Evaluation and Comparison of Predictive Value of Tumor Regression Grades according to Mandard and Becker in Locally Advanced Gastric Adenocarcinoma

Evaluating Treatment Response in GEJ Adenocarcinoma: The Role of Pretherapeutic and Posttherapeutic Iodine Mapping

BACKGROUND

Neoadjuvant therapy regimens have significantly improved the prognosis of GEJ (gastroesophageal junction) cancer; however, there are a significant percentage of patients who benefit from earlier resection or adapted therapy regimens, and the true response rate can only be determined histopathologically. Methods that allow preoperative assessment of response are lacking.

PURPOSE

The purpose of this retrospective study is to assess the potential of pretherapeutic and posttherapeutic spectral CT iodine density (IoD) in predicting histopathological response to neoadjuvant chemotherapy in patients diagnosed with adenocarcinoma of the GEJ.

METHODS

In this retrospective cohort study, a total of 62 patients with GEJ carcinoma were studied. Patients received a multiphasic CT scan at diagnosis and preoperatively. Iodine-density maps were generated based on spectral CT data. All tumors were histopathologically analyzed, and the tumor regression grade (TRG) according to Becker et al ( Cancer . 2003;98:1521-1530) was determined. Two experienced radiologists blindly placed 5 defined ROIs in the tumor region of highest density, and the maximum value was used for further analysis. Iodine density was normalized to the aortic iodine uptake. In addition, tumor response was assessed according to standard RECIST measurement. After assessing interrater reliability, the correlation of IoD values with treatment response and with histopathologic TRG was evaluated.

RESULTS

The normalized ΔIoD (IoD at diagnosis - IoD after neoadjuvant treatment) and the normalized IoD after neoadjuvant treatment correlated significantly with the TRG. For the detection of responders and nonresponders, the receiver operating characteristic (ROC) curve for normalized ΔIoD yielded the highest area under the curve of 0.95 and achieved a sensitivity and specificity of 92.3% and 92.1%, respectively. Iodine density after neoadjuvant treatment achieved an area under the curve of 0.88 and a sensitivity and specificity of 86.8% and 84.6%, respectively (cutoff, 0.266). Iodine density at diagnosis and RECIST did not provide information to distinguish responders from nonresponders. Using the cutoff value for IoD after neoadjuvant treatment, a reliable classification of responders and nonresponders was achieved for both readers in a test set of 11 patients. Intraclass correlation coefficient revealed excellent interrater reliability (intraclass correlation coefficient, >0.9). Lastly, using the cutoff value for normalized ΔIoD as a definition for treatment response, a significantly longer survival of responders was shown.

CONCLUSIONS

Changes in IoD after neoadjuvant treatment of GEJ cancer may be a potential surrogate for therapy response.

Development and validation of an individualized nomogram for gastric cancer patients treated with perioperative chemotherapy followed by radical surgery

Background

Prognostic factors are complicated and changeable for locally advanced gastric cancer (GC) patients. This study aimed to perform a novel prognostic model on survival for locally advanced GC patients who have received neoadjuvant chemotherapy and radical surgery.

Methods

The locally advanced GC patients with neoadjuvant chemotherapy were included in this study from Zhongshan Hospital, Fudan University. A nomogram was developed based on independent prognostic factors identified through a multivariable Cox regression model. Model performance was evaluated in training and independent external cohorts in terms of calibration, discrimination, and clinical usefulness.

