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Indocyanine green (ICG) fluorescence imaging-guided lymphadenectomy has been demonstrated to be effective in increasing the number of lymph nodes (LNs) retrieved in laparoscopic gastrectomy for gastric cancer (GC). Previously, we reported the primary outcomes and short-term secondary outcomes of a phase 3, open-label, randomized clinical trial (NCT03050879) investigating the use of ICG for image-guided lymphadenectomy in patients with potentially resectable GC. Patients were randomly (1:1 ratio) assigned to either the ICG or non-ICG group. The primary outcome was the number of LNs retrieved and has been reported. Here, we report the primary outcome and long-term secondary outcomes including three-year overall survival (OS), three-year disease-free survival (DFS), and recurrence patterns. The per-protocol analysis set population is used for all analyses (258 patients, ICG [n = 129] vs. non-ICG group [n = 129]). The mean total LNs retrieved in the ICG group significantly exceeds that in the non-ICG group (50.5 ± 15.9 vs 42.0 ± 10.3, P  < 0.001). Both OS and DFS in the ICG group are significantly better than that in the non-ICG group (log-rank P  = 0.015; log-rank P  = 0.012, respectively). There is a difference in the overall recurrence rates between the ICG and non-ICG groups (17.8% vs 31.0%). Compared with conventional lymphadenectomy, ICG guided laparoscopic lymphadenectomy is safe and effective in prolonging survival among patients with resectable GC. Due to high rate of metastasis, lymphadenectomy is a cornerstone of the surgical treatment of gastric cancer however the accurate dissection of lymph nodes (LN) can be challenging. Here, the authors present the long-term outcomes of a randomised control trial investigating indocyanine green fluorescence image-guided LN retrieval in gastric cancer patients undergoing laparoscopic gastrectomy.

BackgroundThe definition and predictors of early recurrence (ER) for gastric cancer (GC) patients after radical gastrectomy are unclear.MethodsA minimum-p value approach was used to evaluate the optimal cutoff value of recurrence-free survival to determine ER and late recurrence (LR). Receiver operating characteristic curves were generated for inflammatory indices. Potential risk factors for ER were assessed with a Cox regression model. A decision curve analysis was performed to evaluate the clinical utility.ResultsA total of 401 patients recruited in a clinical trial (NCT02327481) from January 2015 to April 2016 were included in this study. The optimal length of recurrence-free survival to distinguish between ER (n = 44) and LR (n = 52) was 12 months. Factors associated with ER included a preoperative C-reactive protein–albumin ratio (CAR) ≥ 0.131, stage III and postoperative adjuvant chemotherapy (PAC) > 3 cycles. The risk model consisting of both the CAR and TNM stage had a higher predictive ability and better clinical utility than TNM stage alone. Further stratification analysis of the stage III patients found that for the patients with a CAR < 0.131, both PAC with 1–3 cycles (p = 0.029) and > 3 cycles (p < 0.001) could reduce the risk of ER. However, for patients with a CAR ≥ 0.131, a benefit was observed only if they received PAC > 3 cycles (54.2% vs 16.0%, p = 0.004), rather than 1–3 cycles (58.3% vs 54.2%, p = 0.824).ConclusionsA recurrence-free interval of 12 months was found to be the optimal threshold for differentiating between ER and LR. Preoperative CAR was a promising predictor of ER and PAC response. PAC with 1–3 cycles may not exert a protective effect against ER for stage III GC patients with CAR ≥ 0.131.

