Significance of combined preoperative serum Alb and dNLR for diagnosis of pancreatic cancer

Unlocking the complete blood count as a risk stratification tool for breast cancer using machine learning: a large scale retrospective study

Optimizing early breast cancer (BC) detection requires effective risk assessment tools. This retrospective study from Brazil showcases the efficacy of machine learning in discerning complex patterns within routine blood tests, presenting a globally accessible and cost-effective approach for risk evaluation. We analyzed complete blood count (CBC) tests from 396,848 women aged 40-70, who underwent breast imaging or biopsies within six months after their CBC test. Of these, 2861 (0.72%) were identified as cases: 1882 with BC confirmed by anatomopathological tests, and 979 with highly suspicious imaging (BI-RADS 5). The remaining 393,987 participants (99.28%), with BI-RADS 1 or 2 results, were classified as controls. The database was divided into modeling (including training and validation) and testing sets based on diagnostic certainty. The testing set comprised cases confirmed by anatomopathology and controls cancer-free for 4.5-6.5 years post-CBC. Our ridge regression model, incorporating neutrophil-lymphocyte ratio, red blood cells, and age, achieved an AUC of 0.64 (95% CI 0.64-0.65). We also demonstrate that these results are slightly better than those from a boosting machine learning model, LightGBM, plus having the benefit of being fully interpretable. Using the probabilistic output from this model, we divided the study population into four risk groups: high, moderate, average, and low risk, which obtained relative ratios of BC of 1.99, 1.32, 1.02, and 0.42, respectively. The aim of this stratification was to streamline prioritization, potentially improving the early detection of breast cancer, particularly in resource-limited environments. As a risk stratification tool, this model offers the potential for personalized breast cancer screening by prioritizing women based on their individual risk, thereby indicating a shift from a broad population strategy.

Inflammatory biomarkers and nanotechnology: new insights in pancreatic cancer early detection

BACKGROUND

Poor prognosis of pancreatic ductal adenocarcinoma (PDAC) is mainly due to the lack of effective early-stage detection strategies. Even though the link between inflammation and PDAC has been demonstrated and inflammatory biomarkers proved their efficacy in predicting several tumours, to date they have a role only in assessing PDAC prognosis. Recently, the studies of interactions between nanosystems and easily collectable biological fluids, alone or coupled with standard laboratory tests, have proven useful in facilitating PDAC diagnosis. Notably, tests based on magnetic levitation (MagLev) of biocoronated nanosystems have demonstrated high diagnostic accuracy in compliance with the criteria stated by WHO. Herein, the author developed a synergistic analysis that combines a user-friendly MagLev-based approach and common inflammatory biomarkers for discriminating PDAC subjects from healthy ones.

MATERIALS AND METHODS

Plasma samples from 24 PDAC subjects and 22 non-oncological patients have been collected and let to interact with graphene oxide nanosheets.Biomolecular corona formed around graphene oxide nanosheets have been immersed in a Maglev platform to study the levitation profiles.Inflammatory biomarkers such as neutrophil-to-lymphocyte ratio (NLR), derived-NLR (dNLR), and platelet to lymphocyte ratio have been calculated and combined with results obtained by the MagLev platform.

RESULTS

MagLev profiles resulted significantly different between non-oncological patients and PDAC and allowed to identify a MagLev fingerprint for PDAC. Four inflammatory markers were significantly higher in PDAC subjects: neutrophils ( P =0.04), NLR ( P =4.7 ×10 -6 ), dNLR ( P =2.7 ×10 -5 ), and platelet to lymphocyte ratio ( P =0.002). Lymphocytes were appreciably lower in PDACs ( P =2.6 ×10 -6 ).Combining the MagLev fingerprint with dNLR and NLR returned global discrimination accuracy for PDAC of 95.7% and 91.3%, respectively.

CONCLUSIONS

The multiplexed approach discriminated PDAC patients from healthy volunteers in up to 95% of cases. If further confirmed in larger-cohort studies, this approach may be used for PDAC detection.

Diagnostic value of combining preoperative inflammatory markers ratios with CA199 for patients with early-stage pancreatic cancer

BACKGROUND

An early diagnosis of pancreatic cancer (PC) is extremely difficult because of the lack of sensitive liquid biopsy methods and effective biomarkers. We attempted to evaluate whether circulating inflammatory marker could complement CA199 for the detection of early-stage PC.

METHODS

We enrolled 430 patients with early-stage PC, 287 patients with other pancreatic tumors (OPT), and 401 healthy controls (HC). The patients and HC were randomly divided into a training set (n = 872) and two testing sets (n₁ = 218, n₂ = 28). The receiver operating characteristic (ROC) curves were investigated to evaluate the diagnostic performance of circulating inflammatory markers ratios, CA199, and combinations of the markers ratios in the training set, which would then be validated in the two testing sets.

