The Role of the Lymph Node Ratio in Advanced Gastric Cancer After Neoadjuvant Chemotherapy

Comparison of the predictive performance of three lymph node staging systems for late-onset gastric cancer patients after surgery

Introduction

Lymph node (LN) status is a vital prognostic factor for patients. However, there has been limited focus on predicting the prognosis of patients with late-onset gastric cancer (LOGC). This study aimed to investigate the predictive potential of the log odds of positive lymph nodes (LODDS), lymph node ratio (LNR), and pN stage in assessing the prognosis of patients diagnosed with LOGC.

Methods

The LOGC data were obtained from the Surveillance, Epidemiology, and End Results database. This study evaluated and compared the predictive performance of three LN staging systems. Univariate and multivariate Cox regression analyses were carried out to identify prognostic factors for overall survival (OS). Three machine learning methods, namely, LASSO, XGBoost, and RF analyses, were subsequently used to identify the optimal LN staging system. A nomogram was built to predict the prognosis of patients with LOGC. The efficacy of the model was demonstrated through receiver operating characteristic (ROC) curve analysis and decision curve analysis.

Results

A total of 4,743 patients with >16 removed lymph nodes were ultimately included in this investigation. Three LN staging systems demonstrated significant performance in predicting survival outcomes (P < 0.001). The LNR exhibited the most important prognostic ability, as evidenced by the use of three machine learning methods. Utilizing independent factors derived from multivariate Cox regression analysis, a nomogram for OS was constructed.

Discussion

The calibration, C-index, and AUC revealed their excellent predictive performance. The LNR demonstrated a more powerful performance than other LN staging methods in LOGC patients after surgery. Our novel nomogram exhibited superior clinical feasibility and may assist in patient clinical decision-making.

Proximal gastric cancer-time for organ-sparing approach?

BACKGROUND

A steady increase in gastroesophageal junction and proximal gastric cancer (GC) incidence has been observed in the West. Given recent advances in neoadjuvant chemotherapy (NAC), we sought to characterize short- and long-term outcomes of patients with proximal GC who underwent total (TG) vs proximal gastrectomy (PG).

METHODS

Patients with stage II/III proximal GC who underwent curative-intent treatment between 2009 and 2019 were identified using National Cancer Database. Multivariable analysis was used to identify oncologic outcomes after TG vs PG.

RESULTS

Among 7616 patients with GC who underwent surgical resection, PG and TG were performed on 5246 (68.8%) and 2370 patients (31.2%), respectively. Patients who underwent PG were more likely to receive NAC (TG 52.3% vs PG 64.5%) (P < .001). On pathologic analysis, patients who underwent TG were more likely to have pT4 tumors (TG 11.7% vs PG 3.1%), metastatic lymph nodes (LNs) (TG 64.6% vs PG 60.4%), and >16 LNs evaluated (TG 64.1% vs PG 53.1%), yet a lower likelihood of negative resection margins (TG 86.6% vs PG 90.0%) (all P < .001). Although gastrectomy procedure type did not affect long-term survival, receipt of NAC was associated with overall survival (OS) among patients who underwent TG (5-year OS, NAC 43.5% vs no NAC 24.6%) and PG (5-year OS, NAC 43.1% vs no NAC 26.7%) (both P < .001).

CONCLUSION

PG may be an alternative surgical approach to TG in well-selected patients with proximal GC after administration of preoperative systemic chemotherapy.

Prediction of lymph node metastasis in advanced gastric adenocarcinoma based on dual-energy CT radiomics: focus on the features of lymph nodes with a short axis diameter ≥6 mm

Objective

To explore the value of the features of lymph nodes (LNs) with a short-axis diameter ≥6 mm in predicting lymph node metastasis (LNM) in advanced gastric adenocarcinoma (GAC) based on dual-energy CT (DECT) radiomics.