Results

A total of 273 patients received radical resections. The median progression-free survival (PFS) and overall survival (OS) for all patients were 43.8 and 61.2 months, respectively. Nomogram showed that Lauren type made the greatest contribution to prognosis, followed by ypN. The prognostic nomogram had excellent discriminative ability, with a C-index of 0.689 [95% confidence interval (CI): 0.661-0.716], and an area under the receiver operating characteristic (ROC) curve (AUC) of 0.778, 0.746, and 0.725 for 3-, 5- and 10-year OS, respectively. Similar results were obtained in the external validation cohort. Based on the nomogram, the whole cohort was divided into high-risk and low-risk groups. And risk group classification was significantly associated with clinical characteristics, and produced an AUC value of 0.781, 0.748, and 0.727 for 3-, 5- and 10-year OS, respectively. Furthermore, compared with the tumor-node-metastasis (TNM) staging system (8th edition), Japanese criteria, and German criteria, the decision curve analysis (DCA) graphically demonstrated that the new model had more optimal net benefits in predicting the 3-, 5-, and 10-year OS for GC patients. Both C-index and time-dependent ROC curve demonstrated that the nomogram had a stronger capability for accurately predicting prognosis compared with the other staging system.

Conclusions

The nomogram model is an effective support tool to predict OS in GC patients undergoing perioperative chemotherapy followed by radical surgery.

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.

The Evolving Landscape of Neoadjuvant Immunotherapy in Gastroesophageal Cancer

Despite advances in treatment strategies and surgical approaches in recent years, improving survival outcomes in esophagogastric cancer (EGC) patients treated with curative intent remains a significant area of unmet need. The recent emergence of adjuvant immunotherapy as the standard of care for resected EGC demonstrates the impact of immunotherapy in improving recurrence-free survival. Neoadjuvant and perioperative immunotherapies represent another promising approach with potential advantages over adjuvant therapy. Despite the promising results of early neoadjuvant immunotherapy studies, there are several challenges and future research needs. The optimal timing, duration and number of doses in relation to surgery and the optimal combination of immunotherapies are still unclear. In addition, rigorous correlative studies need to be performed to identify biomarkers for patient selection and treatment response prediction to maximize the benefits of neoadjuvant immunotherapy. In this review, we provide a concise summary of the current standard of care for resectable EGC and discuss the rationale for the use of immune checkpoint inhibitors in this setting and the pre-clinical and early clinical data of these novel therapies. Finally, we will examine the potential role and future direction of immunotherapy in the treatment paradigm and the perceived challenges and opportunities that lay ahead.

Sintilimab plus fluorouracil, leucovorin, oxaliplatin and docetaxel regimen as neoadjuvant therapy for resectable gastric cancer and biomarker exploration

At present, preoperative chemotherapy is the standard of care for the neoadjuvant treatment of potentially resectable gastric cancer (GC). However, because the efficacy and prognosis are not ideal, curative effects for this population are unsatisfactory. With the development of immune checkpoint inhibitors, the results of a few encouraging early trials of immunotherapeutic agents as neoadjuvant therapies for resectable GC have been reported. However, markers of the efficacy of immune checkpoint inhibitors remain unclear. This prospective single-center, single-arm observational study was designed to evaluate the efficacy of sintilimab plus the fluorouracil, leucovorin, oxaliplatin and docetaxel regimen as a neoadjuvant treatment for localized GC. More importantly, this work assesses multiple dimensions and include ctDNA, the immune microenvironment and intestinal microbiome to explore correlations between biomarkers and neoadjuvant therapeutic efficacy. Clinical trial registration: ChiCTR2200061629 (www.chictr.org.cn/index.aspx).

Profiling complete regression after pre-operative therapy in gastric cancer patients using clinical and pathological data

INTRODUCTION

The consistent use of pre-operative treatment before surgery for gastric cancer (GC) has resulted in increased rates of complete response. However, factors associated with response have been scantly investigated.

METHODS

Patients with GCs treated between 2017 and 2022 undergoing pre-operative treatment followed by resection were included. Clinicopathological data were analyzed for the association with tumor regression grades (TRG); secondary outcomes included the short-term overall (OS), disease-free (DFS) and disease specific survival (DSS).