RESULTS

Circulating fibrinogen, neutrophils, and monocytes in patients with PC were significantly higher while circulating albumin, prealbumin, lymphocytes, and platelets of patients with PC were significantly lower compared to those of HC and OPT (all P < 0.05). The fibrinogen-to-albumin (FAR), fibrinogen-to-prealbumin (FPR), neutrophil-to-lymphocyte (NLR), platelet-to-lymphocyte (PLR), monocyte-to-lymphocyte (MLR), and fibrinogen-to-lymphocyte (FLR) ratios were significantly higher while the prognostic nutrition index values (PNI) were lower in patients with PC than in HC and OPT (all P < 0.05). Combining the FAR, FPR, and FLR with CA199 exhibited the best diagnostic value for distinguishing patients with early-stage PC from HC with an area under the curve (AUC) of 0.964, and for distinguishing patients with early-stage PC from OPT with an AUC of 0.924 in the training sets. In the testing set, compared with HC, the combination markers had powerful efficiency for PC with an AUC 0.947 and AUC 0.942 when comparing PC with OPT. The AUC was 0.915 for the combination of CA199, FAR, FPR, and FLR for differentiating between patients with pancreatic head cancer (PHC) and other pancreatic head tumors (OPHT), and 0.894 for differentiating between patients with pancreatic body and tail cancer (PBTC) and other pancreatic body and tail tumors (OPBTT).

CONCLUSION

A combination of FAR, FPR, FLR, and CA199 may serve as a potential non-invasive biomarker for differentiating early-stage PC from HC and OPT, especially early-stage PHC.

A novel preoperative inflammation score system established for postoperative prognosis predicting of intrahepatic cholangiocarcinoma

BACKGROUND

Inflammation is implicated in tumorigenesis and has been reported as an important prognostic factor in cancers. In this study, we aimed to develop and validate a novel inflammation score (IFS) system based on 12 inflammatory markers and explore its impact on intrahepatic cholangiocarcinoma (ICC) survival after hepatectomy.

METHODS

Clinical data of 446 ICC patients undergoing surgical treatment were collected from the Primary Liver Cancer Big Data, and then served as a training cohort to establish the IFS. Furthermore, an internal validation cohort including 175 patients was used as internal validation cohort of the IFS. A survival tree analysis was used to divide ICC patients into three groups (low-, median-, and high- IFS-score groups) according to different IFS values. Kaplan-Meier (KM) curves were used to compare the overall survival (OS) and recurrence-free survival (RFS) rates among three different groups. Cox regression analyses were applied to explore the independent risk factors influencing OS and RFS.

RESULTS

In the training cohort, 149 patients were in the low-IFS-score group, 187 in the median-IFS-score group, and 110 in the high-IFS-score group. KM curves showed that the high-IFS-score group had worse OS and RFS rates than those of the low- and median-IFS-score groups (P < 0.001) in both the training and validation cohorts. Moreover, multivariable Cox analyses identified high IFS as an independent risk factor for OS and RFS in the training cohort. The area under the curve values for OS prediction of IFS were 0.703 and 0.664 in the training and validation cohorts, respectively, which were higher than those of the American Joint Committee on Cancer (AJCC) 7th edition TNM stage, AJCC 8th edition TNM stage, and the Child-Pugh score.

CONCLUSION

Our results revealed the IFS was an independent risk factor for OS and RFS in patients with ICC after hepatectomy and could serve as an effective prognostic prediction system in daily clinical practice.

Evaluation of systemic inflammatory and nutritional indexes in locally advanced gastric cancer treated with adjuvant chemoradiotherapy after D2 dissection

BACKGROUND

Many studies have shown that the peripheral blood inflammatory index and nutritional index, such as the platelet lymphocyte ratio (PLR), neutrophil lymphocyte ratio (NLR), lymphocyte monocyte ratio (LMR), systemic inflammation response index (SIRI), pan-immune-inflammation value (PIV), systemic immune-inflammation index (SII), and prognostic nutrition index (PNI), are independent prognostic factors for tumors. The present study aimed to investigate the prognostic role of these peripheral blood indexes before treatment in locally advanced gastric cancer (LAGC) treated with adjuvant chemoradiotherapy after D2 dissection.

METHODS

A total of 89 patients with LAGC who underwent D2 gastrectomy and adjuvant chemoradiotherapy at our hospital from 2010-2018 were eligible. Systemic inflammatory indicators before treatment were evaluated. Receiver operating characteristic curve (ROC), Kaplan-Meier analysis, and Cox regression were utilized for prognosis evaluation.