Materials and methods

Data of patients with GAC who underwent radical gastrectomy and LN dissection were retrospectively analyzed. To ensure the correspondence between imaging and pathology, metastatic LNs were only selected from patients with pN3, nonmetastatic LNs were selected from patients with pN0, and the short-axis diameters of the enrolled LNs were all ≥6 mm. The traditional features of LNs were recorded, including short-axis diameter, long-axis diameter, long-to-short-axis ratio, position, shape, density, edge, and the degree of enhancement; univariate and multivariate logistic regression analyses were used to establish a clinical model. Radiomics features at the maximum level of LNs were extracted in venous phase equivalent 120 kV linear fusion images and iodine maps. Intraclass correlation coefficients and the Boruta algorithm were used to screen significant features, and random forest was used to build a radiomics model. To construct a combined model, we included the traditional features with statistical significance in univariate analysis and radiomics scores (Rad-score) in multivariate logistic regression analysis. Receiver operating curve (ROC) curves and the DeLong test were used to evaluate and compare the diagnostic performance of the models. Decision curve analysis (DCA) was used to evaluate the clinical benefits of the models.

Results

This study included 114 metastatic LNs from 36 pN3 cases and 65 nonmetastatic LNs from 28 pN0 cases. The samples were divided into a training set (n=125) and a validation set (n=54) at a ratio of 7:3. Long-axis diameter and LN shape were independent predictors of LNM and were used to establish the clinical model; 27 screened radiomics features were used to build the radiomics model. LN shape and Rad-score were independent predictors of LNM and were used to construct the combined model. Both the radiomics model (area under the curve [AUC] of 0.986 and 0.984) and the combined model (AUC of 0.970 and 0.977) outperformed the clinical model (AUC of 0.772 and 0.820) in predicting LNM in both the training and validation sets. DCA showed superior clinical benefits from radiomics and combined models.

Conclusion

The models based on DECT LN radiomics features or combined traditional features have high diagnostic performance in determining the nature of each LN with a short-axis diameter of ≥6 mm in advanced GAC.

KBTBD2 promotes proliferation and migration of gastric cancer via activating EGFR signaling pathway

BACKGROUND

To explore the role of Kelch repeat and BTB (POZ) domain containing 2 (KBTBD2) in Gastric cancer(GC) via studying the level of KBTBD2 and its impact on GC cells and mice model.

METHODS

Expression of KBTBD2 in GC was analyzed by analysis of TCGA data, Western blotting and Real-time quantitative polymerasechain reaction (RT-qPCR). The role of KBTBD2 on GC cells proliferation, viability, invasion, migration and apoptosis in vitro were assessed by using western blotting，RT-qPCR，CCK-8, EDU, Colony Formation Assay, Wound healing assay, Transwell, JC-1 mitochondrial membrane potential and flow cytometry assay, respectively. And levels of Bcl-2, BAX, PARP, E-cadherin, Vimentin, N-cadherin, EGFR, SOS1, NROS, BRAF,ERK1/2 and GAPDH were tested by western blotting. Relation of KBTBD2 and epidermal growth factor receptor (EGFR) was predicted by KEGG analysis. KBTBD2 gene GSEA enrichment was analyzed by using R language. Moreover, CCK-8, western blotting, and wound healing assays were used to verify the correlation of KBTBD2 and EGFR pathway. Finally, tumor growth in mice was also investigated. Cells proliferation, migration and apoptosis were detected by Ki67 staining, Tunnel staining and mouse lung metastasis model.

RESULTS

KBTBD2 was highly expressed in GC, and was related to poor prognosis. Moreover, silencing KBTBD2 suppressed GC cell proliferation, migration and invasion, while also inhibited the EMT, but promoted apoptosis. At the same time, KBTBD2 overexpression showed opposite results. In addition, KBTBD2 regulated the EGFR pathway. Further, silencing KBTBD2 inhibited tumor growth, cell proliferation and migration but promoted apoptosis in vivo, and KBTBD2 overexpression showed opposite results.

