk of disease recurrence has not been clearly defined to date.

OBJECTIVE

The aim of this retrospective study was to define, in a series of completely resected EP-NETs, the recurrence-free survival (RFS) rate and a risk score for disease recurrence.

PATIENTS AND METHODS

This was a multicenter retrospective analysis of sporadic pancreatic NETs (PanNETs) or small intestine NETs (SiNETs) [G1/G2] that underwent R0/R1 surgery (years 2000-2016) with at least a 24-month follow-up. Survival analysis was performed using the Kaplan-Meier method and risk factor analysis was performed using the Cox regression model.

RESULTS

Overall, 441 patients (224 PanNETs and 217 SiNETs) were included, with a median Ki67 of 2% in tumor tissue and 8.2% stage IV disease. Median RFS was 101 months (5-year rate 67.9%). The derived prognostic score defined by multivariable analysis included prognostic parameters, such as TNM stage, lymph node ratio, margin status, and grading. The score distinguished three risk categories with a significantly different RFS (p < 0.01).

CONCLUSIONS

Approximately 30% of patients with EP-NETs recurred within 5 years after radical surgery. Risk factors for recurrence were disease stage, lymph node ratio, margin status, and grading. The definition of risk categories may help in selecting patients who might benefit from adjuvant treatments and more intensive follow-up programs.

Inflammation-scores as prognostic markers of overall survival in lung cancer: a register-based study of 6,210 Danish lung cancer patients

Background

Inflammation-scores based on general inflammation markers are suggested as prognostic markers of overall survival (OS) in lung cancer. However, whether these inflammation-scores improves the prognostication performed by well-established prognostic markers is unsettled. In a large register-based lung cancer patient cohort, nine different inflammation-scores were compared, and their ability to optimize the prognostication of OS was evaluated.

Methods

Lung cancer patients diagnosed from 2009–2018 in The Central Denmark Region were identified in the Danish Lung Cancer Registry. Pre-treatment inflammation markers were extracted from the clinical laboratory information system. Prognostication of OS was evaluated by Cox proportional hazard models. Comparison of the inflammation-scores and their added value to established prognostic markers were assessed by Akaike's information criteria and Harrel's C-index.

Results

In total, 5,320 patients with non-small cell lung cancer (NSCLC) and 890 patients with small cell lung cancer (SCLC) were identified. In NSCLC, the Aarhus composite biomarker score (ACBS), including albumin, C-reactive protein, neutrophil count, lymphocyte count and haemoglobin, and the neutrophil-lymphocyte-ratio (NLR) were superior. Furthermore, they improved the prognostication of OS significantly (p <0.0001) (ACBS: HR: 2.24 (95%CI: 1.97–2.54); NLR: HR: 1.58 (95%CI: 1.47 – 1.69)). In SCLC, three scores were equally superior and improved the prognostication of OS p < 0.0001): neutrophil–lymphocyte-ratio (HR:1.62 (95%CI: 1.38–1.90)), modified Glasgow Prognostic Score (mGPS) (HR:1.70 (95%CI: 1.55–1.86) and the Combined NLR and GPS (CNG) (HR:2.10 (95%CI: 1.77–2.49).

Conclusions

The ACBS was the optimal score in NSCLC, whereas neutrophil–lymphocyte-ratio, mGPS and CNG were equally superior in SCLC. Additionally, these inflammation-scores all optimised the prognostication of OS and added value to well-established prognostic markers.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12885-021-09108-5.