RESULTS

The median follow-up time was 29.1 (4.1-115.8) months. The overall survival at 3 years (OS) and the disease-free survival (DFS) were 78.9% and 59.1%, respectively. According to the ROC curve for 3-year DFS, the best cut-off values of pre-treatment NLR, PLR, LMR, SII, SIRI, PIV and PNI were 1.7, 109.3, 2.9, 369.2, 0.58, 218.7, and 48, respectively. Multivariate Cox regression analysis showed that NLR was an independent prognostic factor for DFS (HR 2.991, 95%CI 1.085-8.248, P = 0.034). Kaplan-Meier analysis showed that a higher NLR (>1.70) was significantly associated with a poorer OS (3-year OS: 68.8% vs 92.9%, P = 0.045) and DFS (3-year DFS: 47.5% vs 80.9%, P = 0.005). In terms of the free locoregional recurrence rate (LRR), the prognosis of patients with high NLR was also significantly worse than those with low NLR (70.2% vs 96.0%, P = 0.017). Paraaortic lymph nodes were the most common site of LRR (7/14 patients). The seven cases of paraaortic lymph node metastasis occurred in patients with high NLR.

CONCLUSIONS

In our retrospective analysis, we found that pretreatment NLR could serve as a prognostic factor for survival in LAGC treated with adjuvant chemoradiotherapy after D2 dissection, especially for the prediction of LRR and paraaortic lymph node metastasis. Prospective studies are needed to confirm our findings.

Lung Immune Prognostic Index Could Predict Metastasis in Patients With Osteosarcoma

Background

The lung immune prognostic index (LIPI), composed of serum lactate dehydrogenase (LDH) and the derived neutrophil to lymphocyte ratio (dNLR), is a novel prognostic factor of lung cancer. The prognostic effect of the LIPI has never been verified in osteosarcoma.

Methods

We retrospectively reviewed the osteosarcoma patients with metachronous metastasis from January 2016 to January 2021 in West China Hospital. We collected and analyzed the clinical data and constructed the LIPI for osteosarcoma. The correlation between the LIPI and metastasis was analyzed according to the Kaplan–Meier method and Cox regression analysis with hazard ratios (HRs) and 95% confidence intervals (CIs). Univariate analysis and multivariate analysis were conducted to clarify the independent risk factors of metastasis. The nomogram model was established by R software, version 4.1.0.

Results

The area under the curve (AUC) and best cutoff value were 0.535 and 91, 0.519, and 5.02, 0.594 and 2.77, 0.569 and 227.14, 0.59 and 158, and 0.607 and 2.05 for ALP, LMR, NLR, PLR, LDH, and dNLR, respectively. The LIPI was composed of LDH and dNLR and showed a larger AUC than other hematological factors in the time-dependent operator curve (t-ROC). In total, 184 patients, 42 (22.8%), 96 (52.2%), and 46 (25.0%) patients had LIPIs of good, moderate, and poor, respectively (P &lt; 0.0001). Univariate analysis revealed that pathological fracture, the initial CT report of suspicious nodule, and the NLR, PLR, ALP, and the LIPI were significantly associated with metastasis, and multivariate analysis showed that the initial CT report of suspicious nodule and the PLR, ALP, and LIPI were dependent risk factors for metastasis. Metastatic predictive factors were selected and incorporated into the nomogram construction, including the LIPI, ALP, PLR, initial CT report, and pathological fracture. The C-index of our model was 0.71. According to the calibration plot, this predictive nomogram could accurately predict 3- and 5-year metachronous metastasis. Based on the result of decision curve and clinical impact curve, this predictive nomogram could also help patients obtain significant net benefits.

Conclusion

We first demonstrated the metastatic predictive effect of the LIPI on osteosarcoma. This LIPI-based model is useful for clinicians to predict metastasis in osteosarcoma patients and could help conduct timely intervention and facilitate personalized management of osteosarcoma patients.

