Posttherapy topographical nodal status, ypN-site, predicts survival of patients who received neoadjuvant chemotherapy followed by curative surgical resection for non-type 4 locally advanced gastric cancer: supplementary analysis of JCOG1004-A

Prognostic factors and significance of postoperative adjuvant chemotherapy in patients with advanced gastric cancer undergoing neoadjuvant chemotherapy followed by gastrectomy

PURPOSE

In Japan, gastrectomy with D2 lymph node dissection and postoperative adjuvant chemotherapy are the standard treatments for locally advanced gastric cancer. Neoadjuvant chemotherapy (NAC) is not affected by postgastrectomy syndromes or postoperative complications. This multicenter retrospective study investigated the prognostic factors and significance of postoperative adjuvant chemotherapy in patients with advanced gastric cancer who underwent NAC followed by gastrectomy.

METHODS

Consecutive patients (n = 221) with advanced gastric cancer who underwent NAC followed by curative surgery were enrolled in this study. Prognostic factors including postoperative adjuvant chemotherapy were investigated using univariate and multivariate analyses.

RESULTS

A multivariate analysis revealed that pathological lymph node metastasis (ypN) status and postoperative adjuvant chemotherapy were independent prognostic factors for the overall and relapse-free survival. Forty-five patients (20.4%) did not receive postoperative adjuvant chemotherapy. There were no significant differences between patients with and without adjuvant chemotherapy for all factors, except age. The most common reason for not undergoing postoperative adjuvant chemotherapy was a poor condition (n = 23).

CONCLUSIONS

ypN status and postoperative adjuvant chemotherapy were independent prognostic factors in gastric cancer patients who underwent NAC followed by curative gastrectomy. It is important to maintain the patient's condition during NAC and the perioperative period so that they can receive postoperative adjuvant chemotherapy.

A transformer-based deep learning model for early prediction of lymph node metastasis in locally advanced gastric cancer after neoadjuvant chemotherapy using pretreatment CT images

Background

Early prediction of lymph node status after neoadjuvant chemotherapy (NAC) facilitates promptly optimization of treatment strategies. This study aimed to develop and validate a deep learning network (DLN) using baseline computed tomography images to predict lymph node metastasis (LNM) after NAC in patients with locally advanced gastric cancer (LAGC).

Methods

A total of 1205 LAGC patients were retrospectively recruited from three hospitals between January 2013 and March 2023, constituting a training cohort, an internal validation cohort, and two external validation cohorts. A transformer-based DLN was developed using 3D tumor images to predict LNM after NAC. A clinical model was constructed through multivariate logistic regression analysis as a baseline for subsequent comparisons. The performance of the models was evaluated through discrimination, calibration, and clinical applicability. Furthermore, Kaplan-Meier survival analysis was conducted to assess overall survival (OS) of LAGC patients at two follow-up centers.

Findings

The DLN outperformed the clinical model and demonstrated a robust performance for predicting LNM in the training and validation cohorts, with areas under the curve (AUCs) of 0.804 (95% confidence interval [CI], 0.752-0.849), 0.748 (95% CI, 0.660-0.830), 0.788 (95% CI, 0.735-0.835), and 0.766 (95% CI, 0.717-0.814), respectively. Decision curve analysis exhibited a high net clinical benefit of the DLN. Moreover, the DLN was significantly associated with the OS of LAGC patients [Center 1: hazard ratio (HR), 1.789, P < 0.001; Center 2:HR, 1.776, P = 0.013].

Interpretation

The transformer-based DLN provides early and effective prediction of LNM and survival outcomes in LAGC patients receiving NAC, with promise to guide individualized therapy. Future prospective multicenter studies are warranted to further validate our model.

Funding

National Natural Science Foundation of China (NO. 82373432, 82171923, 82202142), Project Funded by China Postdoctoral Science Foundation (NO. 2022M720857), Regional Innovation and Development Joint Fund of National Natural Science Foundation of China (NO. U22A20345), National Science Fund for Distinguished Young Scholars of China (NO. 81925023), Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application (NO. 2022B1212010011), High-level Hospital Construction Project (NO. DFJHBF202105), Natural Science Foundation of Guangdong Province for Distinguished Young Scholars (NO. 2024B1515020091).