NETest: A Systematic Review Focusing on the Prognostic and Predictive Role

The NETest is a standardized and reproducible liquid biopsy for neuroendocrine tumors (NETs). It evaluates the expression of 51 NET genes by real-time polymerase chain reaction, providing an accurate molecular profile of the neoplasm. Diagnostic utility of NETest has been widely demonstrated, while its role in predicting prognosis and treatment response is less studied. This systematic review aims to collect and discuss the available evidence on the prognostic and predictive role of NETest, trying to answer 3 questions, frequently raised in clinical practice. Is NETest able to differentiate stable from progressive disease? Increased NETest levels (at least >40%) correlate with disease progression. Is NETest able to predict tumor progression and tumor response to treatment? Some studies demonstrated that the baseline NETest score >33-40% could predict tumor progression. Moreover, NETest performed after treatment (as peptide receptor radionuclide therapy) could predict treatment response also before radiological findings, since the decrease or stability of NETest score predicts tumor response to treatment. Is NETest able to evaluate tumor recurrence risk after surgery? NETest can predict surgical treatment outcome detecting minimal residual disease after radical surgery, which is characterized by a lower but positive NETest score (20-40%), while a higher score (>33-40%) is associated with nonradical surgery. In conclusion, in addition to its demonstrated diagnostic role, this systematic review highlights the efficacy of NETest to assess disease status at the moment of the NETest execution and to predict tumor recurrence after surgery. The efficacy for other applications should be proven by additional studies.

Perspectives on the diagnostic, predictive and prognostic markers of neuroendocrine neoplasms (Review)

Neuroendocrine neoplasms (NENs) are a heterogeneous group of rare tumors with different types of physiology and prognosis. Therefore, prognostic information, including morphological differentiation, grade, tumor stage and primary location, are invaluable and contribute to the formulation of treatment decisions. Biomarkers that are currently used, including chromogranin A (CgA), serotonin and neuron-specific enolase, are singular parameters that cannot be used to accurately predict variables associated with tumor growth, including proliferation, metabolic rate and metastatic potential. In addition, site-specific biomarkers, such as insulin and gastrin, cannot be applied to all types of NENs. The clinical application of broad-spectrum markers, as it is the case for CgA, remains controversial despite being widely used. Due to limitations of the currently available mono-analyte biomarkers, recent studies were conducted to explore novel parameters for NEN diagnosis, prognosis, therapy stratification and evaluation of treatment response. Identification of prognostic factors for predicting NEN outcome is a critical requirement for the planning of adequate clinical management. Advances in ‘liquid’ biopsies and genomic analysis techniques, including microRNA, circulating tumor DNA or circulating tumor cells and sophisticated biomathematical analysis techniques, such as NETest or molecular image-based biomarkers, are currently under investigation as potentially novel tools for the management of NENs in the future. Despite these recent findings yielding promising observations, further research is necessary. The present review therefore summarizes the existing knowledge and recent advancements in the exploration of biochemical markers for NENs, with focus on gastroenteropancreatic-neuroendocrine tumors.

Serum Inflammation-based Scores in Endocrine Tumors

CONTEXT

Serum inflammation-based scores reflect systemic inflammatory response and/or patients' nutritional status, and may predict clinical outcomes in cancer. While these are well-described and increasingly used in different cancers, their clinical usefulness in the management of patients with endocrine tumors is less known.

EVIDENCE ACQUISITION

A comprehensive PubMed search was performed using the terms "endocrine tumor," "inflammation," "serum inflammation-based score," "inflammatory-based score," "inflammatory response-related scoring," "systemic inflammatory response markers," "neutrophil-to-lymphocyte ratio," "neutrophil-to-platelet ratio," "lymphocyte-to-monocyte ratio," "Glasgow prognostic score," "neutrophil-platelet score," "Systemic Immune-Inflammation Index," and "Prognostic Nutrition Index" in clinical studies.

EVIDENCE SYNTHESIS

The neutrophil-to-lymphocyte ratio and the platelet-to-lymphocyte ratio are the ones most extensively investigated in patients with endocrine tumors. Other scores have also been considered in some studies. Several studies focused in finding whether serum inflammatory biomarkers may stratify the endocrine tumor patients' risk and detect those at risk for developing more aggressive and/or refractory disease, particularly after endocrine surgery.