BackgroundSerum prealbumin (PALB) can predict the prognosis of patients with gastric cancer (GC). However, the prognostic value of combination of C-reactive protein and PALB (CRP/PALB) remains unclear.MethodsA total of 419 gastric cancer patients included in a clinical trial (NCT02327481) were analyzed. The present study is a substudy of the trial. Receiver operating characteristic (ROC) curves were generated, and by calculating the areas under the curve (AUC) and the C-index, the discriminative ability of each inflammatory index was compared, including CRP/PALB, C-reactive protein/albumin, Glasgow prognostic score (GPS), modified GPS, systemic immune-inflammation index, neutrophil–lymphocyte ratio, and platelet–lymphocyte ratio.ResultsUltimately, 401 patients were included in this study. The optimal cutoff value of CRP/PALB was 17.7. According to this cutoff point, the entire sample was divided into a CRP/PALB < 17.7 (LCP) group and a CRP/PALB ≥ 17.7 (HCP) group, comprising 245 and 156 patients, respectively. There were 54 and 22 patients experienced recurrence in the HCP and LCP group, respectively, p < 0.001. Compared with traditional inflammatory indices, CRP/PALB had the highest AUC (0.707) and C-index (0.716), all p < 0.05. The post-recurrence survival (PRS) of patients in the HCP group was significantly shorter than that in the LCP group (p = 0.010), especially for pathological stage III patients (p = 0.015) or patients with distant (p = 0.018) or local (p = 0.023) recurrences.ConclusionsThe predictive value of preoperative CRP/PALB for the recurrence of GC is significantly better than traditional inflammatory indices. HCP significantly reduces the PRS, especially for pathological stage III patients or patients with distant or local recurrences.

Background Application of indocyanine green (ICG) fluorescence imaging is effective in guiding laparoscopic radical lymphadenectomy for gastric cancer. However, the optimal approach for indocyanine green injection is controversial. Therefore, the objective of this study was aimed to compare the efficacy and ICG injection between the preoperative submucosal and intraoperative subserosal approaches for lymph node (LN) tracing during laparoscopic gastrectomy. Method This randomized controlled trial (ClinicalTrials.gov, NCT04219332) included 266 patients with potentially resectable gastric cancer (cT1–T4a, N0/+, M0) enrolled from a tertiary teaching center between December 2019 and October 2020. The primary endpoint was total number of retrieved LNs. Results In total, 259 patients ( n = 130 and n = 129 in the submucosal and subserosal groups, respectively) were included in the per-protocol analysis. There are no significant differences in total number of retrieved LNs between the two groups (49.8 vs. 49.2, P = 0.713). The rate of LN noncompliance in the submucosal group was comparable to that in the subserosal group (32.3% vs. 33.3%, P = 0.860). No significant difference was found between the submucosal and subserosal groups in terms of the incidence (17.7% vs. 16.3%; P = 0.762) or severity of postoperative complications. The mean fluorescence cost in the submucosal group was higher than that in the subserosal group ($335.3 vs. $182.4; P < 0.001). The overall treatment satisfaction score was lower in the submucosal group than in the subserosal group (70.5 vs. 76.1%, P = 0.048). Conclusion ICG administered by subserosal injection was comparable to that administered by submucosal injection for lymph node tracing in gastric cancer. However, the former approach imposed a lower economic and mental burden on patients undergoing laparoscopic D2 lymphadenectomy. Trial registration ClinicalTrials.gov, NCT04219332 .

Robotic surgery may be an alternative to laparoscopic surgery for gastric cancer (GC). However, randomized controlled trials (RCTs) reporting the differences in survival between these two approaches are currently lacking. From September 2017 to January 2020, 300 patients with cT1-4a and N0/+ were enrolled and randomized to either the robotic (RDG) or laparoscopic distal gastrectomy (LDG) group (NCT03313700). The primary endpoint was 3-year disease-free survival (DFS); secondary endpoints reported here are the 3-year overall survival (OS) and recurrence patterns. The remaining secondary outcomes include intraoperative outcomes, postoperative recovery, quality of lymphadenectomy, and cost differences, which have previously been reported. There were 283 patients in the modified intention-to-treat analysis (RDG group: n  = 141; LDG group: n  = 142). The trial has met pre-specified endpoints. The 3-year DFS rates were 85.8% and 73.2% in the RDG and LDG groups, respectively ( p  = 0.011). Multivariable Cox regression model including age, tumor size, sex, ECOG PS, lymphovascular invasion, histology, pT stage, and pN stage showed that RDG was associated with better 3-year DFS (HR: 0.541; 95% CI: 0.314-0.932). The RDG also improved the 3-year cumulative recurrence rate (RDG vs. LDG: 12.1% vs. 21.1%; HR: 0.546, 95% CI: 0.302-0.990). Compared to LDG, RDG demonstrated non-inferiority in 3-year DFS rate. Robotic surgery has been demonstrated to improve short-term outcomes for patients with gastric cancer who received a gastrectomy, but the long-term effects are less clear. Here, the authors report the survival outcomes of their phase 2 randomized controlled trial comparing robotic to laparoscopic distal gastrectomy in patients with resectable gastric cancer.