Adjuvant treatment for locally advanced gastric cancer: an Asian perspective

Standard adjuvant treatment for locally advanced gastric cancer (LAGC) is regionally different. Whereas perioperative chemotherapy is the standard in Western populations, D2 gastrectomy followed by adjuvant chemotherapy has been the standard in East Asia. Recently, the pivotal phase 3 PRODIGY and RESOLVE studies have demonstrated survival benefits of adding neoadjuvant chemotherapy to surgery followed by adjuvant chemotherapy over up-front surgery followed by adjuvant chemotherapy in Asian patients. Based on these results, neoadjuvant chemotherapy is considered one of the viable options for patients with LAGC. In this review, various aspects of neoadjuvant chemotherapy will be discussed for its optimal application in Asia. Candidates for neoadjuvant chemotherapy should be carefully chosen in consideration of the inaccurate aspects of radiological clinical staging and its potential benefit over up-front surgery followed by a decision on adjuvant chemotherapy according to the pathological stage. Efforts should continuously be made to optimally apply neoadjuvant chemotherapy to patients with LAGC, considering various factors, including a more accurate radiological assessment of the tumor burden and the optimization of post-operative chemotherapy. Future neoadjuvant trials involving novel agents for Asian patients should be designed based on proven Asian regimens rather than adopting Western regimens.

Nomogram for predicting pathological response to neoadjuvant treatment in patients with locally advanced gastric cancer: Data from a phase III clinical trial

PURPOSE

This study aimed to establish a nomogram using routinely available clinicopathological parameters to predict the pathological response in patients with locally advanced gastric cancer (LAGC) undergoing neoadjuvant treatment.

MATERIALS AND METHODS

We conducted this study based on the ongoing Neo-CRAG trial, a prospective study focused on preoperative treatment in patients with LAGC. A total of 221 patients who underwent surgery following neoadjuvant chemotherapy (nCT) or neoadjuvant chemoradiotherapy (nCRT) at Sun Yat-sen University Cancer Center between June 2013 and July 2022 were included in the analysis. We defined complete or near-complete pathological regression and ypN0 as good response (GR), and determined the prognostic value of GR by Kaplan-Meier survival analysis. Eventually, a nomogram for predicting GR was developed based on statistically identified predictors through multivariate logistic regression analysis and internally validated by the bootstrap method.

RESULTS

GR was confirmed in 54 patients (54/221, 24.4%). Patients who achieved GR had a longer progression-free survival and overall survival. Then, five independent factors, including pretreatment tumor differentiation, clinical T stage, monocyte count, CA724 level, and the use of nCRT, were identified. Based on these predictors, the nomogram was established with an area under the curve (AUC) of 0.777 (95% CI, 0.705-0.850) and a bias-corrected AUC of 0.752.

CONCLUSION

A good pathological response after neoadjuvant treatment was associated with an improved prognosis in LAGC patients. The nomogram we established exhibits a high predictive capability for GR, offering potential value in devising personalized and precise treatment strategies for LAGC patients.

Development and evaluation of the Newstage system: integrating tumor regression grade and lymph node status for improved prognostication in neoadjuvant treatment of gastric cancer

BACKGROUND

The predictive correlation of tumor depth of invasion changes after neoadjuvant therapy, and the 8th American Joint Committee on Cancer (AJCC) ypTNM system for gastric cancer may not accurately predict patient prognosis following neoadjuvant therapy.

METHODS

A retrospective analysis was conducted on a total of 258 patients who underwent radical surgery for gastric cancer after neoadjuvant therapy. The Newstage system was established based on tumor regression grade and pathological lymph node status. The 3-year survival rates of patients classified by the Newstage system were compared with those classified by the AJCC ypTNM system.

RESULTS

In a cohort of 258 patients, the 3-year overall survival rates based on the Newstage system were: (I) 94.6%, (II) 79.3%, (III) 54.5%, and (IV) 30.2%. The Newstage system exhibited a lower Akaike information criterion value (902.57 vs. 912.03). Additionally, the area under the ROC curve (0.756 vs. 0.733) and the C-index (0.731 vs. 0.718) was higher than the AJCC ypTNM system. Furthermore, a multivariate analysis indicated that the Newstage system was an independent prognostic factor (p = 0.001).