RESULTS

Among 108 patients, 35.1% had an intestinal histotype GC, and 70.4% were treated with FLOT. Complete tumor regression (TRG1) was documented in 6.5% of patients. Univariable analyses documented that a higher pre-operative albumin (p = 0.04) and the expression of HER2 (p = 0.01) were associated to TRG1. In the multinominal regression model, the log-odds of being classified as TRG1 increased with the expression of HER2 by 170.247 times and with higher pre-operative albumin by 34.525 times, while with a higher Charlson Index and a diffuse hystotipe reduced it by 25.467 times and 3759.126 times, respectively. Among 49 patients (mean follow-up: 17.1 months), TRG1-2 was associated to better OS, DFS and DSS curves compared to TRG 3-5 (respectively p < 0.01, p 0.007 and p < 0.01), altogether with the reported negative impact of comorbidities in OS and DSS multivariable analyses (respectively p 0.04 and p 0.006). The random survival forest further confirmed the impact of HER2 and comorbidity on DSS.

CONCLUSION

A better clinical profile, HER2 expression and intestinal histotype significantly correlated with GC regression. A complete-major response was an independent factor for survival.

Concurrent clinical and pathological response predicts favorable prognosis of patients with gastric cancer after neoadjuvant therapy: a real-world study

BACKGROUND

Response of locally advanced gastric cancer (LAGC) to neoadjuvant therapy (NAT) may be associated with prognosis, but which of the clinical or pathological evaluation can accurately predict a favorable prognosis is still controversial. This study aims to compare the effect of clinical and pathological response on the prognosis of patients with gastric cancer.

METHODS

This study retrospectively analyzed LAGC patients who underwent NAT followed by surgery in the China National Cancer Center from January 2004 to January 2021. Clinical and pathological responses after NAT were evaluated using RECIST 1.1 and Mandard tumor regression grade system (TRG) respectively. Complete response (CR) and partial response (PR) assessed by computed tomography were regarded as clinical response. For histopathology regression assessment, response was defined as Mandard 1, 2, 3 and non-response as Mandard 4, 5. Furthermore, we combined clinical and pathological evaluation results into a variable termed "comprehensive assessment" and divided it into four groups based on the presence or absence of response (concurrent response, only clinical response, only pathological response, both non-response). The association between the prognosis and clinicopathological factors was assessed in univariate and multivariate Cox regression analysis.

RESULTS

In total, 238 of 1073 patients were included in the study after screening. The postoperative pathological response rate and clinical response rate were 50.84% (121/238) and 39.92% (95/238), respectively. 154 patients got consistent results in clinical and pathological evaluation (66 were concurrent response and 88 were both non-response), while the other 84 patients did not. The kappa value was 0.297(p < 0.001), which showed poor consistency. Multivariate Cox regression analysis revealed that comprehensive assessment (P = 0.03), clinical N stage(P < 0.001), vascular or lymphatic invasion (VOLI) (HR 2.745, P < 0.001), and pre-CA724(HR 1.577, P = 0.047) were independent factors for overall survival in patients with gastric cancer. Among four groups in the comprehensive assessment, concurrent response had significantly better survival (median OS: 103.5 months) than the other groups (P = 0.008).

CONCLUSION

Concurrent clinical and pathological response might predict a favorable prognosis of patients with gastric cancer after neoadjuvant therapy, further validation is needed in prospective clinical trials with larger samples.

Response Evaluation after Neoadjuvant Chemotherapy for Resectable Gastric Cancer

BACKGROUND

The method of response evaluation following neoadjuvant chemotherapy (NAC) in resectable gastric cancer has been widely debated. An essential prerequisite is the ability to stratify patients into subsets of different long-term survival rates based on the response mode. Histopathological measures of regression have their limitations, and interest resides in CT-based methods that can be used in everyday settings.

METHODS

We conducted a population-based study (2007-2016) on 171 consecutive patients with gastric adenocarcinoma who were receiving NAC. Two methods of response evaluation were investigated: a strict radiological procedure using RECIST (downsizing), and a composite radiological/pathological procedure comparing the initial radiological TNM stage to the pathological ypTNM stage (downstaging). Clinicopathological variables that could predict the response were searched for, and correlations between the response mode and long-term survival rates were assessed.