Prognostic value of a novel dNLR-PNI score in patients with acute coronary syndrome undergoing percutaneous coronary intervention

There is currently limited information on the prognostic value of the dNLR-PNI (the combination of the derived neutrophil-to-lymphocyte ratio [dNLR] and prognostic nutritional index [PNI]) score for patients with acute coronary syndrome (ACS). We aimed to explore the predictive value of a dNLR-PNI score on the long-term prognosis of patients with ACS undergoing percutaneous coronary intervention (PCI). A total of 1773 patients with ACS who underwent PCI were consecutively enrolled from January 2016 to December 2018. The cutoff values of dNLR and PNI to predict major adverse cardiovascular events (MACE) were calculated using receiver operating characteristic curves. The patients were divided into three groups based on the dNLR-PNI score, and Kaplan-Meier curves and Cox regression models were used for survival analysis. The endpoints were MACE, including all-cause mortality and rehospitalisation for severe heart failure during follow-up. A total of 1542 patients with ACS who underwent PCI were included. Kaplan-Meier curves showed that a higher level of dNLR, PNI, or dNLR-PNI score was associated with a higher risk of MACE (allp < .001). In multivariate Cox regression models, the dNLR-PNI two score (hazard ratio 3.049, 95% confidence interval 1.503-6.184, p = .002) was found to be an independent predictor of all-cause mortality and rehospitalization for severe heart failure. A high dNLR-PNI score was independently associated with a higher risk of developing MACE in patients with ACS undergoing PCI. The dNLR-PNI score may be a useful prognostic parameter for identifying high-risk ACS patients after PCI.

ALB-dNLR Score Predicts Mortality in Coronary Artery Disease Patients After Percutaneous Coronary Intervention

Background

The influence of the albumin/derived neutrophil and lymphocyte ratio (ALB-dNLR) on the outcomes of patients with coronary artery disease (CAD) after percutaneous coronary intervention (PCI) is not known. Here, we aimed to determine the association between the ALB-dNLR score and post-PCI CAD patient outcomes.

Methods

A total of 6,050 patients from the First Affiliated Hospital of Xinjiang Medical University were enrolled between January 2008 and December 2016. These patients were divided into three groups according to their ALB-dNLR scores (0 points, n = 1,121; 1 point, n = 3,119; 2 points, n = 1,810). Mortality after PCI [all-cause (ACM) and cardiac (CM)] was taken as the primary endpoint. The prognostic value of the ALB-dNLR score was determined with the Cox proportional hazard model after adjustment for covariates.

Results

The ACM and CM rates differed among participants in the three groups (P = 0.007 and P = 0.034, respectively). Multivariate Cox analysis showed that the ALB-dNLR score independently predicted both ACM [1 point vs. 0 points, HR = 1.249 (95% CI: 0.79–1.774), P = 0.215; 2 points vs. 0 points, HR = 1.777 (95% CI: 1.239–2.549), P = 0.002] and CM [1 point vs. 0 points, HR = 1.294 (95% CI: 0.871–1.922), P = 0.202; 2 points vs. 0 points, HR = 1.782 (95% CI: 1.185–1.782), P = 0.027]. We also found that among male patients in the three groups, both ACM and CM rates differed (P = 0.006 and P = 0.017, respectively). Multivariate Cox analysis showed that the ALB-dNLR score independently predicted both ACM [1 point vs. 0 points, HR = 1.237 (95% CI: 0.806–0.330), P = 0.330; 2 points vs. 0 points, HR = 1.790 (95% CI: 1.159–2.764), P = 0.009] and CM [1 point vs. 0 points HR = 1.472 (95% CI: 0.892–2.430), P = 0.130; 2 points vs. 0 points, HR = 1.792 (95% CI: 1.182–3.289), P = 0.009].

Conclusion

The ALB-dNLR score is a credible predictor for mortality in patients with CAD who have undergone PCI.

Albumin-Derived NLR Score is a Novel Prognostic Marker for Esophageal Squamous Cell Carcinoma

BACKGROUND

Multidisciplinary treatment for esophageal squamous cell carcinoma (ESCC) has improved outcomes, but the prognosis for ESCC remains poor. Nutritional and inflammatory indicators are reported to be associated with cancer prognosis. The combination of albumin and the derived neutrophil-to-lymphocyte ratio (Alb-dNLR) score was established to measure the immune system and nutritional status. The authors hypothesized that the Alb-dNLR score could be a new reliable prognostic factor for ESCC patients.

METHODS

The study evaluated 269 patients who underwent esophagectomy between April 2010 and March 2018, including 185 patients who received neoadjuvant chemotherapy. The Alb-dNLR score was calculated using serum albumin and the dNLR. The dNLR was calculated as neutrophils to (leukocyte-neutrophil count). The cutoff values of the albumin and dNLR for overall survival (OS) were determined using the receiver operating characteristic curve. Patients were divided into "high" and "low" groups according to the Alb-dNLR score.