CONCLUSIONS

In this review, we summarize the current knowledge on the different serum inflammation-based scores and their usefulness in predicting the phenotype, clinical aggressiveness, and disease outcomes and prognosis in patients with endocrine tumors. The value of such serum inflammation-based scores in the management of patients with endocrine tumors has been emerging over the last decade. However, further research is necessary to establish useful markers and their cut-offs for routine clinical practice for individual diseases.

The Correlation of the Neutrophil-Lymphocyte Ratio and the Platelet-Lymphocyte Ratio With Pathological Findings in Neuroendocrine Tumors

Introduction The relationship between clinical prognostic factors and blood neutrophil-lymphocyte ratio (NLR) and platelet-lymphocyte ratio (PLR) in some tumors has been investigated. In this study, we examined whether there is a relationship between pathological prognostic factors and NLR as well as PLR only in neuroendocrine tumors (NETs). Methods A total of 115 patients with a NET diagnosis between 2014-2020 were included in the study. The efficiency of NLR and PLR in predicting distant metastases was determined by analyzing the receiver operating characteristic (ROC) curve. The relationship between histopathological parameters was also compared. Results The cut-off value of NLR was 3.01 for predicting distant metastasis. At this value, the specificity was 73.7%, the sensitivity was 70.7%, and the likelihood ratio was 2.51. There was a significant relationship between NLR and tumor localization, histological grade, mitosis, Ki-67, distant metastasis, and lymphovascular invasion (all p<0.001). The cut-off value of the PLR in predicting distant metastasis was 134.4. At this value, the specificity was 59.6%, the sensitivity was 58.6%, and the likelihood ratio was 1.44. There was no significant relationship between PLR and the histopathological findings (all p>0.05). Conclusions In our study, a high histological grade, high mitosis, a high Ki-67 proliferation index, distant metastasis, and lymphovascular invasion were found in patients with NLR at a cut-off value above 3.01. However, we could not attain the same results for PLR. For trucut and endoscopic biopsies in particular, follow-up of patients with grades 1 and 2 NETs along with histopathological findings and evaluation of NLR in peripheral blood may be useful. NLR, which is an easily accessible inflammatory marker, can be used as an independent predictive factor in NETs.

Are Markers of Systemic Inflammatory Response Useful in the Management of Patients With Neuroendocrine Neoplasms?

Given the increasing incidence of neuroendocrine neoplasms (NENs) over the past few decades, a more comprehensive knowledge of their pathophysiological bases and the identification of innovative NEN biomarkers represents an urgent unmet need. There is still little advance in the early diagnosis and management of these tumors, due to the lack of sensible and specific markers with prognostic value and ability to early detect the response to treatment. Chronic systemic inflammation is a predisposing factor for multiple cancer hallmarks, as cancer proliferation, progression and immune-evading. Therefore, the relevance of inflammatory biomarkers has been identified as critical in several types of tumours, including NENs. A bidirectional relationship between chronic inflammation and development of NENs has been reported. Neuroendocrine cells can be over-stimulated by chronic inflammation, leading to hyperplasia and neoplastic transformation. As the modulation of inflammatory response represents a therapeutic target, inflammatory markers could represent a promising new key tool to be applied in the diagnosis, the prediction of response to treatment and also as prognostic biomarkers in NENs field. The present review provides an overview of the pre-clinical and clinical data relating the potentially usefulness of circulating inflammatory markers: neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), cytokines and tissue inflammatory markers (PD-1/PD-L1), in the management of NENs. (1) NLR and PLR have both demonstrated to be promising and simple to acquire biomarkers in patients with advanced cancer, including NEN. To date, in the context of NENs, the prognostic role of NLR and PLR has been confirmed in 15 and 4 studies, respectively. However, the threshold value, both for NLR and PLR, still remains not defined. (2) Cytokines seem to play a central role in NENs tumorigenesis. In particular, IL-8 levels seems to be a good predictive marker of response to anti-angiogenic treatments. (3) PD-1 and PD-L1 expression on tumour cells and on TILs, have demonstrated to be promising predictive and prognostic biomarkers in NENs. Unfortunately, these two markers have not been validated so far and further studies are needed to establish their indications and utility.

