A novel scoring system associating with preoperative platelet/lymphocyte and clinicopathologic features to predict lymph node metastasis in early gastric cancer

A nomogram based on platelet-to-lymphocyte ratio for predicting lymph node metastasis in patients with early gastric cancer

Background

Preoperative assessment of the presence of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) remains difficult. We aimed to develop a practical prediction model based on preoperative pathological data and inflammatory or nutrition-related indicators.

Methods

This study retrospectively analyzed the clinicopathological characteristics of 1,061 patients with EGC who were randomly divided into the training set and validation set at a ratio of 7:3. In the training set, we introduced the least absolute selection and shrinkage operator (LASSO) algorithm and multivariate logistic regression to identify independent risk factors and construct the nomogram. Both internal validation and external validation were performed by the area under the receiver operating characteristic curve (AUC), C-index, calibration curve, and decision curve analysis (DCA).

Results

LNM occurred in 162 of 1,061 patients, and the rate of LNM was 15.27%. In the training set, four variables proved to be independent risk factors (p < 0.05) and were incorporated into the final model, including depth of invasion, tumor size, degree of differentiation, and platelet-to-lymphocyte ratio (PLR). The AUC values were 0.775 and 0.792 for the training and validation groups, respectively. Both calibration curves showed great consistency in the predictive and actual values. The Hosmer-Lemeshow (H-L) test was carried out in two cohorts, showing excellent performance with p-value >0.05 (0.684422, 0.7403046). Decision curve analysis demonstrated a good clinical benefit in the respective set.

Conclusion

We established a preoperative nomogram including depth of invasion, tumor size, degree of differentiation, and PLR to predict LNM in EGC patients and achieved a good performance.

Construction of a nomogram for preoperative prediction of the risk of lymph node metastasis in early gastric cancer

Background

The status of lymph node metastasis (LNM) in patients with early gastric cancer (EGC) is particularly important for the formulation of clinical treatment. The purpose of this study was to construct a nomogram to predict the risk of LNM in EGC before operation.

Methods

Univariate analysis and logistic regression analysis were used to determine the independent risk factors for LNM. The independent risk factors were included in the nomogram, and the prediction accuracy, discriminant ability and clinical practicability of the nomogram were evaluated by the receiver operating characteristic curve (ROC), calibration curve and clinical decision curve (DCA), and 100 times ten-fold cross-validation was used for internal validation.

Results

33 (11.3%) cases of AGC were pathologically confirmed as LNM. In multivariate analysis, T stage, presence of enlarged lymph nodes on CT examination, carbohydrate antigen 199 (CA199), undifferentiated histological type and systemic inflammatory response index (SIRI) were risk factors for LNM. The area under the ROC curve of the nomogram was 0.86, the average area under the ROC curve of the 100-fold ten-fold cross-validation was 0.85, and the P value of the Hosmer-Lemeshow test was 0.60. In addition, the clinical decision curve, net reclassification index (NRI) and Integrated Discriminant Improvement Index (IDI) showed that the nomogram had good clinical utility.

Conclusions

We found that SIRI is a novel biomarker for preoperative prediction of LNM in EGC, and constructed a nomogram for preoperative prediction of the risk of LNM in EGC, which is helpful for the formulation of the clinical treatment strategies.

Association between neutrophil-lymphocyte ratio and lymph node metastasis in gastric cancer: A meta-analysis

INTRODUCTION AND AIM

The prognostic role of neutrophil to lymphocyte ratio (NLR) has been explored extensively in the literature. The aim of this meta-analysis was to evaluate the link between NLR and lymph node metastasis in gastric cancer. A method for increasing specificity and sensitivity of pre-treatment staging has implications on treatment algorithms and survival.

SEARCH STRATEGY

The relevant databases were searched as per the Preferred Reporting Items for Systematic Reviews and Meta-Analyses flowchart. After selection, 12 full text articles that met the inclusion criteria were included for quantitative analysis. 2 × 2 squares were generated using lymph node positive/negative, and NLR high/low data. The effect size for each study was calculated using the DerSimonian-Laird random effects model. P values were calculated using the chi-square method. Finally publication bias was evaluated. All statistics were calculated using R Studio.

