Which is the optimal management for locally advanced gastric cancer patients with TRG 0 and 1 after R0 resection?

Deep learning nomogram for predicting neoadjuvant chemotherapy response in locally advanced gastric cancer patients

PURPOSE

Developed and validated a deep learning radiomics nomogram using multi-phase contrast-enhanced computed tomography (CECT) images to predict neoadjuvant chemotherapy (NAC) response in locally advanced gastric cancer (LAGC) patients.

METHODS

This multi-center study retrospectively included 322 patients diagnosed with gastric cancer from January 2013 to June 2023 at two hospitals. Handcrafted radiomics technique and the EfficientNet V2 neural network were applied to arterial, portal venous, and delayed phase CT images to extract two-dimensional handcrafted and deep learning features. A nomogram model was built by integrating the handcrafted signature, the deep learning signature, with clinical features. Discriminative ability was assessed using the receiver operating characteristics (ROC) curve and the precision-recall (P-R) curve. Model fitting was evaluated using calibration curves, and clinical utility was assessed through decision curve analysis (DCA).

RESULTS

The nomogram exhibited excellent performance. The area under the ROC curve (AUC) was 0.848 [95% confidence interval (CI), 0.793-0.893)], 0.802 (95% CI 0.688-0.889), and 0.751 (95% CI 0.652-0.833) for the training, internal validation, and external validation sets, respectively. The AUCs of the P-R curves were 0.838 (95% CI 0.756-0.895), 0.541 (95% CI 0.329-0.740), and 0.556 (95% CI 0.376-0.722) for the corresponding sets. The nomogram outperformed the clinical model and handcrafted signature across all sets (all P < 0.05). The nomogram model demonstrated good calibration and provided greater net benefit within the relevant threshold range compared to other models.

CONCLUSION

This study created a deep learning nomogram using CECT images and clinical data to predict NAC response in LAGC patients undergoing surgical resection, offering personalized treatment insights.

Comparison of Four Lymph Node Staging Systems in Gastric Adenocarcinoma after Neoadjuvant Therapy – A Population-Based Study

Introduction

Neoadjuvant treatment leads in a reduction in positive lymph nodes and examined lymph nodes (ELN), which may affect assessment of lymph node staging and postoperative treatment. We aimed to compare the staging systems of lymph node ratio (LNR), the positive logarithm ratio of lymph nodes (LODDS), negative lymph nodes (NLN), and the 8th AJCC ypN stage for patients with gastric adenocarcinoma after neoadjuvant therapy.

Materials and Methods

Data was collected from the Surveillance, Epidemiology, and End Results database and 1,551 patients with gastric adenocarcinoma who underwent neoadjuvant therapy and radical surgery were enrolled. Harrell’s concordance index, the Receiver Operative Curve, the likelihood ratio test, and the Akaike information criterion were used to compare the predictive abilities of the different staging systems.

Results

Among the 1,551 patients, 689 (44.4%) had ELN < 16 and node-negative patients accounted for 395 (25.5%). When regarded as the categorical variable, LNR had better discrimination power, higher homogeneity, and better model fitness for CSS and OS compared to other stage systems, regardless of the status of ELN. When regarded as the continuos variable, LODDS outperformed others for CSS. Furthermore, the NLN staging system performed superior to others in node-negative patients.

Conclusions

LNR had a better predictive performance than ypN, LODDS and NLN staging systems regardless of the status of ELN when regarded as the categorical variable, whereas LOODS became the better predictive factor for CSS when regarded as the continuos variable. In node-negative patients, NLN might be a feasible option for evaluating prognosis. A combination of LNR and NLN should be considered as user-friendly method in the clinical prognostic assessment.

Neoadjuvant Bevacizumab Plus Docetaxel/Cisplatin/Capecitabine Chemotherapy in Locally Advanced Gastric Cancer Patients: A Pilot Study

Background

Bevacizumab (BEV) plus chemotherapy as a neoadjuvant regimen presents good efficacy in patients with locally advanced cancer. However, its role in patients with locally advanced gastric cancer (LAGC) is not clear. Thus, the study aimed to assess the efficacy and safety of neoadjuvant BEV plus chemotherapy in patients with LAGC.

