Correlation between Prognostic Nutritional Index, Glasgow Prognostic Score, Systemic Inflammatory Response, and TNM Staging in Colorectal Cancer Patients

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.

Novel nomograms based on microvascular invasion grade for early-stage hepatocellular carcinoma after curative hepatectomy

Microvascular invasion (MVI) is a critical risk factor for postoperative recurrence of hepatocellular carcinoma (HCC). This study aimed to firstly develop and validate nomograms based on MVI grade for predicting recurrence, especially early recurrence, and overall survival in patients with early-stage HCC after curative resection. We retrospectively reviewed the data of patients with early-stage HCC who underwent curative hepatectomy in the First Affiliated Hospital of Fujian Medical University (FHFU) and Mengchao Hepatobiliary Hospital of Fujian Medical University (MHH). Kaplan-Meier curves and Cox proportional hazards regression models were used to analyse disease-free survival (DFS) and overall survival (OS). Nomogram models were constructed on the datasets from the 70% samples of and FHFU, which were validated using bootstrap resampling with 30% samples as internal validation and data of patients from MHH as external validation. A total of 703 patients with early-stage HCC were included to create a nomogram for predicting recurrence or metastasis (DFS nomogram) and a nomogram for predicting survival (OS nomogram). The concordance indexes and calibration curves in the training and validation cohorts showed optimal agreement between the predicted and observed DFS and OS rates. The predictive accuracy was significantly better than that of the classic HCC staging systems.

Deep learning for the prediction of the chemotherapy response of metastatic colorectal cancer: comparing and combining H&E staining histopathology and infrared spectral histopathology

Colorectal cancer is a global public health problem with one of the highest death rates. It is the second most deadly type of cancer and the third most frequently diagnosed in the world. The present study focused on metastatic colorectal cancer (mCRC) patients who had been treated with chemotherapy-based regimen for which it remains uncertainty about the efficacy for all eligible patients. This is a major problem, as it is not yet possible to test different therapies in view of the consequences on the health of the patients and the risk of progression. Here, we propose a method to predict the efficacy of an anticancer treatment in an individualized way, using a deep learning model constructed on the retrospective analysis of the primary tumor of several patients. Histological sections from tumors were imaged by standard hematoxylin and eosin (HE) staining and infrared spectroscopy (IR). Images obtained were then processed by a convolutional neural network (CNN) to extract features and correlate them with the subsequent progression-free survival (PFS) of each patient. Separately, HE and IR imaging resulted in a PFS prediction with an error of 6.6 and 6.3 months respectively (28% and 26% of the average PFS). Combining both modalities allowed to decrease the error to 5.0 months (21%). The inflammatory state of the stroma seemed to be one of the main features detected by the CNN. Our pilot study suggests that multimodal imaging analyzed with deep learning methods allow to give an indication of the effectiveness of a treatment when choosing.

Can neutrophil-lymphocyte ratio and mean platelet volume be used to predict metastasis in individuals with lung cancer?

Chronic inflammation plays an important role in the etiopathogenesis of many life-threatening chronic diseases, including cancer. Currently, the relationship between inflammation, native immunity and cancer is widely accepted; however, many of the mechanisms mediating this relationship remain undetermined and the clinical significance of these markers is unclear. The purpose of this study was to investigate the potential of neutrophil-lymphocyte ratio (NLR) and mean platelet volume (MPV) to indicate the existence of metastasis in lung cancer. This retrospective cross-sectional study evaluated patients with lung cancer of any pathological type who was admitted to the Palliative Care Unit of the referral hospital in the region between January 2019 and February 2020. Patient characteristics, distant organ metastasis, treatments, NLR and MPV values were noted. Patients were grouped as with or without metastasis. Characters, NLR, MPV values were compared. One hundred twenty-six patients were included. The mean age of the patients was 61.17 ± 9.4 years and 7.9% (n = 10) were female. The patients with a history of chemotherapy were 47% (n = 60) and distant organ metastases were present in 38.9% (n = 49) of the patients. The mean MPV value of 49 patients with distant metastasis was 8.34 ± 0.8 fL. MPV values of those with metastasis were found to be significantly higher than those without (P = .010). There was no significant difference in NLR values between groups (P = .920). Lung cancer patients with metastasis were found with higher MPV values. MPV can be effective and most accessible test in prediction of metastasis in lung cancer patients regardless of the pathological type.