RESULTS

Meta-analysis showed a 1.90 times (odds ratio, with 95% CI 1.52-2.38) increase in risk of positive lymph node status with high neutrophil to lymphocyte ratio. This has significant implications for cancer screening and staging, as NLR is a highly reproducible, cost-effective, and widely available prognostic factor for gastric cancer patients. Additionally, high or low NLR values may have implications for management pathways. Patients with lymph node metastasis can be offered neoadjuvant chemotherapy, avoiding salvage therapy in the form of adjuvant chemoradiotherapy, which is poorly tolerated.

CONCLUSION

This meta-analysis shows an association between NLR and positive lymph node status in gastric cancer patients with implications for staging, as well as preoperative personalisation of therapy.

Predictive value of neutrophil-to-lymphocyte ratio for distant metastasis in gastric cancer patients

As a systemic inflammatory marker, the significance of NLR in predicting tumor prognosis and early lymph node metastasis is well known, including gastric cancer (GC). However, whether NLR can reflect GC metastasis status remains to be explored. We retrospectively enrolled 1667 GC patients treated in our hospital from December 2010 to December 2018. Patients were grouped according to the presence or absence of metastases. Receiver operating characteristics (ROC) curve analysis was used to evaluate the diagnostic efficacy of markers in assessing GC metastasis. Then we conducted a joint ROC curve analysis. The effects of clinicopathological parameters on GC metastasis were assessed using multiple logistic regression analysis. 743 (44.6%) patients were diagnosed with metastatic GC. Patients with GC metastases have younger age, higher CEA, CA19-9, CA72-4 and NLR. Based on the comparison of AUC, NLR has diagnostic efficacy comparable to that of GC markers. The AUC of NLR combined with GC markers had significantly higher predicting efficacy than that without combination for assessing peritoneal metastasis (P = 0.013), osseous metastasis (P = 0.017) and hepatic metastasis (P < 0.001). In multiple logistic regression analysis, age, NLR, CEA, CA19-9 and CA72-4 were found to be independently associated with GC metastasis (all P < 0.05). NLR was a risk factor of GC metastasis. Combining CEA, CA19-9, CA72-4 and NLR could better predict metastases in GC.

Inflammation-related indicators to distinguish between gastric stromal tumors and leiomyomas: A retrospective study

BACKGROUND

Gastric leiomyomas and gastric stromal tumors are the most common types of gastric tumors encountered. In recent years, the incidence of the two types of tumors has been increasing, but the differential diagnosis is still a challenge in clinical work. However, as there are many reports on stromal tumors and inflammation-related indicators are gradually being paid attention to as important factors in predicting tumor prognosis, the two main purposes of this study were to explore the inflammation-related differences between the two types of tumors and to develop a nomogram as a predictive model.

AIM

To explore the differences in platelet-lymphocyte ratio (PLR), neutrophil-lymphocyte ratio (NLR), lymphocyte mononuclear cell ratio (LMR), and SII between the two types of tumors, and simultaneously create the nomogram model.

METHODS

This study enrolled 88 patients in the gastric stromal tumor group and 56 patients in the gastric leiomyoma group, and the relevant data of the two groups were entered into the system for an integrated analysis. The primary objective of this study was to identify the differences in the inflammation index between the two types of tumors.

RESULTS

There were statistically significant differences between the two groups in sex, age, and tumor location. In comparison, gastric leiomyomas seem to be more common in women, young patients, and gastric cardia, which is in line with our previous research; the groups showed the following statistical differences: PLR (158.2% vs 134.3%, P = 0.028), NLR (2.35 vs 1.68, P = 0.000), LMR (5.75 vs 10.8, P = 0.004), and SII (546.2 vs 384.3, P = 0.003). The results of the multivariate logistic regression analysis showed that sex, age, tumor location, and LMR were independent risk factors for the identification of the two types of tumors. After considering the risk factors selected by the above analysis into the predictive model, a predictive model for distinguishing gastrointestinal stromal tumors from gastric leiomyomas was established as the nomogram.

CONCLUSION

Gastric leiomyomas and gastric stromal tumors are not only different in factors such as age of the patient, but also in inflammatory indicators such as LMR and PLR. We have established a predictive model related to the laboratory indicators and are looking forward to further research conducted in this clinical area.