Methods

Twenty resectable patients with LAGC who received BEV plus docetaxel/cisplatin/capecitabine (DCC) chemotherapy for 3 cycles with 21 days as one cycle as neoadjuvant regimen were involved. Besides, their treatment response, survival profiles, and adverse events were assessed.

Results

In total, two (10.0%), 9 (45.0%), 8 (40.0%), and 1 (5.0%) patients achieved complete remission, partial remission, stable disease, and progressive disease (PD) according to imaging evaluation, which resulted in 55.0% of objective response rate and 95.0% of disease control rate, respectively. Moreover, the number of patients with pathological response grades 1, 2, and 3 was 8 (40.0%), 8 (40.0%), and 3 (15.0%); while 1 (5.0%) patient did not receive surgery due to PD, thus the data of this patient was not assessable. Meanwhile, 18 (90.0%) patients achieved R0 resection. Regarding survival profile, the median disease-free survival or overall survival were both not reached. The 1-year, 2-, and 3-year disease-free survival rates were 88.8, 80.7, and 67.3%. Meanwhile, the 1-, 2-, and 3-year overall survival rates were 100.0%, 75.8%, and 75.8%, respectively. Additionally, the main adverse events were anemia (90.0%), alopecia (90.0%), leukopenia (70.0%), and anorexia (65.0%). Indeed, most adverse events were of grade 1 or 2 and were manageable.

Conclusion

Neoadjuvant BEV plus DCC chemotherapy presents a favorable pathological response and survival profile with acceptable safety in patients with LAGC.

Combination of tumor markers predicts progression and pathological response in patients with locally advanced gastric cancer after neoadjuvant chemotherapy treatment

BACKGROUND

The prognostic values of preoperative tumor markers (TMs) remain elusive in patients with locally advanced gastric cancer (LAGC) after neoadjuvant chemotherapy treatment (NACT). This study aimed to assess and establish a novel scoring system incorporating carcinoembryonic antigen (CEA), carbohydrate antigen 19-9 (CA19-9), carbohydrate antigen 72-4 (CA72-4) to enhance prognostic accuracy for progression-free survival (PFS) and pathological response (pCR).

METHODS

Patients' data were retrospectively analyzed from December 2006 to December 2017 in our center. The cutoff value of TMs was determined using the time-dependent receiver operating test characteristics method. These three TMs were allocated 1 point each for the post neoadjuvant chemotherapy combination of tumor markers (post-NACT CTM) scores. The training group comprised 533 patients, responsible for full analysis, and the validation group comprised 137 patients based on the selection protocol.

RESULTS

Of 533 enrolled patients, 138, 233, 117, and 45 patients scored 0, 1, 2, 3 respectively. The 3-year PFS rate Multivariate analysis revealed that post-NACT CTM score was an independent predictor of PFS (0 vs. 1, HR: 1.34, 95% CI: 0.92-1.96, P = 0.128; 0 vs. 2, HR: 2.03, 95% CI: 1.35-3.05, P = 0.001; 0 vs. 3, HR: 2.98, 95% CI: 1.83-4.86, P < 0.001). The time-dependent area under curve (AUC) revealed a consistent highest level for post-NACT CTM than other three single TMs. Lower post-NACT CTM score significantly correlated with higher pCR rate based on multivariate logistic regression (2/3 vs. 1, OR: 2.77, 95% CI: 0.90-8.53, P = 0.077; 2/3 vs. 0, OR: 4.33, 95% CI: 1.38-13.61, P = 0.012). A nomogram was formed with both internal and external validation.

CONCLUSIONS

The post-NACT CTM score system served as a strong independent predictor for PFS and pCR in LAGC patients who received NACT. Further population-based studies are required to confirm our results.