Background Whether the change of the pre- and postoperative systemic inflammatory response (SIR) levels will affect the prognosis of gastric cancer (GC) is unclear. We aimed to investigate the dynamic changes in the pre- and postoperative SIR and their prognostic value for GC. Methods The clinicopathological data from 2257 patients who underwent radical gastrectomy between January 2009 and December 2014 at Fujian Medical University Union Hospital (FMUUH) were analyzed. Perioperative SIR changes were reported as changes in the lymphocyte-monocyte ratio (LMR), neutrophil-lymphocyte ratio (NLR), platelet-lymphocyte ratio (PLR), and systemic immune-inflammation index (SII). Results The SIR levels showed different trends from postoperative months 1 to 12. Multivariate analysis showed that preoperative (pre)-LMR was an independent predictor for the prognosis ( P  = 0.024). The postoperative 12-month (post-12-month) LMR predicted the 5-year overall survival (OS) rate with the highest accuracy (areas under the curve [AUC] 0.717). Patients were divided into four groups according to the optimal cutoff of the preoperative and post-12-month LMR: high pre-LMR to high postoperative (post)-LMR group, high pre-LMR to low post-LMR group, low pre-LMR to high post-LMR group, and low pre-LMR to low post-LMR group. The survival analysis showed 5-year OS rate was significantly higher in patients with high post-12-month LMR than in patients with low post-12-month LMR, regardless of pre-LMR levels (81.6% vs. 44.2%, P  < 0.001). The prognostic accuracy was significantly improved by incorporating the post-12-month LMR in the tumor-node-metastasis (TNM) staging system ( P  = 0.003). Conclusions The remeasurement of LMR at post-12-month is helpful in predicting the long-term survival of GC.

Background The potential of the application of artificial intelligence and biochemical markers of oxidative stress to predict the prognosis of older patients with gastric cancer (GC) remains unclear. Methods This retrospective multicenter study included consecutive patients with GC aged ≥ 65 years treated between January 2012 and April 2018. The patients were allocated into three cohorts (training, internal, and external validation). The GC-Integrated Oxidative Stress Score (GIOSS) was developed using Cox regression to correlate biochemical markers with patient prognosis. Predictive models for five-year overall survival (OS) were constructed using random forest (RF), decision tree (DT), and support vector machine (SVM) methods, and validated using area under the curve (AUC) and calibration plots. The SHapley Additive exPlanations (SHAP) method was used for model interpretation. Results This study included a total of 1,859 older patients. The results demonstrated that a low GIOSS was a predictor of poor prognosis. RF was the most efficient method, with AUCs of 0.999, 0.869, and 0.796 in the training, internal validation, and external validation sets, respectively. The DT and SVM models showed low AUC values. Calibration and decision curve analyses demonstrated the considerable clinical usefulness of the RF model. The SHAP results identified pN, pT, perineural invasion, tumor size, and GIOSS as key predictive features. An online web calculator was constructed based on the best model. Conclusions Incorporating the GIOSS, the RF model effectively predicts postoperative OS in older patients with GC and is a robust prognostic tool. Our findings emphasize the importance of oxidative stress in cancer prognosis and provide a pathway for improved management of GC. Trial registration Retrospectively registered at ClinicalTrials.gov (trial registration number: NCT06208046, date of registration: 2024–05-01).