CONCLUSIONS

KBTBD2 was highly expressed in GC. KBTBD2 promotes the progress of GC by activating EGFR signal pathway. KBTBD2 may thus be a novel target for treating GC.

Hyperthermic Intraperitoneal Chemotherapy (HIPEC), Oncological Outcomes and Long-Term Survival among Patients with Gastric Cancer and Limited Peritoneal Disease Progression after Neoadjuvant Chemotherapy

INTRODUCTION

The role of surgery in stage IV gastric cancer with peritoneal metastasis (PM) remains unclear. The objective of the current single-center study was to define the impact of gastrectomy with cytoreductive surgery (CRS) and hyperthermic intraperitoneal chemotherapy (HIPEC) on outcomes among Central European GC patients with limited peritoneal disease progression after neoadjuvant chemotherapy (NAC).

METHODS

Patients with histologically confirmed GC who underwent curative-intent multimodal treatment between 2013 and 2023 were included. Patients without adenocarcinoma, who did not undergo gastrectomy, had early (cT1) or metastatic GC at the time of initial diagnosis, who underwent multivisceral resection, incomplete cytoreduction or palliative care, died before planned curative-intent treatment, or had incomplete clinical or pathological missing information were excluded.

RESULTS

A total of 74 patients who underwent curative-intent treatment for GC with PM were included in the final analytic cohort. Patients who underwent gastrectomy with CRS+HIPEC were less likely to achieve TOO (CRS+HIPEC: 28% vs. CRS: 57.1%, p = 0.033) compared with individuals after CRS alone. Specifically, patients who underwent gastrectomy with CRS+HIPEC had a higher likelihood of postoperative complications (CRS+HIPEC: 48% vs. CRS: 20.4%, p = 0.018) and longer hospital LOS (median, CRS+HIPEC: 12 vs. CRS: 10, p = 0.019). While administration of HIPEC did not impact long-term survival (median OS, CRS+HIPEC: 16 months vs. CRS: 12 months, p = 0.55), postoperative complications (median OS, CCI < 30:16 months vs. CCI > 30:5 months, p = 0.024) and ICU stay (median OS, no ICU stay: 16 months vs. ICU stay: 5 months, p = 0.008) were associated with worsened long-term survival among GC patients with PM.

CONCLUSIONS

Data from the current study demonstrated a lack of survival benefit among advanced GC patients with PM undergoing gastrectomy with CRS+HIPEC when compared with individuals after gastrectomy with CRS alone. Administration of perioperative chemotherapy and achievement of TO failed to withstand the peritoneal disease progression during NAC.

Log odds of positive lymph nodes as a novel prognostic predictor for gastric cancer: a systematic review and meta-analysis

BACKGROUND

We conducted a systematic review and meta-analysis to summarize the predictive and prognostic ability of the log odds of positive lymph nodes (LODDS) staging system and compare it with pathological N (pN) classification and the ratio-based lymph node system (rN) for the overall survival (OS) of gastric cancer (GC).

METHODS

Through a systematic review till March 7, 2022, we identified population-based studies that reported the prognostic effects of LODDS in patients with GC. We compare the predictive effectiveness of the LODDS staging system with that of the rN and pN classification systems for the OS of GC.

RESULTS

Twelve studies comprising 20,312 patients were included in this systematic review and meta-analysis. The results showed that LODDS1, LODDS2, LODDS3, and LODDS4 in GC patients were correlated with poor OS compared with LODDS0 (LODDS1 vs. LODDS0: HR = 1.62, 95% CI (1.42, 1.85); LODDS2 vs. LODDS0: HR = 2.47, 95% CI (2.02, 3.03); LODDS3 vs. LODDS0: HR = 3.15, 95% CI (2.50, 3.97); LODDS4 vs. LODDS0: HR = 4.55, 95% CI (3.29, 6.29)). Additionally, significant differences in survival were observed among patients with different LODDS classifications (all P-values were < 0.001) with the same rN and pN classifications. Meanwhile, for patients with different pN or rN classifications with the same LODDS classification, prognosis was highly similar.