A novel robust nomogram based on preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) for predicting lymph node metastasis of gastric cancer

BACKGROUND

Accurate assessment of lymph node status in gastric cancer (GC) patients can help to select appropriate treatment strategies for GC, but the diagnostic accuracy of conventional methods needs to be improved. The aim of this study was to investigate the predictive value of preoperative hemoglobin and albumin levels and lymphocyte and platelet counts (HALP) on lymph node status in GC patients and to construct a risk prediction model.

METHODS

This study retrospectively analyzed the clinicopathological characteristics of 349 patients with GC who underwent radical gastrectomy, among which 250 patients were recruited in the training cohort and 99 patients in the independent validation cohort. Significant risk factors in univariate analysis were further identified as independent variables in multivariate logistic regression analysis, which were then incorporated and presented in a nomogram. Receiver operating characteristic (ROC) curves, Calibration curve and decision curve analysis (DCA) curves were used to evaluate the discrimination, prediction accuracy and clinical effectiveness of the model.

RESULTS

Multifactorial logistic regression analysis showed that alcohol use (OR =2.203, P=0.036), Depth of invasion (OR =7.756, P<0.001), differentiation (OR =2.252, P=0.018), carcinoembryonic antigen (CEA) (OR =2.443, P=0.017), carbohydrate antigen 19-9 (CA199) (OR =2.715, P=0.008) and HALP (OR =2.276, P=0.032) were independent risk factors for lymph node metastasis (LNM) in GC. We used these factors to construct a nomogram for predicting LNM in GC patients, and the ROC curves showed good discrimination of the model with AUC values of 0.854 (training cohort) and 0.868 (validation cohort), respectively, and the calibration curves showed good predictive ability of the nomogram, in addition to the DCA curves results showed the clinical usefulness of the model.

CONCLUSIONS

In conclusion, we established a nomogram for predicting LNM in patients with GC.

Platelet-to-lymphocyte ratio and C-reactive protein as markers for colorectal polyp histological type

Background

The platelet-to-lymphocyte ratio (PLR) and C-reactive protein (CRP) level are markers that have been reported to predict the histological type of various tumors, and here, we evaluated their utility in predicting colorectal polyp histological types.

Methods

We retrospectively reviewed 172 patients with colorectal polyps who underwent endoscopic polypectomy. The associations between histological type and clinicopathologic parameters were assessed by multivariate analysis.

Results

The optimal PLR and CRP cut-off values were 113.32 and 0.39, respectively. The PLR (P = 0.002) and CRP (P = 0.009) values were associated with the histological type according to the univariate analysis, whereas low PLR (P ≤ 0.001) and CRP (P = 0.017) values were independent risk factors in the multivariate analysis together with maximum tumor diameter (P ≤ 0.001) and tumor number (P = 0.0014).

Conclusions

Preoperative PLR and CRP are correlated with the colorectal polyp histological type.

Preoperative Platelet-to-Lymphocyte Ratio (PLR) for Predicting the Survival of Stage I-III Gastric Cancer Patients with a MGC Component

Background

The preoperative platelet-to-lymphocyte ratio (PLR) evaluates the prognosis of gastric cancer patients. However, whether preoperative PLR may be used to evaluate the prognosis of mucinous gastric carcinoma (MGC) patients is poorly investigated. The present study evaluated the effect of preoperative PLR on overall survival in gastric cancer patients with a mucinous component.

Methods

A total of 336 MGC were enrolled in this study, and the characteristics of the tumor, including pathological features and clinical data, were retrospectively analyzed.

Results

A high PLR was associated with larger tumor size, advanced tumor invasion, lymph node metastasis, advanced TNM stage, tumor location, total gastrectomy, low hemoglobin level, low albumin level, high fibrinogen level, high platelet level, and high neutrophil-to-lymphocyte ratio (NLR, all P's < 0.05). Multivariate analysis identified age (HR = 1.876; 95% CI 1.361-2.585, P < 0.001), TNM stage (HR = 2.350; 95% CI 1.216-4.542, P = 0.011), globulin (HR = 1.520; 95% CI 1.067-2.165, P = 0.020), total gastrectomy (HR = 0.537; 95% CI 0.373-0.772, P = 0.001), and PLR (HR = 1.582; 95% CI 1.066-2.348, P = 0.023) as independent prognostic factors for OS.