RESULTS

RECIST failed to identify half of the patients progressing to metastatic disease, and it was unable to assign patients to subsets with different long-term survival rates based on the response mode. However, the TNM stage response mode did achieve this objective. Following re-staging, 48% (78/164) were downstaged, 15% (25/164) had an unchanged stage, and 37% (61/164) were upstaged. A total of 9% (15/164) showed a histopathological complete response. The 5-year overall survival rate was 65.3% (95% CI 54.7-75.9%) for TNM downstaged cases, 40.0% (95% CI 20.8-59.2%) for stable disease, and 14.8% (95% CI 6.0-23.6%) for patients with TNM progression, p < 0.001. In a multivariable ordinal regression model, the Lauren classification and tumor site were the only significant determinants of the response mode.

CONCLUSIONS

Downsizing, as a method for evaluating the response to NAC in gastric cancer, is discouraged. TNM re-staging by comparing the baseline radiological CT stage to the pathological stage following NAC is suggested as a useful method that may be used in everyday situations.

Time to surgery does not affect oncologic outcomes in locally advanced gastric cancer after neoadjuvant chemotherapy: a meta-analysis

Aim: The authors conducted a meta-analysis to determine the association between time-to-surgery (TTS) after neoadjuvant chemotherapy and patient outcomes in locally advanced gastric cancer. Methods: Electronic databases were searched to identify potential studies, in which the authors compared patient outcomes between those with TTS within 4 (and 6) weeks of completion of neoadjuvant chemotherapy and those after 4 (and 6) weeks. Results: Six studies, including 1238 patients, were eligible for inclusion. Pooled data showed no significant differences in rates of pathological complete response, major pathological response, ypN0, complications, R0 resection and operative time between groups of longer TTS and shorter TTS. Conclusion: There was no statistically advantageous impact of prolonged TTS on pathological and surgical outcomes. Large, population-based studies are warranted.

Intratumoral heterogeneity affects tumor regression and Ki67 proliferation index in perioperatively treated gastric carcinoma

BACKGROUND

Intratumoral heterogeneity (ITH) is a major problem in gastric cancer (GC). We tested Ki67 and tumor regression for ITH after neoadjuvant/perioperative chemotherapy.

METHODS

429 paraffin blocks were obtained from 106 neoadjuvantly/perioperatively treated GCs (one to five blocks per case). Serial sections were stained with Masson's trichrome, antibodies directed against cytokeratin and Ki67, and finally digitalized. Tumor regression and three different Ki67 proliferation indices (PI), i.e., maximum PI (KiH), minimum PI (KiL), and the difference between KiH/KiL (KiD) were obtained per block. Statistics were performed in a block-wise (all blocks irrespective of their case-origin) and case-wise manner.

RESULTS

Ki67 and tumor regression showed extensive ITH in our series (maximum ITH within a case: 31% to 85% for KiH; 4.5% to 95.6% for tumor regression). In addition, Ki67 was significantly associated with tumor regression (p < 0.001). Responders (<10% residual tumor, p = 0.016) exhibited prolonged survival. However, there was no significant survival benefit after cut-off values were increased ≥20% residual tumor mass. Ki67 remained without prognostic value.

CONCLUSIONS

Digital image analysis in tumor regression evaluation might help overcome inter- and intraobserver variability and validate classification systems. Ki67 may serve as a sensitivity predictor for chemotherapy and an indicator of ITH.

MORBIDITY AND SURVIVAL AFTER PERIOPERATIVE CHEMOTHERAPY IN GASTRIC CANCER: A STUDY USING THE BECKER'S CLASSIFICATION AND REGRESSION

BACKGROUND

Gastric cancer is an aggressive neoplasm with a poor prognosis. The multimodal approach with perioperative chemotherapy is currently the recommended treatment for patients with locally advanced gastric cancer. This treatment induces a histopathological response expressed either through the degree of regression of the primary tumor or of the lymph nodes or through yTNM staging. Despite its advantages, there are still doubts regarding the effects of chemotherapy on postoperative morbidity and mortality.