CONCLUSION

The Newstage system exhibits superior predictive performance in estimating survival rates for neoadjuvant therapy in gastric cancer. It also functions as an independent prognostic factor.

Body composition parameters predict pathological response and outcomes in locally advanced gastric cancer after neoadjuvant treatment: A multicenter, international study

BACKGROUND

Body composition profiles influence the prognosis of several types of cancer; however, the role of body composition in patients with locally advanced gastric cancer (LAGC) after neoadjuvant treatment (NT) has not been well characterized.

PATIENTS AND METHODS

A total of 213 patients with LAGC who underwent gastrectomy after NT at a high-volume institution from southern China were comprehensively evaluated for primary analysis. Additionally, 170 and 77 patients from Western China and Italy, respectively, were reviewed for external validation. The skeletal muscle index (SMI), skeletal muscle radiodensity (SMD), and the subcutaneous as well as the visceral adiposity index were assessed from clinically acquired CT scans at diagnosis and preoperatively.

RESULTS

Overall, none of the body composition parameters significantly changed after NT. The pre-NT skeletal muscle radiodensity (SMD) and change in SMI (ΔSMI) were both significantly lower in the patients with poor response (tumor regression <50%; mean SMD: 43.5 vs 46.5, P = 0.003; mean ΔSMI: -1.0 vs 2.2, P < 0.001), and the cutoff values were calculated according to the Youden index as 43.7 and 1.2, respectively. Based on these 2 parameters, a novel model, the Skeletal Muscle Score (SMS), was proposed to predict the pathological response (AUC = 0.764 alone and = 0.822 in combination with the radiological response). Moreover, patients with an SMI loss >1.2 had a significantly prolonged drainage tube removal time (mean: 10.0 vs 8.2, P = 0.003) and postoperative hospital stay (mean: 11.1 vs 9.8, P = 0.048), as well as a significantly higher rate of postoperative complications (30.9% vs 16.7%, P = 0.015). In the multivariate analysis, SMI loss >1.2 independently predicted poor overall survival (HR: 1.677, 95% CI 1.040-2.704, P = 0.034) and recurrence-free survival (HR: 1.924, 95% CI 1.165-3.175, P = 0.011). ΔSMI was also significantly associated with pathological response, surgical outcomes, and survival in the 2 external cohorts (P all < 0.05).

CONCLUSIONS

For LAGC, the pre-NT SMD and ΔSMI could accurately predict the pathological response after NT. An SMI loss >1.2 is closely associated with poorer outcomes and may indicate the need more supportive treatment.

Nomogram for Predicting Survival in Advanced Gastric Cancer after Neoadjuvant Chemotherapy and Radical Surgery

BACKGROUND

Neoadjuvant chemotherapy (NAC) with subsequent radical surgery has become a popular treatment modality for advanced gastric cancer (AGC) worldwide. However, the survival benefit is still controversial, and prognostic factors remain undetermined.

AIM

To identify clinical parameters that are associated with the survival of AGC patients after NAC and radical surgery and to establish a nomogram integrating multiple factors to predict survival.

METHODS

We reviewed the medical profiles of 215 AGC patients who received NAC and radical resection, and clinical parameters concerning NAC, surgery, pathological findings, and adjuvant chemotherapy were analyzed using a Cox regression model to determine their impact on survival. Based on these factors, a nomogram was developed and validated.

RESULTS

The overall 1-year and 3-year survival rates were 85.8% and 55.6%, respectively. Younger age (<60 years old), increased examined lymph nodes (exLNs), successful R0 resection, the achievement of pathological complete response (pCR), and acceptance of adjuvant chemotherapy were positive predictors of survival. The C-index of the established nomogram was 0.785. The area under receiver operating curve (ROC) at 1/3 years of prediction was 0.694/0.736, respectively. The model showed an ideal calibration following internal bootstrap validation.

CONCLUSION

A nomogram predicting survival after NAC and surgery was established. Since this nomogram exhibited satisfactory and stable predictive power, it can be inferred that this is a practical tool for predicting AGC patient survival after NAC and radical surgery.