Exploration of gastric neuroendocrine carcinoma (GNEC) specific signaling pathways involved in chemoresistance via transcriptome and in vitro analysis

Gastric neuroendocrine carcinoma (GNEC) is rare cancer detected in the stomach. Previously, we demonstrated that the poorer prognosis of GNEC patients compared with gastric adenocarcinoma (GAC) patients was probably due to the lack of response to chemotherapy. Thus, it is crucial to study the specific GNEC gene expression pattern and investigate chemoresistance mechanism of GNEC. The transcriptome of GNEC patients was compared with that of GAC patients using RNA-seq. The KEGG analysis was employed to explore the specific differential expression gene function enrichment pattern. In addition, the transcriptomes of two GNEC cell lines, ECC10 and ECC12, were also compared with those of two GAC cell lines, MGC-803 and AGS, using RNA-seq. Comparing patient samples and cell lines transcriptome data, we try to uncover the potential targets and pathways which may affect the chemoresistance of GNEC. By combing all transcriptome data, we identified 22 key genes that were specifically up-regulated in GNEC. This panel of genes probably involves in the chemoresistance of GNEC. From our current experimental data, NeuroD1, one of the 22 genes, is associated with the prognosis of GNEC patients. Knockdown of NeuroD1 enhanced the sensitivity to irinotecan of GNEC cell lines. Our research sheds light in identifying a panel of novel therapeutic target specifically for GNEC clinical treatment which has not been reported before.

Stage predictivity of neutrophil/lymphocyte and platelet/lymphocyte ratios in pancreatic neuroendocrine tumors

Objectives

This study aimed to analyze the correlations between European Neuroendocrine Tumor Society (ENEST), Tumor Node Metastasis (TNM) staging systems and pre-operative neutrophil/lymphocyte (NLR) and platelet/lymphocyte ratios (PLR) in patients with pancreatic neuroendocrine tumor (PNET).

Material and Methods

Forty-four patients with diagnosed PNET were analyzed retrospectively. Accordingly, the patients' blood and clinicopathological parameters were analyzed. The correlations between laboratory parameters and tumor stages were evaluated using Eta correlation analysis. The control group was composed of volunteering healthy participants who had similarities with our study group as regards age and gender.

Results

According to ENETS classification, 34% of the patients were stage I, 25% were stage II, 20.4% were stage III and 20.4% were stage IV. NLR and PLR mean values were 2.4 and 127, respectively. NLR values of the patients in the study group were higher than those of the control group (p= 0.001). NLR and PLR values of stage I, II, III and IV patients tended to increase in parallel to the higher stages according to ENETS system (p= 0.0001 and p= 0.0001, respectively). Similarly, NLR and PLR values increased in parallel to the higher stages according to TNM system (p= 0.0001 and p= 0.0001, respectively). In addition, NLR values were found to be higher in patients with lymph node metastasis than in those without (p= 0.001).

Conclusion

Increased levels of inflammatory mediators such as NLR and PLR are associated with advanced stages of patients with PNET.

Gastroenteropancreatic neuroendocrine neoplasms and inflammation: A complex cross-talk with relevant clinical implications

Neuroendocrine neoplasms (NENs) are a group of tumors originating from the neuroendocrine system. They mainly occur in the digestive system and the respiratory tract. It is well-know a strict interaction between neuroendocrine system and inflammation, which can play an important role in NEN carcinogenesis. Inflammatory mediators, which are produced by the tumor microenvironment, can favor cancer induction and progression, and can promote immune editing. On the other hand, a balanced immune system represents a relevant step in cancer prevention through the elimination of dysplastic and cancer cells. Therefore, an inflammatory response may be both pro- and anti-tumorigenic. In this review, we provide an overview concerning the complex interplay between inflammation and gastroenteropancreatic NENs, focusing on the tumorigenesis and clinical implications in these tumors.

