Preoperative Peripheral Blood Lymphocyte-to-Monocyte Ratio Predicts Long-Term Outcome for Patients with Pancreatic Ductal Adenocarcinoma

New model to predict survival in advanced pancreatic ductal adenocarcinoma patients by measuring GGT and LDH levels and monocyte count

Introduction

Pancreatic ductal adenocarcinoma (PDAC) is a lethal cancer with a poor survival outcome. Predicting patient survival allows physicians to tailor treatments to specific individuals. Thus, a simple and cost-effective prognosis model is sorely needed.

Methods

This retrospective study assesses the prognostic value of blood biomarkers in advanced and metastatic PDAC patients (n=96) from Spain. Cut-off points for hematological parameters were calculated and correlated with overall survival (OS) using Kaplan-Meier, log-rank test, robust Cox proportional hazards and logistic regressions.

Results

In univariate analysis, individuals with low levels of GGT, LDH, ALP, leukocyte-, neutrophil- and monocyte counts showed significantly longer survival than patients with higher levels. In multivariate analysis, lower levels of GGT (HR (95%CI), 2.734 (1.223-6.111); p=0.014), LDH (HR (95%CI), 1.876 (1.035-3.400); p=0.038) and monocyte count (HR (95%CI), 1.657 (1.095-2.506); p = 0.017) remained significantly beneficial. In consequence, we propose a prognostic model based on logistic regression (AUC=0.741) of these three biomarkers as a pioneer tool to estimate OS in PDAC.

Conclusion

This study has demonstrated that the joint use of GGT (<92.00), LDH (<220.00) and monocyte count (<800) are independent positive prognostic factors in PDAC that can predict one-year survival in a novel prognostic logistic model.

The prognostic role of lymphocyte-to-monocyte ratio in patients with resectable pancreatic cancer: a systematic review and meta-analysis

Objectives

This systematic review and meta-analysis examined whether the lymphocyte-to-monocyte ratio (LMR) can serve as an indicator for predicting the prognosis of patients with resectable pancreatic cancer.

Patients and Methods

This meta-analysis was registered with PROSPERO: CRD42023461260. A systematic literature search was conducted in the PubMed, Embase, Cochrane, and Web of Science databases up to September 2023 to assess whether LMR can predict the prognosis of patients with resectable pancreatic cancer. The outcomes measured included subgroup analyses of overall survival (OS) with hazard ratios (HR) and confidence intervals of geographical region, patient population, and LMR threshold. A sensitivity analysis was also performed for OS and HR and confidence intervals were calculated for recurrence-free survival (RFS).

Results

A total of 14 eligible articles, comprising 4,019 patients, were included in the comprehensive analysis. The results of this comprehensive analysis indicate that LMR is a robust predictor of OS, demonstrating strong prognostic significance (HR = 0.55, 95% CI [0.44-0.69], I2 = 79%, P < 0.00001). This predictive significance extended to various types of pancreatic cancer, such as pancreatic ductal adenocarcinoma (HR = 0.73, 95% CI [0.57-0.93], I2 = 46%, P = 0.01), pancreatic neuroendocrine neoplasms (HR = 0.81, 95% CI [0.66-0.99], P = 0.04) and other subtypes (HR = 0.40, 95% CI [0.22-0.72], I2 = 89%, P < 0.00001), but not to pancreatic head cancer (HR = 0.46, 95% CI [0.16-1.13], I2 = 59%, P = 0.12). LMR retained its predictive value across different regions, including Asia (HR = 0.62, 95% CI [0.47-0.76], I2 = 68%, P < 0.0001), Europe (HR = 0.78, 95% CI [0.67-0.91], I2 = 0%, P = 0.002), and the Americas (HR = 0.14, 95% CI [0.08-0.24], I2 = 0%, P < 0.00001). Notably, both LMR cut-off values greater than or equal to three (HR = 0.62, 95% CI [0.47-0.82], I2 = 67%, P = 0.0009) and less than three (HR = 0.47, 95% CI [0.32-0.69], I2 = 85%, P = 0.0001) exhibited prognostic significance. The sensitivity analysis for OS confirmed the strong predictive value of LMR, whereas LMR did not exhibit predictive significance for RFS (HR = 0.35, 95% CI [0.09-1.32], I2 = 95%, P = 0.12). In both subgroups categorized by Newcastle-Ottawa Scale (NOS) scores of ≥7 (HR = 0.66, 95% CI [0.54-0.80], I2 = 53%, P = 0.04) and <7 (HR = 0.41, CI [0.23-0.72], I2 = 89%, P < 0.00001), LMR was demonstrated to have predictive value.

Conclusion

Despite the observed heterogeneity and potential biases in the included studies, the findings of this study suggest that LMR may serve as a valuable predictor of OS in patients with resectable pancreatic cancer.