Prognostic value of preoperative immune-nutritional scoring systems in remnant gastric cancer patients undergoing surgery

BACKGROUND

Remnant gastric cancer (GC) is defined as GC that occurs five years or more after gastrectomy. Systematically evaluating the preoperative immune and nutritional status of patients and analyzing its prognostic impact on postoperative remnant gastric cancer (RGC) patients are crucial. A simple scoring system that combines multiple immune or nutritional indicators to identify nutritional or immune status before surgery is necessary.

AIM

To evaluate the value of preoperative immune-nutritional scoring systems in predicting the prognosis of patients with RGC.

METHODS

The clinical data of 54 patients with RGC were collected and analyzed retrospectively. Prognostic nutritional index (PNI), controlled nutritional status (CONUT), and Naples prognostic score (NPS) were calculated by preoperative blood indicators, including absolute lymphocyte count, lymphocyte to monocyte ratio, neutrophil to lymphocyte ratio, serum albumin, and serum total cholesterol. Patients with RGC were divided into groups according to the immune-nutritional risk. The relationship between the three preoperative immune-nutritional scores and clinical characteristics was analyzed. Cox regression and Kaplan–Meier analysis was performed to analyze the difference in overall survival (OS) rate between various immune-nutritional score groups.

RESULTS

The median age of this cohort was 70.5 years (ranging from 39 to 87 years). No significant correlation was found between most pathological features and immune-nutritional status (P > 0.05). Patients with a PNI score < 45, CONUT score or NPS score ≥ 3 were considered to be at high immune-nutritional risk. The areas under the receiver operating characteristic curves of PNI, CONUT, and NPS systems for predicting postoperative survival were 0.611 [95% confidence interval (CI): 0.460–0.763; P = 0.161], 0.635 (95%CI: 0.485–0.784; P = 0.090), and 0.707 (95%CI: 0.566–0.848; P = 0.009), respectively. Cox regression analysis showed that the three immune-nutritional scoring systems were significantly correlated with OS (PNI: P = 0.002; CONUT: P = 0.039; NPS: P < 0.001). Survival analysis revealed a significant difference in OS between different immune-nutritional groups (PNI: 75 mo vs 42 mo, P = 0.001; CONUT: 69 mo vs 48 mo, P = 0.033; NPS: 77 mo vs 40 mo, P < 0.001).

CONCLUSION

These preoperative immune-nutritional scores are reliable multidimensional prognostic scoring systems for predicting the prognosis of patients with RGC, in which the NPS system has relatively effective predictive performance.

Gustave Roussy immune score is a prognostic marker in patients with small cell lung cancer undergoing immunotherapy: a real-world retrospective study

Background

The utilization of the Gustave Roussy Immune Score (GRIm-Score) in patient selection for immunotherapy was initially reported. The objective of this retrospective study is to assess the potential of the GRIm-Score, a novel prognostic score based on nutritional and inflammatory markers, as a prognostic predictor in patients with small cell lung cancer (SCLC) undergoing immunotherapy.

Methods

This retrospective study conducted at a single center included 159 patients with SCLC who received immunotherapy. The objective of the study was to investigate potential differences in overall survival (OS) and progression-free survival (PFS) among patients stratified by their GRIm-Score, utilizing the Kaplan-Meier survival analysis and the log-rank test. The final independent prognostic factors were identified through both propensity score matching (PSM) analysis and multivariable Cox proportional hazards regression analysis.