Conclusion

Preoperative PLR is related to pathological features and may independently evaluate the survival of MGC. Therefore, preoperative PLR may help physicians develop treatment plans and evaluate survival in these patients.

A genomic-clinicopathologic Nomogram for the preoperative prediction of lymph node metastasis in gastric cancer

BACKGROUND

Preoperative evaluation of lymph node (LN) state is of pivotal significance for informing therapeutic decisions in gastric cancer (GC) patients. However, there are no non-invasive methods that can be used to preoperatively identify such status. We aimed at developing a genomic biosignature based model to predict the possibility of LN metastasis in GC patients.

METHODS

We used the RNA profile retrieving strategy and performed RNA expression profiling in a large GC cohort (GSE62254, n = 300) from Gene Expression Ominus (GEO). In the exploratory stage, 300 GC patients from GSE62254 were involved and the differentially expressed RNAs (DERs) for LN-status were determined using the R software. GC samples in GSE62254 were randomly allocated into a learning set (n = 210) and a verification set (n = 90). By using the Least absolute shrinkage and selection operator (LASSO) regression approach, a set of 23-RNA signatures were established and the signature based nomogram was subsequently built for distinguishing LN condition. The diagnostic efficiency, as well as the clinical performance of this model were assessed using the decision curve analysis (DCA). Metascape was used for bioinformatic analysis of the DERs.

RESULTS

Based on the genomic signature, we established a nomogram that robustly distinguished LN status in the learning (AUC = 0.916, 95% CI 0.833-0.999) and verification sets (AUC = 0.775, 95% CI 0.647-0.903). DCA demonstrated the clinical value of this nomogram. Functional enrichment analysis of the DERs was performed using bioinformatics methods which revealed that these DERs were involved in several lymphangiogenesis-correlated cascades.

CONCLUSIONS

In this study, we present a genomic signature based nomogram that integrates the 23-RNA biosignature based scores and Lauren classification. This model can be utilized to estimate the probability of LN metastasis with good performance in GC. The functional analysis of the DERs reveals the prospective biogenesis of LN metastasis in GC.

Construction and Validation of a Risk-Scoring Model that Preoperatively Predicts Lymph Node Metastasis in Early Gastric Cancer Patients

OBJECTIVE

The aim of this study was to create a risk-scoring model to preoperatively predict the incidence of lymph node metastasis (LNM) in early gastric cancer (EGC) patients to guide treatment.

METHODS

To construct the risk-scoring model, we retrospectively analyzed a primary cohort of 548 EGC patients. Univariate analysis and logistic regression were performed. A risk-scoring model for predicting LNM in EGC patients was developed based on preoperative factors, and another cohort of 73 patients was then analyzed to validate the model.

RESULTS

In the primary cohort, LNM was pathologically confirmed in 72 (13.1%) patients. In the multivariate analysis, the presence of ulceration and tumor size on gastroscopy, undifferentiated histological type, and presence of enlarged lymph nodes on computed tomography or endoscopic ultrasonography were independent risk factors for LNM. A 17-point risk-scoring model was developed to predict LNM risk. The cut-off score of the model was 8, and the area under the receiver operating characteristic curve (AUC) of the model was 0.835 [95% confidence interval (CI) 0.784-0.886]. In the validation cohort, the AUC of the model was 0.829 (95% CI 0.699-0.959).

CONCLUSIONS

We developed and validated an effective 17-point risk-scoring model that could preoperatively predict LNM for EGC patients.

Clinical significance of peripheral blood-derived inflammation markers in advanced gastric cancer after radical resection

Background

The prognostic significance of peripheral blood-derived inflammation markers in patients with gastric cancer (GC) has not been elucidated. This study aimed to investigate the relationship between systemic inflammatory markers and GC prognosis.

Methods

A prospective observational cohort study involving 598 patients was conducted to analyze the prognosis of GC based on systemic inflammatory markers. The following peripheral blood-derived inflammation markers were evaluated: the neutrophil-lymphocyte ratio (NLR), platelet lymphocyte ratio (PLR), systemic immune-inflammation index (SII), C-reactive protein/albumin (CRP/Alb) ratio, Glasgow Prognostic Score (GPS), modified Glasgow Prognostic Score (mGPS), prognostic nutrition index (PNI), and prognostic index (PI). The receiver operating characteristics (ROC) curve and the Youden index were used to determine the optimal cutoff values. Univariate and multivariate analysis of prognostic factors was conducted accordingly.