Background Neoadjuvant immunotherapy has been shown to improve survival in patients with gastric cancer. This study sought to develop and validate a radiomics-based machine learning (ML) model for patients with locally advanced gastric cancer (LAGC), specifically to predict whether patients will achieve a major pathological response (MPR) following neoadjuvant immunotherapy. With its predictive capabilities, this tool shows promise for enhancing clinical decision-making processes in the future. Methods This study utilized a multicenter cohort design, retrospectively gathering clinical data and computed tomography (CT) images from 268 patients diagnosed with advanced gastric cancer who underwent neoadjuvant immunotherapy between January 2019 and December 2023 from two medical centers. Radiomic features were extracted from CT images, and a multi-step feature selection procedure was applied to identify the top 20 representative features. Nine ML algorithms were implemented to build prediction models, with the optimal algorithm selected for the final prediction model. The hyperparameters of the chosen model were fine-tuned using Bayesian optimization and grid search. The performance of the model was evaluated using several metrics, including the area under the curve (AUC), accuracy, and Cohen’s kappa coefficient. Results Three cohorts were included in this study: the development cohort (DC, n  = 86), the internal validation cohort (IVC, n  = 59), and the external validation cohort (EVC, n  = 52). Nine ML models were developed using DC cases. Among these, an optimized Bayesian-LightGBM model, demonstrated robust predictive performance for MPR following neoadjuvant immunotherapy in LAGC patients across all cohorts. Specifically, within DC, the LightGBM model attained an AUC of 0.828, an overall accuracy of 0.791, a Cohen’s kappa coefficient of 0.552, a sensitivity of 0.742, a specificity of 0.818, a positive predictive value (PPV) of 0.586, a negative predictive value (NPV) of 0.867, a Matthews correlation coefficient (MCC) of 0.473, and a balanced accuracy of 0.780. Comparable performance metrics were validated in both the IVC and the EVC, with AUC values of 0.777 and 0.714, and overall accuracies of 0.729 and 0.654, respectively. These results suggested good fitness and generalization of the Bayesian-LightGBM model. Shapley Additive Explanations (SHAP) analysis identified significant radiomic features contributing to the model’s predictive capability. The SHAP values of the features wavelet.LLH_gldm_SmallDependenceLowGrayLevelEmphasis, wavelet.HHL_glrlm_RunVariance, and wavelet.LLH_glszm_LargeAreaHighGrayLevelEmphasis were ranked among the top three, highlighting their significant contribution to the model’s predictive performance. In contrast to existing radiomic models that exclusively focus on neoadjuvant chemotherapy, our model integrates both neoadjuvant immunotherapy and chemotherapy, thereby offering more precise predictive capabilities. Conclusion The radiomics-based ML model demonstrated significant efficacy in predicting the pathological response to neoadjuvant immunotherapy in LAGC patients, thereby providing a foundation for personalized treatment strategies.

BackgroundThe oncologic efficacy of laparoscopic versus open surgery for advanced distal gastric cancer (ADGC) beyond 3 years after surgery remain obscure.MethodsA total of 1256 patients with ADGC at two teaching institutions in China from April 2007 to December 2014 were enrolled. The general data of the two groups were identified to enable rigorous estimation of propensity scores. Restricted mean survival time (RMST) and Landmark analysis was used to compare survival.ResultsAfter matching 461 patients each in the open distal gastrectomy (ODG) and laparoscopic distal gastrectomy (LDG) groups, they were included into analysis. The 3- and 5-year overall survival (OS) and disease-free survival were comparable in two groups. RMST-stratified analysis showed that the 3-year RMST of ODG group was similar to that of LDG group in patients with cT4a (− 1.38 years, p = 0.163) or with cT4a and tumor size > 5 cm, whereas the 5-year RMST had significant differences between groups in cT4a patients(− 8.36 years, P = 0.005) or cT4a and tumor size > 5 cm patients(4.67 years, P = 0.042). In patients with cT4a and tumors > 5 cm, the number of peritoneal recurrences was significantly fewer in the ODG group than in the LDG group (4 vs. 17, P = 0.033), and the peritoneal recurrence time and multiple-site recurrence time were both later in the ODG group.ConclusionBy reducing recurrence, ODG achieves a better survival for GC patients with serous infiltration and tumors larger than 5 cm beyond 3 years after surgery. The present findings can serve as a reference for surgical options and the setting of follow-up time point for clinical studies.