CONCLUSION

The findings show that LODDS is correlated with the prognosis of GC patients and is superior to the pN and rN classifications for prognostic assessment.

Development and validation of prognostic model based on extragastric lymph nodes metastasis and lymph node ratio in node-positive gastric cancer: a retrospective cohort study based on a multicenter database

BACKGROUND

Regional lymph node metastasis (LNM) is a competent and the most intensive predictor for the prognostic evaluation of patients after curative surgery. This study is based on the databases of two large medical centers in North and South China. It aims to establish a prognostic model based on extragastric LNM (ELNM) and lymph node ratio (LNR) in node-positive gastric cancer (GC).

METHODS

Clinical data of 874 GC patients with pathologically confirmed LNM in a large medical center in southern China, were included as the training cohort. In addition, the clinical data of 674 patients with pathologically confirmed LNM from a large medical center in northern China were used as the validation cohort.

RESULTS

In the training cohort, a modified N staging system (mNstage) based on ELNM and LNR was established; it has a significantly higher prognostic accuracy than the pN, LNR and ELNM staging system (Akaike Information Criterion, pN stage vs. LNR stage vs. ELNM stage vs. mN stage=5498.479 vs. 5537.815 vs. 5569.844 vs. 5492.123; Bayesian Information Criterion, pN stage vs. LNR stage vs. ELNM stage vs. mN stage=5512.799 vs. 5547.361 vs. 5574.617 vs. 5506.896; likelihood-ratio χ2 , pN stage vs. LNR stage vs. ELNM stage vs. mN stage=177.7 vs. 149.8 vs. 115.79 vs. 183.5). In the external validation, mNstage also has higher prognostic accuracy than the pN, LNR and ELNM staging system. Cox multivariate regression analysis showed that age, mNstage, pT stage, and perineural invasion were independent factors. A nomogram model was established according to the four factors (age, mNstage, pT stage, and perineural invasion). The nomogram model was greater than the traditional tumor-node-metastasis (TNM) staging in the training cohort [1-year area under the curve (AUC), American Joint Commission for Cancer (AJCC) 8th TNM vs. nomogram=0.692 vs. 0.746, 3-year AUC: AJCC 8th TNM vs. nomogram=0.684 vs. 0.758, 5-year AUC: AJCC 8th TNM vs. nomogram=0.725 vs. 0.762]. In the external validation, the nomogram also showed better prognostic value and greater prediction accuracy than the traditional TNM staging.

CONCLUSION

The prognostic model based on ELNM and LNR has good prognostic prediction in patients with node-positive GC.

Machine learning for lymph node metastasis prediction of in patients with gastric cancer: A systematic review and meta-analysis

Objective

To evaluate the diagnostic performance of machine learning (ML) in predicting lymph node metastasis (LNM) in patients with gastric cancer (GC) and to identify predictors applicable to the models.

Methods

PubMed, EMBASE, Web of Science, and Cochrane Library were searched from inception to March 16, 2022. The pooled c-index and accuracy were used to assess the diagnostic accuracy. Subgroup analysis was performed based on ML types. Meta-analyses were performed using random-effect models. Risk of bias assessment was conducted using PROBAST tool.

Results

A total of 41 studies (56182 patients) were included, and 33 of the studies divided the participants into a training set and a test set, while the rest of the studies only had a training set. The c-index of ML for LNM prediction in training set and test set was 0.837 [95%CI (0.814, 0.859)] and 0.811 [95%CI (0.785-0.838)], respectively. The pooled accuracy was 0.781 [(95%CI (0.756-0.805)] in training set and 0.753 [95%CI (0.721-0.783)] in test set. Subgroup analysis for different ML algorithms and staging of GC showed no significant difference. In contrast, in the subgroup analysis for predictors, in the training set, the model that included radiomics had better accuracy than the model with only clinical predictors (F = 3.546, p = 0.037). Additionally, cancer size, depth of cancer invasion and histological differentiation were the three most commonly used features in models built for prediction.