A novel and validated nomogram to predict overall survival for gastric neuroendocrine neoplasms

BACKGROUND

This study aims to develop and validate an effective nomogram to estimate the individual outcome of patients with Gastric neuroendocrine neoplasms (G-NENs).

METHODS

A total of 260 patients diagnosed with G-NENs at two medical centers were included, with 156 patients allocated as training set and 104 patients as validation. Predictive nomogram was constructed based on multivariate analyses using RMS package in R version. The predictive accuracy and discriminative ability were analyzed by C-index, risk group stratification and calibration curve, which was compared with other predictive systems for G-NENs.

RESULTS

In multivariate analysis, age, Ki-67, mitoses, neutrophil to lymphocyte ratio, serum tumor marker and distant metastasis were significantly associated with overall survival. The constructed prognostic nomogram demonstrated a good calibration and discrimination value with 0.884 and 0.852 C-indices in training and validation dataset. Compare to World Health Organization (WHO) grading system (C-indices=0.760 and 0.732) and American Joint Committee on Cancer (AJCC) tumor-node-metastasis (TNM) staging system (C-indices=0.747 and 0.811), the nomogram displayed a better predictive accuracy.

CONCLUSIONS

The novel prognostic nomogram showed superior predictive value in overall survival of G-NENs. It might be a useful tool for clinicians in estimating individual survival in G-NENs patients.

Pretreatment hematologic markers as prognostic predictors of gastroenteropancreatic neuroendocrine tumors: a systematic review and meta-analysis

Background

Systemic inflammation can be reflected by peripheral hematologic parameters and combined index like the lymphocyte count, neutrophil count, platelet count, neutrophil-to-lymphocyte (NLR), and platelet-to-lymphocyte ratio (PLR). This systematic review and meta-analysis aimed to summarize the association between the hematologic markers and prognosis of gastroenteropancreatic neuroendocrine tumors (GEP–NETs).

Methods

A computerized systematic search of PubMed, Embase, and Web of Science was conducted up to August 2016. Studies evaluating prognosis value of hematologic parameters in patients with GEP–NETs were retrieved. For meta-analysis, hazard ratios (HRs) with 95% confidence intervals (95% CIs) were extracted and synthesized using Review Manager software.

Results

We identified eight retrospective cohort studies comprising a total of 724 cases. The majority of included studies focused on pancreatic neuroendocrine tumors (PNETs). The prognostic values of NLR, PLR, and platelet count were reported in six studies, two studies, and one study, respectively. All the parameters were associated with prognostic outcomes in patients with GEP–NETs. A high NLR was significantly associated with poor prognosis in GEP–NETs (pooled HR 3.05, 95% CI 1.96–4.76, I² = 0%, P < 0.00001 for overall survival (OS); pooled HR 3.30, 95% CI 2.04–5.32, I² = 0%, P < 0.00001 for recurrence-free survival [RFS]). In PNETs, pooled-analyses also showed significant superiority of a low NLR on OS (pooled HR 4.21, 95% CI 1.95–9.13, I² = 0%, P = 0.0003) and RFS (pooled HR 5.37, 95% CI 2.14–13.47, I² = 0%, P = 0.003).

Conclusions

These findings suggest that the elevated NLR could be an adverse prognosis factor for GEP–NETs. The conclusion should be mainly limited to PNETs as the majority of included cases were PNET patients. The prognostic value of other hematologic parameters deserves further investigation. We recommend that further studies should use a continuous NLR variable and adopt a prospective and matched study design.