AIMS

This study aims to evaluate the impact of perioperative chemotherapy and its effect on anatomopathological results and postoperative morbidity and on patient survival.

METHODS

This is an observational retrospective study on 134 patients with advanced gastric cancer who underwent perioperative chemotherapy and curative radical surgery. The degree of histological regression of the primary tumor was evaluated according to Becker's criteria; the proportion of regressed lymph nodes was determined, and postoperative complications were evaluated according to the Clavien-Dindo classification. Survival times were compared between the groups using Kaplan-Meier curves and the Mantel-Cox log-rank test.

RESULTS

In all, 22.3% of the patients were classified as good responders and 75.9% as poor responders. This variable was not correlated with operative morbidity (p=1.68); 64.2% of patients had invaded lymph nodes and 46.3% had regressed lymph nodes; and 49.4% had no lymphatic invasion and 61.9% had no signs of venous invasion. Postoperative complications occurred in 30.6% of the patients. The group of good responders had an average survival of 56.0 months and the group of poor responders had 34.0 months (p=0.17).

CONCLUSION

Perioperative chemotherapy induces regression in both the primary tumor and lymph nodes. The results of the operative morbidity were similar to those described in the literature. However, although the group of good responders showed better survival, this value was not significant. Therefore, further studies are needed to evaluate the importance of the degree of lymph node regression and its impact on the survival of these patients.

Comparison of tumor regression grading systems for locally advanced gastric adenocarcinoma after neoadjuvant chemotherapy

BACKGROUND

Current tumor regression grade (TRG) evaluations are based on various systems which brings confusion for oncologists and pathologists when interpreting results. The recent six-tier system (JGCA2017-TRG) recommended by the Japanese Gastric Cancer Association (JGCA) is worth investigating, as four-tier TRG systems are favored in various parts of the world.

AIM

To compare the predictive accuracies of five published TRG systems.

METHODS

Data were retrospectively collected from patients with locally advanced gastric cancer (LAGC) who underwent neoadjuvant chemotherapy followed by D2 Lymphadenectomy between January 2005 and January 2014 at our institution. Outcomes were overall survival (OS) and disease-free survival (DFS), which were evaluated separately using the following TRG systems: JGCA2017, JGCA, Becker, AJCC/CAP, and Mandard.

RESULTS

All five published TRG systems were independent predictors for OS and DFS. Concordance indices of the JGCA2017, JGCA, Becker, AJCC/CAP-TRG, and Mandard systems were 0.651/0.648 0.652/0.649, 0.693/0.695, 0.688/0.685, and 0.674/0.675 for OS and DFS, respectively. The four-tier Becker system showed the highest c-index, which was significantly greater than that of the six-tier JGCA2017 and five-tier JGCA systems (P < 0.05 in OS and DFS). When residual tumor percentages were reset as: “no residual tumor”, < 10%, < 100%, and “no response”, the rearranged cutoff values achieved a maximum c-index with 0.728 for OS and 0.737 for DFS, which was superior to the other five systems.

CONCLUSION

The newly introduced six-tier JGCA-TRG system cannot increase prognostic stratification. The four-tier Becker system is more suitable for LAGC patients. A population-based study is warranted to define the optimal criterion for TRG in LAGC patients.

CA724 Predicts Tumor Regression Grade in Locally Advanced Gastric Cancer Patients with Neoadjuvant Chemotherapy

Purpose: Tumor regression grade (TRG) is widely used to evaluate the efficacy of neoadjuvant chemotherapy (NCT) and it is related to many clinicopathological factors. However, whether TRG can be predicted by clinical characteristics is unknown.

Methods: 141 locally advanced gastric cancer (GC) patients who underwent NCT and curative operation were retrospectively analyzed. TRG is reevaluated according to the CAP guideline. The values of CA199, CA125 and CA724 before NCT (pre-) and after NCT (post-) were extracted from our database. Survival curves on overall survival (OS) were obtained by Kaplan-Meier method, and differences were analyzed by log-rank test. Associations between categorical variables were explored by chi-square test or Fisher's exact method. Univariable and multivariate analyses were performed by logistic regression model or Cox proportional hazard regression model.