RESULTS

A high Alb-dNLR score was found in 61 cases (22.7%). The 5-year OS was 34% in the high Alb-dNLR group and 66.2% in the low Alb-dNLR group (p < 0.0001). The 5-year cause-specific survival (CSS) was 51.5% in the high Alb-dNLR group and 74.7% in the low Alb-dNLR group (p < 0.0001). Multivariate analyses demonstrated that the Alb-dNLR score was an independent prognostic factor for OS (hazard ratio [HR], 2.198; 95% confidence interval [CI], 1.460-3.263; p = 0.0002) and CSS (HR, 1.733; 95% CI, 1.035-2.835; p = 0.0371).

CONCLUSIONS

The Alb-dNLR score is an extremely useful, easy-to-use parameter to predict OS and CSS for ESCC patients.

Bioinformatic and experimental analyses of key biomarkers in pancreatic cancer

The present study aimed to screen the key genes in pancreatic cancer and to explore the pathogenesis of pancreatic cancer. A total of three expression profiling datasets (GSE28735, GSE16515 and GSE15471) associated with pancreatic cancer were retrieved from the public gene chip database. The differentially expressed genes (DEGs) were screened by GEO2R and subjected to Gene Ontology (GO) and signaling pathway enrichment analysis. Furthermore, a protein interaction network was constructed. The GEPIA online database was used to screen for genes that affect the prognosis of pancreatic cancer. Finally, cell functional experiments were performed on the selected key genes. A total of 72 DEGs were identified, including 52 upregulated and 20 downregulated genes. Enrichment analysis revealed roles of the DEGs in endodermal cell differentiation, cell adhesion, extracellular matrix-receptor interaction and PI3K-Akt signaling pathway. In total, 10 key nodal genes were identified, including integrin subunit α 2 (ITGA2), ITGB6 and collagen α 1 chain 1. Through survival analysis, two genes with an impact on the prognosis of pancreatic cancer were identified, namely ITGA2 and ITGB6. Silencing of ITGB6 in a pancreatic cancer cell line significantly suppressed cell proliferation and induced cell cycle arrest at G2/M phase. The identified key genes and signaling pathways may help to deepen the understanding of the molecular mechanisms involved in pancreatic cancer and provide a theoretical basis to develop novel therapies.

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.

Prognostic role of pretreatment lung immune prognostic index in extensive-stage small-cell lung cancer treated with platinum plus etoposide chemotherapy

BACKGROUND

To investigate the prognostic role of lung immune prognostic index (LIPI) in extensive-stage small-cell lung cancer (ES-SCLC) patients treated with platinum plus etoposide chemotherapy.

METHODS

Data were obtained from two randomized controlled trials (NCT00119613 and NCT00363415). Overall survival (OS) and progression-free survival (PFS) was assessed according to LIPI score through Kaplan-Meier analysis. Univariate and multivariate Cox-regression analysis were performed to investigate predictors for OS and PFS.

RESULTS

A total of 911 patients with ES-SCLC treated with platinum plus etoposide chemotherapy (CT) were included for analysis. The median age at diagnosis was 62 years, and 760 (83.4%) had performance status of 1 or less. 1-year OS for ES-SCLC with poor, intermediate, and good LIPI was 20%, 30% and 31%, respectively, and 1-year PFS was 7%, 15% and 21%, respectively. Cox-regression analysis showed that the PFS and OS of ES-SCLC with a poor LIPI score was significantly worse than those with good LIPI scores (HR 1.81, 95% CI: 1.38-2.36; p< 0.001 and HR 1.35, 95% CI: 1.07-1.72, p= 0.012), while no significant difference was observed between intermediate and poor LIPI groups in terms of OS (HR 1.01, 95% CI: 0.82-1.23, p= 0.82), but not for PFS (HR 1.27, 95% CI: 1.00-1.61, p= 0.048). In addition, LIPI score was significantly associated with disease control rate and objective response rate (both p< 0.0001).

CONCLUSION

Prognosis of patients with pretreatment LIPI score of 2 is poorer than those with LIPI score of 0-1 among ES-SCLC who received first-line platinum plus etoposide chemotherapy; Further studies are still recommended to confirm our findings in prospective studies.

Association Between the Pretreatment Albumin-to-Alkaline Phosphatase Ratio and Clinical Outcomes in Patients With Bladder Cancer Treated With Radical Cystectomy: A Retrospective Cohort Study

Objective

Serum albumin-to-alkaline phosphatase ratio (AAPR) has been proven to be a prognostic indicator of many malignant tumors. However, whether it can predict the prognosis of bladder cancer (BC) patients who underwent radical cystectomy (RC) remains unclear. This study was designed to assess the relationship between AAPR and clinical outcomes in patients with BC treated with RC.

Methods

The clinicopathological data of 199 BC patients receiving RC in our institution from January 2012 to December 2017 were retrospectively collected and analyzed. They were divided into three groups based on the optimal cut-off values and the association between AAPR groups and their clinical outcomes were evaluated.