Results

The optimal cutoff values of the PNI, fibrinogen, NLR, PLR, SII, and CRP/Alb were 49.5, 397 ng/dl, 2.5, 154, 556, and 0.05, respectively. Multivariate analysis showed that age, PLR, TNM stage, and chemotherapy were the independent prognostic factors for advanced gastric cancer (AGC). Adjuvant chemotherapy improved the long-term prognosis of patients with PLR ≥154, but chemotherapy had no significant effect on the survival of patients with PLR < 154.

Conclusions

Our findings show that higher PLR (≥154) is an independent risk factor for poor prognosis in GC patients. Besides, PLR can predict adjuvant chemotherapy (oxaliplatin/5-fluorouracil combination) response in patients with GC after surgery.

Tumor-Associated Neutrophils Can Predict Lymph Node Metastasis in Early Gastric Cancer

The consensus of endoscopic therapy for early gastric cancer (EGC) mainly depends on its clinicopathological features. However, the roles of tumor-associated neutrophils (TANs) in EGC remain uncertain. Here, we explored its predictive role for lymph node metastasis (LNM) in EGC. Three hundred twenty-two patients who underwent radical gastrectomy for EGC were enrolled. Preoperative peripheral blood was used to analyze the neutrophil-to-lymphocyte ratio (NLR), and the different status of TANs was determined by hematoxylin-and-eosin staining (H&E) and immunohistochemistry (IHC). TANs, rather than NLR, were positively associated with tumor size, Lauren classification, lymphovascular invasion (LVI), and LNM. Univariate analysis revealed that TANs were associated with LNM as well as tumor size, depth of invasion, Lauren classification, histological classification, LVI, and perineural invasion. In addition to histological classification and LVI, TANs were found to be an independent risk factor for LNM in EGC (P = 0.013). Stratification analysis by depth of invasion showed LVI in SM1 tumor, and both LVI and TANs (P = 0.042) in SM2 tumor were independent risk factors for LNM. In conclusion, TANs in EGC can predict LNM, and TANs may help to estimate LNM precisely in addition to the current criteria.

Clinicopathological and prognostic significance of platelet-lymphocyte ratio (PLR) in gastric cancer: an updated meta-analysis

BACKGROUND

Pre-treatment PLR (platelet-lymphocyte ratio) was reported to be associated with the prognosis in gastric cancer (GC), but the results remain inconclusive. This meta-analysis aimed to investigate the prognostic potential of the pre-treatment PLR in gastric cancer.

METHODS

We performed a systematic literature search in PubMed, Embase, and the Cochrane Library to identify eligible publications. The hazard ratio (HR)/odds ratio (OR) and its 95% confidence (CI) of survival outcomes and clinicopathological parameters were calculated.

RESULTS

A total of 49 studies (51 cohorts), collecting data from 28,929 GC patients, were included in the final analysis. The pooled results demonstrated that the elevated pre-treatment PLR was significantly associated with poor overall survival (OS) (HR 1.37, 95% CI 1.26-1.49, p < 0.001; I² = 79.90%, P_h < 0.001) and disease-free survival (DFS) (HR 1.52, 95% CI 1.22-1.90, p < 0.001, I² = 88.6%, P_h < 0.001). Furthermore, the patients with the elevated PLR had a higher risk of lymph node metastasis (OR = 1.17, 95% CI 1.02-1.33, p = 0.023), serosal invasion (T3+T4) (OR = 1.34, 95% CI 1.10-1.64, p = 0.003), and increased advanced stage (III+IV) (OR = 1.20, 95% CI 1.06-1.37, p = 0.004).

CONCLUSIONS

An elevated pre-treatment PLR was a prognostic factor for poor OS and DFS and associated with poor clinicopathological parameters in GC patients.

Integrating tumor and nodal radiomics to predict lymph node metastasis in gastric cancer

BACKGROUND

To develop and validate a radiomics method via integrating tumor and lymph node radiomics for the preoperative prediction of lymph node (LN) status in gastric cancer (GC).