Conclusion

ML has shown to be of excellent diagnostic performance in predicting the LNM of GC. One of the models covering radiomics and its ML algorithms showed good accuracy for the risk of LNM in GC. However, the results revealed some methodological limitations in the development process. Future studies should focus on refining and improving existing models to improve the accuracy of LNM prediction.

Systematic Review Registration

https://www.crd.york.ac.uk/PROSPERO/, identifier CRD42022320752

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.

Prognostic performance of different lymph node classification systems in young gastric cancer

Background

Accurate staging plays a pivotal role in cancer care. The lymph node (LN) ratio (LNR) and the log odds of positive LNs (LODDS) have been suggested as alternatives to the N staging since the TNM system has the risk of stage migration. The prognostic significance of LNR and LODDS in young patients with gastric cancer (GC) has not been reported. This study aims to investigate the correlations between LNR and LODDS and survival of young patients with GC, and compare the predictive performance of these LN staging methods.

Methods

GC patients before the age of 40 from 2004 to 2016 in the Surveillance, Epidemiology and End Results database were enrolled. The prognostic evaluation of the N factor, LNR and LODDS was compared using the time-dependent receiver operating characteristic (ROC) analysis, area under the curve (AUC), C-index and Akaike information criterion (AIC).

Results

Multivariate survival analysis identified that the LNR and LODDS were significantly independent prognostic indicators for overall survival (OS) in young patients with GC and in the subgroups comprised of patients with ≤15 LNs examined. The time-dependent ROC curves of the LNR and LODDS were continuously superior to that of the N factor in predicting OS during the observation period. And the AUCs revealed that the predictive accuracy of the LNR and LODDS was remarkably superior to the N factor at 1 and 3 years (P<0.05). The model incorporating LNR or LODDS had higher C-index and lower AIC when comparing to the model incorporating the N factor.

Conclusions

The LNR and LODDS improve accuracy of survival risk prediction in young patients with GC when comparing to the N factor. These two novel LN classification methods should be considered as alternatives to the N staging for the prognostic prediction of young patients with GC.

Down-staging depth score could be a survival predictor for locally advanced gastric cancer patients after preoperative chemoradiotherapy

Objective

The predictive effect of preoperative chemoradiotherapy (CRT) is low and difficult in guiding individualized treatment. We examined a surrogate endpoint for long-term outcomes in locally advanced gastric cancer patients after preoperative CRT.

Methods

From April 2012 to April 2019, 95 patients with locally advanced gastric cancer who received preoperative concurrent CRT and who were enrolled in three prospective studies were included. All patients were stage T_3/4N₊. Local control, distant metastasis-free survival (DMFS), disease-free survival (DFS) and overall survival (OS) were evaluated. Clinicopathological factors related to long-term prognosis were analyzed using univariate and multivariate analyses. The down-staging depth score (DDS), which is a novel method of evaluating CRT response, was used to predict long-term outcomes.

Results

The median follow-up period for survivors was 30 months. The area under the curve (AUC) of the receiver operating characteristic (ROC) curve predicted by the DDS was 0.728, which was better than the pathological complete response (pCR), histological response and ypN0. Decision curve analysis further affirmed that DDS had the largest net benefit. The DDS cut-off value was 4. pCR and ypN0 were associated with OS (P=0.026 and 0.049). Surgery and DDS are correlated with DMFS, DFS and OS (surgery: P=0.001, <0.001 and <0.001, respectively; and DDS: P=0.009, 0.013 and 0.032, respectively). Multivariate analysis showed that DDS was an independent prognostic factor of DFS (P=0.021).

Conclusions

DDS is a simple, short-term indicator that was a better surrogate endpoint than pCR, histological response and ypN0 for DFS.