Results

The average age of the patients was (64.0 ± 8.7) years and 79.9% were male. Based on the cut-off values of AAPR, patients were divided into three groups: low-AAPR group (AAPR < 0.37, n = 35), medium-AAPR group (AAPR = 0.37-0.59, n = 61) and high-AAPR group (AAPR > 0.59, n = 103). The median overall survival (OS) of each AAPR group was 12.5, 24, and 29 months, respectively (P value <0.0001). After adjusting the Cox proportional hazards model, medium- and high- AAPR groups showed a reduced risk trend of death, with a risk ratio of 0.44 (95% CI = 0.21-0.91) and 0.25 (95% CI = 0.12-0.49), respectively (P for trend <0.001). No nonlinear relationship was identified by smooth fitting curve between AAPR and OS. By subgroup analysis, we observed that compared to the low-AAPR group, the trends of the HRs in the medium- and high-AAPR group were decreased across nearly all subgroups after stratification. Moreover, the AAPR-based nomograms for OS, CSS and RFS were also constructed. The C-index showed a good predictive accuracy (OS, C-index 0.728, 95% CI 0.663-0.793; CSS, C-index 0.792, 95% CI 0.748-0.838; RFS, C-index 0.784, 95% CI 0.739-0.829).

Conclusion

Pretreatment AAPR is significantly associated with the prognosis of BC patients receiving RC, which can be conducive to the clinical decision-making and risk stratification in those patients. The nomogram based on AAPR is a reliable model for predicting survival of BC patients after RC.

Assessment of systematic inflammatory and nutritional indexes in extensive-stage small-cell lung cancer treated with first-line chemotherapy and atezolizumab

BACKGROUND

The present study aims to investigate the prognostic role of systematic inflammatory and nutritional indexes in extensive-stage small-cell lung cancer (ES-SCLC) treated with first-line chemotherapy and atezolizumab.

MATERIALS AND METHODS

Prospective cohort population involving 53 patients were identified from NCT03041311 trial. The following peripheral blood-derived inflammatory and nutritional indexes, including neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), lymphocyte-monocyte ratio (LMR), systemic immune-inflammation index (SII), systemic inflammation response index (SIRI), prognostic nutrition index (PNI), advanced lung cancer inflammation index (ALI), and lung immune prognostic index (LIPI) were evaluated.

RESULTS

The optimal cut-off values of the ALI, LMR, NLR, PLR, PNI, SII and SIRI were 323.23, 2.73, 2.57, 119.23, 48, 533.28 and 2.32, respectively. With a median follow-up of 17.1 months, the 1-year OS and PFS were 56% and 8%, respectively. Multivariate analysis showed that PLR was the only independent prognostic factors for OS among ES-SCLC patients treated with chemotherapy and atezolizumab (HR 4.63, 95%CI: 1.00-21.46, p = 0.05). K-M analysis showed that the OS and PFS for patients with high PLR (> 119.23) were significantly poorer than these with low PLR (≤ 119.23) (p = 0.0004 for OS and p = 0.014 for PFS). In external validation set, prognosis of patients with high PLR was also significantly poorer than these with low PLR in terms of OS (p = 0.038) and PFS (p = 0.028).

CONCLUSION

Pre-treatment PLR could serve as a valuable independent prognostic factor for ES-SCLC who receive chemotherapy and immune checkpoint inhibitors. Further, prospective studies are still needed to confirm our findings.

Serum proteomics analysis of feline mammary carcinoma based on label-free and PRM techniques

Background

Feline mammary carcinoma is the third most common cancer that affects female cats.

Objectives

The purpose of this study was to screen differential serum proteins in feline and clarify the relationship between them and the occurrence of feline mammary carcinoma.

Methods

Chinese pastoral cats were used as experimental animals. Six serum samples from cats with mammary carcinoma (group T) and six serum samples from healthy cats (group C) were selected. Differential protein analysis was performed using a Label-free technique, while parallel reaction monitoring (PRM) was performed to verify the screened differential proteins.

Results

A total of 82 differential proteins were detected between group T and group C, of which 55 proteins were down regulated and 27 proteins were up regulated. Apolipoprotein A-I, Apolipoprotein A-II (ApoA-II), Apolipoprotein B (ApoB), Apolipoprotein C-III (ApoC-III), coagulation factor V, coagulation factor X, C1q, albumen (ALB) were all associated with the occurrence of feline mammary carcinoma. Differential proteins were involved in a total of 40 signaling pathways, among which the metabolic pathways associated with feline mammary carcinoma were the complement and coagulation cascade and cholesterol metabolism. According to the Label-free results, ApoB, ApoC-III, ApoA-II, FN1, an uncharacterized protein, and ALB were selected for PRM target verification. The results were consistent with the trend of the label-free.