Nomogram predicting the risk of recurrence after curative-intent resection of primary non-metastatic gastrointestinal neuroendocrine tumors: An analysis of the U.S. Neuroendocrine Tumor Study Group

BACKGROUND

The risk of recurrence after resection of non-metastatic gastro-entero-pancreatic neuroendocrine tumors (GEP-NET) is poorly defined. We developed/validated a nomogram to predict risk of recurrence after curative-intent resection.

METHODS

A training set to develop the nomogram and test set for validation were identified. The predictive ability of the nomogram was assessed using c-indices.

RESULTS

Among 1477 patients, 673 (46%) were included in the training set and 804 (54%) in y the test set. On multivariable analysis, Ki-67, tumor size, nodal status, and invasion of adjacent organs were independent predictors of DFS. The risk of death increased by 8% for each percentage increase in the Ki-67 index (HR 1.08, 95% CI, 1.05-1.10; P < 0.001). GEP-NET invading adjacent organs had a HR of 1.65 (95% CI, 1.03-2.65; P = 0.038), similar to tumors ≥3 cm (HR 1.67, 95% CI, 1.11-2.51; P = 0.014). Patients with 1-3 positive nodes and patients with >3 positive nodes had a HR of 1.81 (95% CI, 1.12-2.87; P = 0.014) and 2.51 (95% CI, 1.50-4.24; P < 0.001), respectively. The nomogram demonstrated good ability to predict risk of recurrence (c-index: training set, 0.739; test set, 0.718).

CONCLUSION

The nomogram was able to predict the risk of recurrence and can be easily applied in the clinical setting.

Prognostic Significance of Preoperative Neutrophil-to-Lymphocyte Ratio in Surgically Resectable Pancreatic Neuroendocrine Tumors

Background

The aim of this study was to evaluate the predictive and prognostic value of the preoperative neutrophil-to-lymphocyte ratio (NLR) and platelet-to-lymphocyte ratio (PLR) in pancreatic neuroendocrine tumor (PNET) patients undergoing potentially curative resection.

Material/Methods

A retrospective review of 172 patients with PNETs was conducted. Kaplan-Meier curves and multivariate Cox proportional models were used to calculate overall survival (OS) and disease-free survival (DFS). The predictive performance of the NLR was compared with other inflammation-based scores and conventional stratification systems using receiver operating characteristic (ROC) curve analysis.

Results

Elevated NLR and PLR were both associated with advanced AJCC stage and high grade. In the univariate analysis, elevated NLR and PLR were both significantly associated with decreased OS and DFS. In the multivariate analysis, the preoperative NLR, but not the PLR, was an independent risk factor for OS (HR=4.471, 95% CI 1.531–13.054, p=0.006) and DFS (HR=2.531, 95% CI 1.202–5.329, p=0.015). The discriminatory capability of the NLR was superior to that of other inflammation-based scores in OS prediction. Furthermore, the predictive range was expanded by incorporating the NLR into the conventional stratification systems, including the AJCC stage and WHO classification systems.

Conclusions

As an independent prognostic factor, an elevated preoperative NLR is superior to the PLR with respect to predicting clinical outcomes in PNET patients undergoing potentially curative resection. The incorporation of the NLR into the existing conventional stratification systems improved the predictive accuracy.

Development and validation of a prognostic nomogram for IgA nephropathy

IgA nephropathy (IgAN) shows strong heterogeneity between individuals. IgAN prognosis is associated with pathological lesions and clinical indicators. However, simple tools for evaluating the clinical prognosis remain inadequate. Our objective was to develop an intuitive estimation tool for predicting the IgAN prognosis. 349 patients with IgAN at The Chinese People’s Liberation Army General Hospital were retrospectively analyzed from data between 2000 and 2006. A nomogram was developed using COX regression coefficients to predict decline of estimate Glomerular filtration rate (eGFR) ≥ 50% and end-stage renal disease (ESRD). The discriminative ability and predictive accuracy of the nomogram was determined via concordance index (C-index) and calibration curve. The results were verified in an independent validation cohort. In the derivation cohort, the nomogram was developed using mesangial hypercellularity, tubular atrophy/interstitial fibrosis, average proteinuria (A-P), and average mean arterial pressure (A-MAP) during hospitalization. The C-index of the nomogram was 0.88 (95% CI, 0.80 to 0.96). The calibration curve showed good agreement between prediction and actual observation. Furthermore, the nomogram demonstrated good discrimination (C-index = 0.87, 95% CI 0.78 to 0.95) and calibration in the validation cohort. The nomogram could predict the prognosis of IgAN effectively and intuitively.