The Prognostic Value of Lymph Node Ratio in Locally Advanced Esophageal Cancer Patients Who Received Neoadjuvant Chemotherapy

BACKGROUND

The lymph node (LN) ratio (LNR) has been proposed as a sensitive prognosticator in patients with esophageal squamous cell carcinoma (ESCC), especially when the number of LNs harvested is insufficient. We investigated the association between the LNR and survival in patients with locally advanced ESCC who received neoadjuvant chemotherapy (NAC) and explored whether the LNR is a prognosticator in these patients when stratified by their response to NAC.

METHODS

We retrospectively reviewed 199 locally advanced ESCC patients who received curative resection after NAC between January 2011 and December 2019. The predictive accuracy of the adjusted X-tile cut-off values for LNR of 0 and 0.13 was compared with that in the Union for International Cancer Control pathological N (UICC pN) categories. The association between survival rate and clinicopathological features was examined.

RESULTS

Multivariate analysis identified that the LNR was an independent risk factor for recurrence-free survival [RFS; hazard ratio (HR) 6.917, p < 0.001] and overall survival (OS) (HR 4.998, p < 0.001). Moreover, even when stratified by response to NAC, the LNR was a significant independent risk factor for RFS and OS (p < 0.001). The receiver operating characteristic curves identified that the prognostic accuracy of the LNR tended to be better than that of the UICC pN factor in all cases and responders.

CONCLUSION

The LNR had a significant prognostic value in patients with locally advanced ESCC, including in those who received NAC.

Lymph Node Involvement in Advanced Gastric Cancer in the Era of Multimodal Treatment-Oncological and Surgical Perspective

Simple Summary

Gastric cancer (GC) continues to be one of the major oncological challenges on a global scale. The role of neoadjuvant chemotherapy (NAC) in GC is to downstage primary tumour, eliminate potential micrometastases, and increase the chance for radical resection. Although systemic treatment prolongs the survival in advanced GC, persistent lymph node (LN) metastases indicate poor prognosis. Therefore, further identification of prognostic factors after NAC is urgent and could positively influence clinical outcomes. This article aimed to review the actual trends and future perspectives in multimodal therapy of advanced GC, with a particular interest in the post-neoadjuvant pathological nodal stage. Since downstaged and primarily node-negative patients show a similar prognosis, the main target for NAC in advanced GC should be nodal clearance. Adequate staging and personalised perioperative therapy seem to be of great importance in the multimodal treatment of GC.

Abstract

Gastric cancer (GC) continues to be one of the major oncological challenges on a global scale. The role of neoadjuvant chemotherapy (NAC) in GC is to downstage primary tumour, eliminate potential micrometastases, and increase the chance for radical resection. Although systemic treatment prolongs the survival in advanced GC, persistent lymph node (LN) metastases indicate poor prognosis. Further identification of prognostic factors after NAC is urgent and could positively influence clinical outcomes. This article aimed to review the actual trends and future perspectives in multimodal therapy of advanced GC, with a particular interest in the post-neoadjuvant pathological nodal stage. A favourable prognostic impact for ypN0 patients is observed, either due to truly negative LN before the start of therapy or because preoperative therapy achieved a pathologically complete nodal response. Ongoing trials investigating the extent of lymphadenectomy after neoadjuvant therapy will standardise the LN dissection from the multimodal therapy perspective. Since downstaged and primarily node-negative patients show a similar prognosis, the main target for NAC in advanced GC should be nodal clearance. Adequate staging and personalised perioperative therapy seem to be of great importance in the multimodal treatment of GC.

The Prognostic Value of Postoperative Lymph Node Ratio in Gastric Adenocarcinoma Patients Treated With Neoadjuvant Chemotherapy

Objective

In this study, we aimed to investigate the prognostic value of postoperative lymph node ratio (LNR)in locally advanced gastric cancer (GC) patients receiving neoadjuvant chemotherapy (NACT).