Conclusions

This experimen is the first to confirm ApoA-II and ApoB maybe new feline mammary carcinoma biomarkers and to analyze their mechanisms in the development of such carcinoma in feline.

Significance of serum albumin and derived neutrophil-to-lymphocyte ratio score in assessment of disease activity in rheumatoid arthritis patients

Background

Albumin and derived neutrophil to lymphocyte ratio (dNLR) are known biomarkers that can reflect systemic inflammation and it has been hypothesized that combination of both markers in one score (albumin-dNLR score) can be useful in monitoring rheumatoid arthritis (RA) patients. The current study intended to measure albumin -dNLR score in patients with RA in the order to find whether these new biomarkers could reflect the activity of the disease and the articular activity detected by ultrasonography. We measured serum albumin and dNLR in blood samples obtained from 100 RA patients and from 100 apparently healthy controls (HC). Albumin -dNLR score was calculated according to the presence of hypoalbuminemia (≤ 3.76 gm/dl) and/or raised dNLR (>1.37).

Results

RA patients had a significantly elevated dNLR (p< 0.001) and albumin-dNLR score (p< 0.001) compared to their levels in HC, while serum albumin was significantly decreased (p< 0.001) in RA patients than its level in HC. In RA patients, albumin-dNLR score correlated significantly with DAS28 (p< 0.001), erythrocyte sedimentation rate (ESR) (p< 0.001), C-reactive protein (p< 0.001), grey scale (p< 0.001), power Doppler (p< 0.001) and total ultrasound score (p< 0.001). Also, tender joint count, ESR and albumin-dNLR score were significant predictors of DAS28 in multivariate regression analysis.

Conclusions

Our study settled that albumin - dNLR score is increased in RA patients than in healthy subjects. The score correlated well with DAS28, acute phase reactants, and ultrasonographic synovitis scores implying that it could be an easy valuable biomarker to monitor RA disease activity.

Systemic Inflammatory Biomarkers, Especially Fibrinogen to Albumin Ratio, Predict Prognosis in Patients with Pancreatic Cancer

Purpose

Systemic inflammatory response is a critical factor that promotes the initiation and metastasis of malignancies including pancreatic cancer (PC). This study was designed to determine and compare the prognostic value of neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and fibrinogen-to-albumin ratio (FAR) in resectable PC and locally advanced or metastatic PC.

Materials and Methods

Three hundred fifty-three patients with resectable PC and 807 patients with locally advanced or metastatic PC were recruited in this study. These patients were classified into a training set (n=758) and a validation set (n=402). Kaplan-Meier survival plots and Cox proportional hazards regression models were used to analyze prognosis.

Results

Overall survival (OS) was significantly better for patients with resectable PC with low preoperative PLR (p=0.048) and MLR (p=0.027). Low FAR, MLR, NLR (p < 0.001), and PLR (p=0.003) were significantly associated with decreased risk of death for locally advanced or metastatic PC patients. FAR (hazard ratio [HR], 1.522; 95% confidential interval [CI], 1.261 to 1.837; p < 0.001) and MLR (HR, 1.248; 95% CI, 1.017 to 1.532; p=0.034) were independent prognostic factors for locally advanced or metastatic PC.

Conclusion

The prognostic roles of FAR, MLR, NLR, and PLR in resectable PC and locally advanced or metastatic PC were different. FAR showed the most prognostic power in locally advanced or metastatic PC. Low FAR was positively correlated with OS in locally advanced or metastatic PC, which could be used to predict the prognosis.

Lymphocyte-to-monocyte ratio effectively predicts survival outcome of patients with obstructive colorectal cancer

BACKGROUND

Obstructive colorectal cancer (OCC) is always accompanied by severe complications, and the optimal strategy for patients with OCC remains undetermined. Different from emergency surgery (ES), self-expandable metal stents (SEMS) as a bridge to surgery (BTS), could increase the likelihood of primary anastomosis. However, the stent failure and related complications might give rise to a high recurrence rate. Few studies have focused on the indications for either method, and the relationship between preoperative inflammation indexes and the prognosis of OCC is still underestimated.

AIM

To explore the indications for ES and BTS in OCCs based on preoperative inflammation indexes.

METHODS

One hundred and twenty-eight patients who underwent ES or BTS from 2008 to 2015 were enrolled. Receiver operating characteristic (ROC) curve analysis was used to define the optimal preoperative inflammation index and its cutoff point. Kaplan–Meier analyses and Cox proportional hazards models were applied to assess the association between the preoperative inflammation indexes and the survival outcomes [overall survival (OS) and disease-free survival (DFS)]. Stratification analysis was performed to identify the subgroups that would benefit from ES or BTS.