MATERIALS AND METHODS

We retrospectively collected 170 contrast-enhanced abdominal CT images from GC patients. Five times repeated random hold-out experiment was employed. Tumor and nodal radiomics features were extracted from each individual tumor and LN respectively, and then multi-step feature selection was performed. The optimal tumor and nodal features were selected using Pearson correlation analysis and sequential forward floating selection (SFFS) algorithm. After feature fusion, the SFFS algorithm was used to develop radiomics signatures. The performance of the radiomics signatures developed based on logistic regression classifier was further analyzed and compared using the area under the receiver operating characteristic curve (AUC).

RESULTS

The AUC values, reported as mean ± standard deviation, were 0.9319 ± 0.0129 and 0.8546 ± 0.0261 for the training and validation cohorts respectively. The radiomic signatures could predict LN status, especially in T2-stage, diffuse-type and moderately/well differentiated GC. After integrating clinicopathologic information, the radiomic-clinicopathologic model (training cohort, 0.9432 ± 0.0129; validation cohort, 0.8764 ± 0.0322) showed a better discrimination capability than other radiomics models and clinicopathologic model. The radiomic-clinicopathologic model also showed superior performance to the gastroenterologist' decision in all experiments, and outperformed the radiologist in some experiments.

CONCLUSION

Our proposed method presented good predictive performance and great potential for predicting LNM in GC. As a noninvasive preoperative prediction tool, it can be helpful for guiding the prognosis and treatment decision-making in GC patients.

A preoperative risk model for early recurrence after radical resection may facilitate initial treatment decisions concerning the use of neoadjuvant therapy for patients with pancreatic ductal adenocarcinoma

BACKGROUND

Neoadjuvant chemotherapy may benefit patients with pancreatic ductal adenocarcinoma with resectable and borderline disease. Inappropriate use of neoadjuvant therapy, however, may lead to the loss of therapeutic opportunities. Until an effective prediction model of individual drug sensitivity is established, no accurate model exists to help surgeons decide on the appropriate use of neoadjuvant chemotherapy. We hypothesized that early recurrence in patients undergoing upfront, early resection may be an indication for neoadjuvant chemotherapy. Therefore, we aimed to use preoperative clinical parameters to establish a model of early recurrence to select patients at high risk for neoadjuvant chemotherapy.

METHODS

Patients who underwent resection for pancreatic ductal adenocarcinoma between January 2014 and November 2017 were analyzed retrospectively. After the minimum P-value approach, the patients were divided into three groups: early recurrence, middle recurrence, and late/non-recurrence. Preoperative clinicopathologic factors that could predict early recurrence were included in a Cox proportional hazards regression model for univariate and multivariate analyses. The factors related to early recurrence were included to establish nomogram and decision tree models, which were then validated in 68 patients.

RESULTS

We found that 235 (72.5%) of 324 patients had recurrence with a median recurrence-free survival of 210 days. The early recurrence, middle recurrence, and late/non-recurrence groups differed in preoperative carbohydrate antigen 19-9 and carcinoembryonic antigen levels, "resectability" on cross-sectional imaging, resection requiring a vascular resection, T stage, tumor size, and adjuvant chemotherapy. The best cutoff value of early recurrence was the first 162 days postoperatively. Univariate and multivariate analyses showed that selected preoperative chief complaints, lymph node enlargement and resectability on cross-sectional imaging, preoperative carbohydrate antigen 19-9 levels >210 kU/L, and a neutrophil/lymphocyte ratio >4.2 were independent predictors for early recurrence.

CONCLUSION

We have successfully built a prediction model of early recurrence of patients with pancreatic ductal adenocarcinoma with the optimal cutoff early-recurrence value of 162 days. Our nomogram and decision tree models may be used to select those at high risk for early recurrence to guide preoperative decision-making concerning the use of neoadjuvant therapy in those patients who have "resectable" disease and not only the more classic criteria of borderline resectability.

Significance of CT attenuation and F-18 fluorodeoxyglucose uptake of visceral adipose tissue for predicting survival in gastric cancer patients after curative surgical resection

BACKGROUND

The purpose of this study was to investigate the prognostic significance of computed tomography (CT) attenuation and F-18 fluorodeoxyglucose (FDG) uptake of visceral adipose tissue (VAT) to predict peritoneal recurrence-free survival (RFS) as well as RFS and overall survival (OS) in patients with advanced gastric cancer (AGC).