Methods

LNR was calculated as the ratio of positive LNs to the total LNs removed. The receiver operating characteristic (ROC) curve was plotted to estimate the cut-off value of LNR for recurrence. The area under the curve of LNR was 0.714 (95% CI: 0.604-0.825, p<0.001) with 60% sensitivity and >0.255 with 76% specificity. Patients were grouped as group I (≤0.255) and group II (>0.255).

Results

In this study, 157 GC patients were included (39.5% female and 60.5% male). Of the patients, 97 (61.8%) were in group I and 60 (38.2%) were in group II. Disease‑free survival (DFS) was not reached in group I, and it was 16 months in group II (p<0.001). Overall survival (OS) was 58 months in group I and 28 months in group II (p>0.001). In multivariate analysis, lymphovascular invasion, neoadjuvant response, adjuvant treatment, and LNR were found to be the factors associated with DFS and OS (p<0.05).

Conclusion

In our study, it was observed that LNR can predict survival rates better than LN staging.

The Prognostic Value of Lymph Node Ratio after Neoadjuvant Chemotherapy in Patients with Locally Advanced Gastric Adenocarcinoma

Purpose

This study aimed to investigate the prognostic value of lymph node ratio (LNR) in patients with locally advanced gastric cancer who received neoadjuvant chemotherapy.

Materials and Methods

We retrospectively enrolled gastric cancer patients treated with neoadjuvant chemotherapy and curative surgery at the First Affiliated Hospital of Zhejiang University from 2004 to 2015 as the study cohort. Patients with the same inclusion criteria treated in 2016–2017 were enrolled as the validation cohort. Kaplan-Meier curves were assessed using the log-rank test to analyze the differences in overall survival (OS). Multivariate survival analysis was performed using the Cox proportional hazards model. The areas under the receiver operating characteristic curve of ypN and LNR categories for predicting the actual 3-year OS were compared.

Results

A total of 265 patients were included in the proposal cohort. The median number of retrieved lymph nodes (rLNs) was 32. The number of positive lymph nodes (pLNs) increased as rLN increased (P=0.037), but the LNR remained relatively constant (P=0.462). The LNR was categorized into 4 groups according to the prognosis: ypNr0, node-negative with rLN>25; ypNr1, node-negative with rLN≤25 or 0<LNR≤0.1; ypNr2, 0.1<LNR≤0.3; and ypNr3, LNR>0.3. In the validation cohort of 43 enrolled patients, there was a clear distinction in OS that significantly (P<0.001) varied depending on the LNR values and LNR was the only independent prognostic factor in multivariate analysis (P<0.001).

Conclusions

LNR was an independent prognostic factor for survival of patients with gastric cancer after preoperative chemotherapy and might be an alternative predictor for ypN stage.

Multimodal Therapy of Upper Gastrointestinal Malignancies

n/a

Treatment of Gastric Cancer Patients During COVID-19 Pandemic: The West is More Vulnerable

The outbreak of the COVID-19 is currently the biggest international concern. Treatment of gastric cancer (GC) patients in the pandemic era with high hospital burden and under severe oncological/surgical resource constraints should implicate a need for resource re-allocation with a new "pandemic" GC treatment algorithm. The neoadjuvant/perioperative (radio-)chemotherapy is applied in the majority of advanced GC cases with poor postoperative therapy compliance. In the East, radical surgery is frequently used in the first instance, with adjuvant chemotherapy reserved for patients with a high risk of recurrence. Moreover, the elderly population might be effectively treated by surgery alone, thus saving oncological resources for younger people who need a more aggressive approach. In this framework, prioritization is a key concept based on the severity of symptoms and the need for urgent (surgical) intervention. High-risk and marginally effective surgery should be replaced with definitive radio- and/or chemotherapy. The pandemic framework to provide optimal care for GC patients must be based on multidisciplinary decision-making and include all anti-cancer treatment options: surgery, systemic therapy, and radiotherapy. The priority and staffing dictate adherence to the new algorithm. We believe that these priorities may improve the delivery of care to all, including elderly GC patients.