Results

Our analysis of the 159 patients revealed that there was a significant decrease in both OS and PFS with each increase in the GRIm-Score group, displaying a stepwise pattern. Moreover, even after conducting PSM analysis, the significant associations between the modified three-category risk scale-based GRIm-Score and survival outcomes remained significant. Both the total cohort and PSM cohort were subjected to multivariable analysis, which demonstrated that the three-category risk assessment-based GRIm-Score was a valuable predictor of both OS and PFS.

Conclusions

In addition, the GRIm-Score may serve as a valuable and non-invasive prognostic predictor for SCLC patients undergoing PD1/PD-L1 immunotherapy.

Pan-immune-inflammation value is associated with the clinical stage of colorectal cancer

Objective

We investigated the clinical significance of preoperative pan-immune-inflammation value (PIV) in patients with colorectal cancer (CRC).

Methods

In this retrospective study, 366 cases who underwent surgery for CRC were enrolled. Their clinical data were collected. PIV was calculated with the formula PIV = [neutrophil count (109/L)× platelet count (109/L) × monocyte count (109/L) /lymphocyte count (109/L). Patients were divided into high PIV (&gt; median PIV) and low PIV (&lt; median PIV) groups. The relationship between PIV and clinicopathological features of CRC was investigated. Receiver operating characteristic (ROC) curve was plotted to indicate the value of immune-inflammatory biomarkers (IIBs) in predicting the TNM stage of CRC, and the area under the curve (AUC) was calculated to evaluate the actual clinical value of IIBs. AUC &gt; 0.5 and closer to 1 indicated the better predictive efficacy. The influencing factors of PIV in CRC were analyzed.

Results

We found that PIV was positively correlated with tumor size (r = 0.300, p &lt; 0.05), carcinoembryonic antigen (CEA) (r = 0.214, p &lt; 0.05) and carbohydrate antigen 125 (CA-125) (r = 0.249, p &lt; 0.05), but negatively correlated with albumin (Alb) (r = −0.242, p &lt; 0.05). PIV was significantly different in patients with different tumor locations (left or right), surgical methods (laparotomy versus laparoscopic surgery) (p &lt; 0.05), and patients with different pathological T stages, N-stage and TNM stages (p &lt; 0.05). ROC curve analysis of IIBs showed the AUC of PIV was greater than other markers when combined with CEA or carbohydrate antigen 19–9 (CA19–9). Multivariate regression analysis identified T stage, CEA, Alb, and tumor size as the independent influential factors of PIV in CRC.

Conclusion

PIV is associated with the tumor stage in patients with CRC, which may be useful in preoperative assessment of CRC.

Gustave Roussy Immune Score as a Novel Prognostic Scoring System for Colorectal Cancer Patients: A Propensity Score Matching Analysis

Aim

The Gustave Roussy Immune Score (GRIm-Score) was originally designed to select cancer patients for immunotherapy, and later was reported to be a novel prognostic scoring system in lung cancer and esophageal cancer. This study was aimed to determine the prognostic role and predictive performance of GRIm-Score in colorectal cancer (CRC) CRC patients.

Methods

We conducted a single-institution study of 1,579 adult CRC patients receiving surgical removal, and those patients were divided into low GRIm-Score group (scores 0, 1) and high GRIm-Score group (scores 2, 3). Propensity score matching (PSM) was executed to balance the potential confounding factors between the two groups. Survival and time-dependent receiver operating characteristic (Td-ROC) analyses were applied to depict the prognostic role and predictive significance of GRIm-Score in CRC patients.

Results

There were 200 cases CRC patients in high GRIm-Score group and 1,379 cases in low GRIm-Score group. CRC patients with high GRIm-Score correspond with higher level of CEA, CA125, and inflammatory indexes, such as NLR, PLR, SII, PNI, and ALRI. Correlation analysis exhibited that GRIm-Score correlated well with the established inflammatory indexes. Survival analysis revealed that CRC patients in high GRIm-Score group showed worse overall survival (OS, P <0.0001) and disease-free survival (DFS, P <0.0001) compared with those in low GRIm-Score group. Results from multivariate Cox regression implicated that high GRIm-Score was not only a potent prognostic index for unfavorable OS (HR = 1.622, 95%CI: 1.118–2.355, P = 0.0109), but also a potent risk factor for worse DFS (HR = 1.743, 95%CI: 1.188–2.558, P = 0.0045). Td-ROC analysis demonstrated that GRIm-Score exhibited the superior discriminatory power in the prediction of OS and DFS when compared to SII, PNI, and ALRI. Such strong associations between high levels of preoperative GRIm-Score and unfavorable survival outcomes remained robust after PSM analysis.