RESULTS

OS and DFS were comparable between the ES and BTS groups (P > 0.05). ROC curve analysis showed derived neutrophil-to-lymphocyte ratio (dNLR) as the optimal biomarker for the prediction of DFS in ES (P < 0.05). Lymphocyte-to-monocyte ratio (LMR) was recommended for BTS with regard to OS and DFS (P < 0.05). dNLR was related to stoma construction (P = 0.001), pneumonia (P = 0.054), and DFS (P = 0.009) in ES. LMR was closely related to lymph node invasion (LVI) (P = 0.009), OS (P = 0.020), and DFS (P = 0.046) in the BTS group. dNLR was an independent risk factor for ES in both OS (P = 0.032) and DFS (P = 0.016). LMR affected OS (P = 0.053) and DFS (P = 0.052) in the BTS group. LMR could differentiate the OS between the ES and BTS groups (P < 0.05).

CONCLUSION

Preoperative dNLR and LMR could predict OS and DFS in patients undergoing ES and BTS, respectively. For OCC, as the potential benefit group, patients with a low LMR might be preferred for BTS via SEMS insertion.

Diagnostic and Prognostic Impact of Neutrophil-to-Lymphocyte Ratio for Intraductal Papillary Mucinous Neoplasms of the Pancreas With High-Grade Dysplasia and Associated Invasive Carcinoma

OBJECTIVES

The aim of this study was to evaluate the diagnostic and prognostic impact of systemic inflammatory markers for IPMN with high-grade dysplasia (HGD)/invasive carcinoma.

METHODS

Neutrophil-to-lymphocyte ratio (NLR), derived NLR, platelet-to-lymphocyte ratio, and C-reactive protein-to-albumin ratio were compared across the different histological grades of 205 IPMN cases. We also tested the diagnostic performance for IPMN with HGD/invasive carcinoma.

RESULTS

The median (interquartile range) preoperative NLR was higher in IPMN with HGD/invasive carcinoma (2.03 [1.48-2.93]) than IPMN with low-grade dysplasia (1.74 [1.42-2.24], P = 0.0137). The C-reactive protein-to-albumin ratio and derived NLR values were also significant higher in cases with HGD/invasive carcinoma. A combination assay of NLR, carcinoembryonic antigen, and carbohydrate antigen 19-9 revealed a 58.8% sensitivity and 76.8% specificity. Among the cases with worrisome features, the high NLR values increased the positive predictive value (68.8%) compared with low values (31.8%). In IPMN cases with the associated invasive carcinoma, high NLR values showed association with the deeper vertical invasion and shorter survival periods.

CONCLUSIONS

Preoperative NLR, combined with tumor markers and image findings, can be a useful predictive marker for the presence of HGD/invasive carcinoma in IPMNs. Preoperative NLR also predicts the long-term outcomes in IPMN cases with invasive carcinoma.

The association between albumin-dNLR score and disease activity in patients with rheumatoid arthritis

BACKGROUND

Recently, clinical studies have described an association between albumin and the derived neutrophil to lymphocyte ratio (dNLR) with several diseases. This study was aimed to investigate the albumin-dNLR (ALB-dNLR) score in rheumatoid arthritis (RA) patients and assess its relationship with clinical and laboratory parameters of RA.

METHODS

We retrospectively enrolled 127 RA patients, 155 osteoarthritis (OA) patients, and 155 healthy controls. The ALB-dNLR score was based on serum albumin level, neutrophil count, and white cell count. The Spearman's rank test was used to measure the correlations between ALB-dNLR score and disease activity as well as laboratory indexes.

RESULTS

The ALB-dNLR score was significantly higher in RA patients than in OA patients (P < 0.001) and in healthy controls (P < 0.001). The proportion of higher ALB-dNLR score has been raised along with increased disease activity (P < 0.001). The Spearman's rank test showed that ALB-dNLR score was positively associated with DAS28 score, CRP, ESR, IgA, and platelet count. Moreover, the receiver operating characteristic (ROC) curve showed that the area under the curve (AUC) of ALB-dNLR was 0.693 (95% CI: 0.631-0.755), which was higher than that of albumin (AUC: 0.625, 95% CI: 0.559-0.692) and dNLR (AUC: 0.680, 95% CI: 0.617-0.743) alone.

CONCLUSIONS

The results demonstrate that the ALB-dNLR score increased in RA patients. The ALB-dNLR score may be a useful marker to estimate the disease activity of RA patients.