Results: TRG was related to OS (P < 0.001), especially when divided into responders (TRG 0-1) and non-responders (TRG 2-3). Pre-CA724 (p = 0.029) and post-CA199 (p = 0.038) were related to OS. In multivariable analysis, pre-CA724 (p = 0.015) and post-CA199 (p = 0.007) were independent prognostic factors for OS, respectively. The changes (diff-) of all tumor markers were not related to OS. Among the clinical characteristics, pre-CA724 (P = 0.047) and tumor size (P = 0.012) were related to TRG, while pre-CA199 (P = 0.377) and pre-CA125 (P = 0.856) were not. In logistics analysis, pre-CA724 (P = 0.032), tumor size (P = 0.011) and tumor location (P = 0.047) were independent risk factors to pathological response.

Conclusion: CA724 was an independent prognostic factor for OS and could be used to predict pathological response.

Validating a nodal regression system for gastric cancer: An ancillary cohort study of the GASTRODOC trial

BACKGROUND

To validate a nodal regression system for gastric cancer and to verify its impact on prognosis.

METHODS

This is an ancillary study which included 47 patients of the GASTRODOC trial. The dedicated pathologists of each Institute were invited to revise all the lymph nodes included in the surgical specimens in order to classify the regression according to the grading system proposed by Tsekrekos et al. The association of the nodal regression system and the clinico-pathological characteristics and prognosis were investigated.

RESULTS

According to the classification of Tsekrekos et al., there were 19 (40.4%) patients with grade a, 14 (29.8%) with grade b and 14 (29.8%) with grade c nodal regression. This regression system showed significant statistical associations with pathological N status (p < 0.001), residual tumor classification (p = 0.003) and Becker regression system (p = 0.011). At multivariable analysis only Tsekrekos' grading regression system was significantly associated with the PFS (HR 10.1, 95% CI 1.3-75.5; p = 0.025).

CONCLUSIONS

The analyzed nodal regression system is significantly associated with Becker's regression system and it has a strong correlation with prognosis.

Evaluation of dual-energy CT derived radiomics signatures in predicting outcomes in patients with advanced gastric cancer after neoadjuvant chemotherapy

BACKGROUND

To investigate the prognostic value of dual-energy CT (DECT) based radiomics to predict disease-free survival (DFS) and overall survival (OS) for patients with advanced gastric cancer (AGC) after neoadjuvant chemotherapy (NAC).

METHODS

From January 2014 to December 2018, a total of 156 AGC patients were enrolled and randomly allocated into a training cohort and a testing cohort at a ratio of 2:1. Volume of interest of primary tumor was delineated on eight image series. Four feature sets derived from pre-NAC and delta radiomics were generated for each survival arm. Random survival forest was used for generating the optimal radiomics signature (RS). Statistical metrics for model evaluation included Harrell's concordance index (C-index) and the average cumulative/dynamic AUC throughout follow-up. A clinical model and a combined Rad-clinical model were built for comparison.

RESULTS

The pre-IU (derived from iodine uptake images before NAC) RS performed best for DFS and OS in the testing cohort (C-indices, 0.784 and 0.698; the average cumulative/dynamic AUCs, 0.80 and 0.77). When compared with the clinical model, the radiomics model had significantly higher C-index to predict DFS in the testing cohort (0.784 vs. 0.635, p < 0.001), but no statistical difference was found for OS (0.698 vs. 0.680, p = 0.473). The combined Rad-clinical models showed improved performance in the testing cohort, with C-indices of 0.810 and 0.710 for DFS and OS, respectively.

CONCLUSION

DECT-derived radiomics serves as a promising non-invasive biomarker to predict survival for AGC patients after NAC, providing an opportunity for transforming proper treatment.