Conclusion

GRIm-Score, a novel inflammatory and nutritional risk scoring system, is a potent prognostic index in CRC patients receiving surgical removal. GRIm-Score can be used as an effective and simplified risk stratification tool for postoperative survival prediction of CRC patients.

Predictive Value of Routine Blood Test in patients with Early Esophageal Cancer: A Matched Case-Control Study

Aims: The present study was to evaluate the diagnostic value of routine blood test as potential inflammatory markers in early esophageal cancer (EEC) patients.

Methods: A matched case-control study was conducted by recruiting 314 patients who were pathologically diagnosed with EEC and then underwent Endoscopic Submucosal Dissection (ESD) from July 2015 to July 2019 in First Affiliated Hospital of Nanjing Medical University. Each EEC patient was matched against one healthy control on the criteria of gender, and age (±2 years). Additionally, a total of 40 subjects (20 cases and 20 controls) were also included in the validation set. Statistical analysis of selected hematological parameters was performed between the two groups. The correlation between preoperative blood indexes and clinicopathological characteristics after ESD in EEC patients were further assessed.

Results: Mono-factor analysis showed that the index of monocyte (p<0.001), MCV (p=0.018), MCH (p=0.01), MPV (p=0.022), PT (p=0.003), PT-INR (p=0.003), PDW (p<0.001) and MLR (p<0.001) were statistically significant in EEC patients when compared with those in healthy controls. Multivariate logistic regression analysis further identified that PDW and MLR was independently associated with the risk of early esophageal cancer (both p<0.001). The higher level of NLR (P=0.007) and MLR (P=0.015) were statistically significant with submucosal invasion in EEC patients and the level of MLR were significantly associated with larger tumor size (P=0.030). The results of the validation group were in consistence with the primary group.

Conclusions: Hematological parameters of MLR and PDW can be used as an adjuvant tool for the diagnosis of EEC. Moreover, the value of MLR can reflect the invasion depth index.

The role of prognostic nutritional index for clinical outcomes of gastric cancer after total gastrectomy

The purpose of this article is to evaluate the relationship between the nutrition-based microenvironment and clinicopathological information for gastric cancer patients and to investigate the prognostic value of nutrition index for gastric cancer patients undergoing total gastrectomy. We retrospectively collected clinical information of 245 gastric cancer patients who underwent total gastrectomy in our hospital between January 1st 2005 and December 30th 2015. According to the prognostic nutritional index (PNI) level, they were divided into low PNI (< 43) group and high PNI (≥ 43) group. The relationship between PNI and the disease-free survival (DFS) and overall survival (OS) were analyzed by statistical analysis. Univariate analyses demonstrated that TNM stage (p = 0.025), patients age (p = 0.042), lymph node metastasis (p = 0.028), tumor differentiation (p = 0.037) and a low PNI (p = 0.033) were closely correlated with a poor prognosis. In multivariate analysis, TNM stage (p = 0.027) and a low PNI (p = 0.041) were found to be independently associated with poor survival. Additionally, when age was considered as a stratified factor, univariate analyses demonstrated that low PNI correlated with shorter DFS in non-elderly (< 65) patients (p = 0.022) and shorter DFS (p = 0.036) and OS (p = 0.047) in elderly (≥ 65) patients. The low prognostic nutritional index is an independent risk factor associated with poor gastric cancer survival which represents the nutritional microenvironment. Patients with low pre-operative prognostic nutritional index levels should be observed more closely after surgery to prevent the occurrence of post-operative complications in the near future.