Nomogram individually predicts the overall survival of patients with gastroenteropancreatic neuroendocrine neoplasms

Background:

The current study aimed to establish a novel nomogram to predict the overall survival of individual Chinese patients with gastroenteropancreatic neuroendocrine neoplasms (GEP-NENs). Furthermore, this study sought to externally validate this nomogram using the Surveillance, Epidemiology, and End Results (SEER) database.

Methods:

The records of 1183 patients with GEP-NENs treated at five high-capacity institutions in China between 2005 and 2015 were retrospectively analysed. In addition, 10 236 GEP-NEN cases from the SEER database were included as an external validation set.

Results:

A multivariate analysis using Cox proportional hazards (PHs) regression was performed, and a nomogram was constructed. Discrimination, calibration, and external validation were performed using the SEER data set. The multivariate Cox model indicated that age, tumour size, differentiation, lymph node metastases, and distant metastases were independent covariates associated with survival. With respect to the training set, the nomogram exhibited better discrimination power than TNM classification (Harrell’s concordance index (C-index): 0.837 vs 0.784, P=0.006). Discrimination was also excellent and superior to that of TNM classification for the SEER-based validation set (C-index: 0.808 vs 0.717, P<0.001). The calibrated nomogram predicted a survival rate that closely corresponded to the actual survival rate.

Conclusions:

We developed a nomogram that predicted the 3- and 5-year overall survival rates of patients with GEP-NENs. Validation revealed excellent discrimination and calibration for this nomogram, suggesting that it exhibits satisfactory clinical utility that might improve individualised predictions of survival risks and lead to the creation of additional clinical therapies.

Does neutrophil-to-lymphocyte ratio predict 1-year mortality in patients with primary biliary cholangitis? Results from a retrospective study with validation cohort

OBJECTIVES

Neutrophil-to-lymphocyte ratio (NLR) has been used to predict prognosis in various liver diseases, but its role in primary biliary cholangitis (PBC) is not clarified. We aimed to investigate the prognostic usefulness of NLR for 1-year mortality in PBC.

METHODS

The study recruited a retrospective cohort with 88 patients with PBC and a prospective validation cohort with 63 participants who were followed-up for 1 year. NLR and other laboratory measurements were analysed by multivariate regression model for identifying independent factors for early mortality. The cut-off threshold of NLR was determined by calculating the area under the receiver operating characteristics curve (AUROC) and used in a subsequent Kaplan-Meier survival analysis.

RESULTS

Univariate and multivariate analyses showed that Mayo Risk Score (MRS), serum creatinine and NLR were independent indicators for mortality. NLR yielded significantly higher AUROC (0.86) than those of platelet-to-lymphocyte ratio (0.58, p=0.03), but comparable with MRS (0.87, p=0.88). Spearman's correlation analysis represented a positive correlation between escalating NLR and aggravating Child-Pugh grade (r=0.44, p<0.001). Patients with NLR <2.18 exhibited higher survival (with 100% sensitivity and 67.1% specificity) within 1 year follow-up duration, and NLR ≥2.18 was indicative of higher mortality (log-rank test, p<0.001). In addition, these results were internally confirmed by a validation cohort.

CONCLUSION

NLR is closely related to short-term mortality in patients with PBC.