METHODS

We retrospectively enrolled 117 patients with AGC who underwent staging FDG positron emission tomography (PET)/CT and subsequent curative surgical resection. CT attenuation and FDG uptake (SUV) of VAT and maximum FDG uptake of primary tumor (SUVmaxT) were measured from PET/CT images. The relationship of VAT attenuation and SUV with clinico-histopathologic factors and survival was assessed.

RESULTS

There was a significant positive correlation between VAT attenuation and SUV (p < 0.001, r = 0.799). In correlation analyses, both VAT attenuation and SUV showed significant positive correlations with T stage, TNM stage, tumor size, and platelet-to-lymphocyte ratio (p < 0.05), and patients who experienced recurrence during the first 3-year after surgery had significantly higher VAT attenuation and SUV than those who had no recurrence (p < 0.05). Patients with high VAT attenuation and SUV showed significantly worse RFS, peritoneal RFS, and OS than those with low values (p < 0.05). On multivariate survival analysis, VAT attenuation was significantly associated with peritoneal RFS and OS and VAT SUV was significantly associated with OS (p < 0.05).

CONCLUSIONS

CT attenuation and FDG uptake of VAT on staging FDG PET/CT were correlated with tumor characteristics and were significant predictive factors for peritoneal RFS and OS in patients with AGC.

The value of preoperative lymphocytes-to-monocytes ratio in predicting lymph node metastasis in gastric cancer

Background

This study was aimed to evaluate value of preoperative lymphocytes-to-monocytes ratio (LMR) as a predictor for lymph node metastasis in gastric cancer.

Methods

Patients with pathologically diagnosed malignant gastric tumor were reviewed retrospectively. Patients’ demographic data, clinical manifestations and LMR were collected. The postoperative pathology data including the tumor size, tumor sites, differentiation degree of tumor, depth of tumor invasion, metastatic lymph nodes, total dissected lymph nodes, distant metastasis, vessel carcinoma embolus, neural invasion, Lauren’s classification, Ki-67 and TNM stage were collected. Receiver operating characteristic curve (ROC) was used to determine the cut-off point of LMR. The association between LMR and the clinicopathologic factors was further analyzed.

Results

A total of 177 subjects were enrolled into the study. LMR =3.79 was used as cut-off point; the patients with LMR ≥3.79 were classified as high-LMR group (123 cases) and the patients with LMR <3.79 as low-LMR group (54 cases). LMR was an independent risk factor for lymph node metastasis.

Conclusions

Low preoperative LMR was positively correlated with lymph node metastasis in gastric cancer patients, and had predictive value for lymph node metastasis in gastric cancer patients.

A Risk-Scoring Model for Predicting Lymph Node Metastasis in Early Gastric Cancer Patients: a Retrospective Study and External Validation

BACKGROUND

The possibility of lymph node metastasis (LNM) is critical to the assessment of the indication for endoscopic submucosal dissection. Thus, the aim of this study is to identify the risk factors for LNM and construct a risk-scoring model for patients with early gastric cancer to guide treatment.

METHODS

A retrospective examination of reports and studies carried out January 2000 and December 2014 was conducted. A risk-scoring model for predicting LNM was developed based on the data thus collected. In addition, the model is subject to verification and validation by three institutions.

RESULTS

Of the 1029 patients, 228 patients (22%) had LNM. Multivariate analysis showed that female, depressed type, undifferentiated type, submucosa, tumor size, and lymphovascular invasion were significantly associated with LNM. An 11-point risk-scoring model was used to predict LNM risk. An area under the receiver operating characteristic (AUROC) of the risk-scoring model was plotted using the development set and the AUROC of the model [0.76 (95% CI 0.73-0.80)] to predict LNM risk. After internal and external validation, the AUROC curve for predicting LNM was 0.77 (95% CI 0.68-0.86), 0.82 (95% CI 0.72-0.91), and 0.82 (95% CI 0.70-0.94), respectively.

CONCLUSIONS

A risk-scoring model for predicting LNM was developed and validated. It could help with personalized care for patients with EGC.