Association of immune inflammatory biomarkers with pathological complete response and clinical prognosis in young breast cancer patients undergoing neoadjuvant chemotherapy

Background

The persistence of inflammatory stimulus has a tight relationship with the development of age-related diseases, ultimately resulting in a gradual escalation in the prevalence of tumors, but this phenomenon is rare in young cancer patients. Breast cancer arising in young women is characterized by larger tumor diameters and more aggressive subtypes, so neoadjuvant chemotherapy (NACT) can be especially appropriate for this population. Immune inflammatory biomarkers have been reportedly linked to the prognosis of some malignant tumor types, with varying results. In this study, we investigated the possible predictive value of blood-based markers in young breast cancer patients undergoing NACT, in addition to the association between the clinicopathological features and prognosis.

Methods

From December 2011 to October 2018, a total of 215 young breast cancer patients referred to Harbin Medical University Cancer Hospital received NACT and surgery were registered in this retrospective study. The pretreatment complete blood counts were used to calculate the neutrophil-to-lymphocyte ratio (NLR), platelet-to-lymphocyte ratio (PLR), monocyte-to-lymphocyte ratio (MLR), and pan-immune-inflammation value (PIV).

Results

NLR, PLR, MLR, and PIV optimal cut-off values were 1.55, 130.66, 0.24, and 243.19, as determined by receiver operating characteristic analysis. Multivariate analysis revealed that PIV, HR status, HER-2 status, and Ki-67 index were all independent predictive factors for pathological complete response. Subgroup analysis revealed that young breast cancer patients in the population characterized by low PIV and HR negative group were more likely to get pCR (P=0.001). The five-year overall survival (OS) rate was 87.9%, and Cox regression models identified PIV as independently related to OS.

Conclusion

In the present study, the pretreatment PIV was found to be a useful prognostic indicator for pCR and long-term survival in young breast cancer patients undergoing NACT. High immune and inflammation levels, MLR and PIV were connected to poor clinical prognosis in young breast cancer patients. PIV is a promising biomarker to guide strategic decisions in treating young breast cancer.

A novel combined carbohydrate antigen 19-9 and lymphocyte-to-monocyte ratio score can predict early recurrence of resectable pancreatic ductal adenocarcinoma

PURPOSE

Pancreatic ductal adenocarcinoma (PDAC) often recurs early after radical resection, which causes a poor prognosis. This study aimed to establish a scoring model to assess the optimal treatment in patients who underwent surgery for PDAC.

METHODS

This single-center retrospective study included 127 patients who underwent radical resection for PDAC between 2005 and 2021. Early recurrence (ER) was defined as recurrence within 12 months after resection. The predictive effect for ER was evaluated using receiver operating characteristic (ROC) curves of preoperative parameters.

RESULTS

ER occurred in 43 (33.9%) patients. The ER group had a significantly worse prognosis than the non-ER group (p < 0.0001). The carbohydrate antigen 19-9 (CA19-9) level and lymphocyte-to-monocyte ratio (LMR) were the strongest diagnostic factors (areas under the ROC curves: 0.74 and 0.68, respectively). The ER prediction score was calculated using optimal cutoff values. A higher CA19-9-LMR score was associated with a worse prognosis in terms of the overall and recurrence-free survival (p = 0.0017 and p < 0.0001, respectively). A multivariate analysis identified a high CA19-9-LMR score as an independent predictor of ER.

CONCLUSIONS

The CA19-9-LMR scoring model can predict ER after surgery and is applicable for risk stratification in the assessment of patients with resectable PDAC.

Mass cytometry-based peripheral blood analysis as a novel tool for early detection of solid tumours: a multicentre study

OBJECTIVE

Early detection of a tumour remains an unmet medical need, and approaches with high sensitivity and specificity are urgently required. Mass cytometry time-of-flight (CyTOF) is a powerful technique to profile immune cells and could be applied to tumour detection. We attempted to establish diagnostic models for hepatocellular carcinoma (HCC) and pancreatic ductal adenocarcinoma (PDAC).

DESIGN

We performed CyTOF analysis for 2348 participants from 15 centres, including 1131 participants with hepatic diseases, 584 participants with pancreatic diseases and 633 healthy volunteers. Diagnostic models were constructed through random forest algorithm and validated in subgroups.

RESULTS

We determined the disturbance of systemic immunity caused by HCC and PDAC, and calculated a peripheral blood immune score (PBIScore) based on the constructed model. The PBIScore exhibited good performance in detecting HCC and PDAC, with both sensitivity and specificity being around 80% in the validation cohorts. We further established an integrated PBIScore (iPBIScore) by combining PBIScore and alpha-fetoprotein or carbohydrate antigen 19-9. The iPBIScore for HCC had an area under the curve (AUC) of 0.99, 0.97 and 0.96 in training, internal validation and external validation cohorts, respectively. Similarly, the iPBIScore for PDAC showed an AUC of 0.99, 0.98 and 0.97 in the training, internal validation and external validation cohorts, respectively. In early-stage and tumour-marker-negative patients, our iPBIScore-based models also showed an AUC of 0.95-0.96 and 0.81-0.92, respectively.

CONCLUSION

Our study proved that the alterations of peripheral immune cell subsets could assist tumour detection, and provide a ready-to-use detection model for HCC and PDAC.