Prognostic value of neutrophil-to-lymphocyte ratio for nasopharyngeal carcinoma: A meta-analysis

BACKGROUND

The prognostic value of the neutrophil-to-lymphocyte ratio (NLR) for nasopharyngeal carcinoma (NPC) remains controversial. This study was designed to provide a more accurate assessment of the prognostic value, based on a meta-analysis.

METHODS

A comprehensive search for relevant studies published before June 2016 was performed using the PubMed, Cochrane Library, and Web of Science databases. The correlations of NLR with overall survival (OS) and progression-free survival (PFS) were evaluated for NPC. Hazard ratios (HRs) and associated 95% confidence intervals (CIs) were calculated to estimate the effects.

RESULTS

Six studies with a total of 4359 NPC patients were included in this meta-analysis. The pooled results showed that, among patients with NPC, elevated pretreatment NLR was associated with poorer OS (HR = 1.74, 95% CI = 1.45-2.10) and PFS (HR = 1.48, 95% CI = 1.30-1.69). Subgroup analyses indicated that the use of different cut-off values for NLR (<3 or ≥3) did not affect the consistent prognostic value of NLR for OS or PFS. No significant heterogeneity or publication bias was observed among the included studies for OS or PFS (P > .05).

CONCLUSIONS

This meta-analysis indicates that elevated pretreatment NLR might be a valuable predicative biomarker of poor prognosis for patients with NPC.

Circulating tumor cells and miRNAs as prognostic markers in neuroendocrine neoplasms

The prognosis of neuroendocrine neoplasms (NENs) is widely variable and has been shown to associate with several tissue- and blood-based biomarkers in different settings. The identification of prognostic factors predicting NEN outcome is of paramount importance to select the best clinical management for these patients. Prognostic markers have been intensively investigated, also taking advantage of the most modern techniques, in the perspective of personalized medicine and appropriate resource utilization. This review summarizes the available data on the possible role of circulating tumor cells and microRNAs as prognostic markers in NENs.

Association of neutrophil-lymphocyte ratio and T lymphocytes with the pathogenesis and progression of HBV-associated primary liver cancer

Background

The neutrophil–lymphocyte ratio (NLR) is a new prognostic predictor for patients with liver cancer. The association of NLR and T lymphocytes with the pathogenesis and progression of liver cancer is poorly understood.

Methods

Seventy-three patients with hepatitis B virus (HBV)-associated primary liver cancer (HBV-PLC), 50 patients with HBV-associated liver cirrhosis (HBV-LC) and 37 patients with chronic HBV infection (CHB) were prospectively enrolled from July 1, 2013 to February 28, 2014 in Beijing Ditan Hospital, Capital Medical University (Beijing, China). The NLR, proportions and concentrations of neutrophils and lymphocytes, concentration of subpopulations of lymphocytes, and the expression of CD31 (index for recent thymic output) and HLA-DR (index for activation of T lymphocytes) of T cells in the peripheral blood samples of the patients were assessed and statistically compared between different groups.

Results

The NLR was significantly increased from patients with CHB, those with HBV-LC to those with HBV-PLC (P<0.05), along with significant increase of neutrophils and decrease of lymphocytes in the same way (P<0.05). The concentrations of T lymphocytes, natural killer cells, B cells, CD4⁺ T cells and CD8⁺ T cells were decreased from patients with CHB, those with HBV-LC to those with HBV-PLC, and were significantly reduced in patients with HBV-PLC compared with those in patients with CHB (P<0.05). The CD31 and HLA-DR expression of naive CD4⁺ and CD8⁺ T cells was significantly decreased and increased, respectively in patients with HBV-PLC compared with that in patients with CHB.

Conclusions

Elevated NLR, resulted from the increase of neutrophils and decrease of lymphocytes, is positively associated with the pathogenesis and progression of HBV-PLC. The reduced thymic output and hyperactivation of T lymphocytes may contribute to the decrease of T lymphocytes, which could be also related to the pathogenesis of HBV-PLC.