Comprehensive evaluation of tumor response better evaluates the efficacy of neoadjuvant chemotherapy and predicts the prognosis in gastric cancer - a post hoc analysis of a single-center randomized controlled trial
Gastric cancer (GC) remains the fifth most prevalent malignancy and the fourth leading cause of global cancer-relevant death, it is often diagnosed at a late stage with a 5-year survival rate of less than 30% . For locally advanced GC (stage II/III), perioperative chemotherapy combined with radical resection has been proven superior to surgery alone by several clinical trials, especially the MAGIC study . The RESOLVE and PRODIGY studies further demonstrate the superiority of perioperative chemotherapy over postoperative chemotherapy . With the introduction of preoperative chemotherapy, the precise evaluation of tumor response to NACT for GC patients has become a pivotal issue. To date, the tumor regression grade (TRG) through pathological evaluation is the most commonly used method for response evaluation and is recommended in the National Comprehensive Cancer Network (NCCN) Guidelines (V4.2024, www.nccn.org/patients ). One drawback of TRG, however, is the absence of a contrast with the pathological status of pre-chemotherapy tumor samples . Computed tomography (CT) is the most widely used imaging modality for assessing the tumor response to NACT based on the Response Evaluation Criteria in Solid Tumors version 1.1 (RECIST v1.1). However, its performance is limited in GC, primarily because only lymph nodes with a short-axis diameter greater than 15 mm are considered target lesions under RECIST v1.1 . To explore more accurate methods for assessing the efficacy of NACT in GC, researchers have conducted extensive investigations, including endoscopic ultrasound (EUS), positron emission tomography-computed tomography (PET-CT), and deep learning models based on radiomics . Over the years, serum tumor markers (TMs) have also been demonstrated as valuable indicators for predicting chemotherapy efficacy, including carcinoembryonic antigen (CEA), carbohydrate antigen (CA)19 − 9, CA125, and CA72-4 . Furthermore, patient-reported outcomes, such as the subjective symptomatic relief experienced by patients, hold potential value in assessing treatment efficacy . Nevertheless, the results across various studies frequently exhibit inconsistency, and a universally accepted approach for assessing NACT efficacy in GC has yet to be established . Current evaluation methods in the literature are often overly complex, limiting their clinical applicability. It is important to highlight that most previous studies have primarily focused on technical enhancements within individual evaluation modalities. However, relying on a solitary evaluation method is inadequate for a comprehensive assessment of NACT efficacy. In this study, we aimed to systematically evaluate and compare the strengths and limitations of prevalent assessment methods for tumor response, thereby further exploring the optimal methods suitable for routine clinical application. To ensure the reliability and feasibility of these methods, we employed long-term efficacy measures, specifically overall survival (OS) and recurrence-free survival (RFS), as validation criteria. 

Study population This study was a post-hoc analysis of data collected during a single-center randomized controlled trial (NCT02404753) which aimed to assess laparoscopic distal gastrectomy after NACT for locally advanced GC . A total of 96 patients had histologically proven gastric adenocarcinoma with a clinical stage of cT2-4aN + M0 and received neoadjuvant chemotherapy from April 23, 2015, to November 16, 2017. Patients were randomized to undergo either laparoscopy-assisted distal gastrectomy with D2 lymphadenectomy or open distal gastrectomy with D2 lymphadenectomy. The primary endpoint was a 3-year recurrence-free survival rate. Almost all patients received standard pre- and post-surgery chemotherapy except an inoperable patient because of rapid disease progression, and a series of efficacy-related examinations on eligible patients were carried out during the chemotherapy course. Detailed comprehensive treatment regimens can be found in our previous publication . All participants from the original study were included in this post-hoc analysis. This post-hoc analysis focuses on tumor response to NACT reflected by examinations, including imaging data, pathological parameters, serum tumor markers, and patient-reported outcomes. The study design was approved by the Peking University Cancer Hospital Ethics Committee. Written informed consent was obtained from each patient for the use of clinical information. Baseline characteristics of eligible patients are shown in Table . The study workflow is shown in Figure . Tumor response assessment The assessment of tumor response to NACT includes endoscopic ultrasonography (EUS), computed tomography (CT), pathology, serum tumor markers (TMs), degree of symptomatic relief, and laparoscopic exploration (LE). The details of assessment methods are as follows. Endoscopic ultrasonography (EUS) assessment The cross-sectional area (EUS-area) and cross-sectional longest diameter (EUS-diameter) of the primary tumor lesion before and after NACT were detected by EUS to evaluate the tumor response. At least a 50% decrease in EUS-area or at least a 30% decrease in the EUS-diameter of tumor lesions was defined as partial response (PR). At least a 25% increase in EUS-area or EUS-diameter of tumor lesions was considered progressive disease (PD). Otherwise, it was defined as stable disease (SD). The tumor response rate was calculated as follows : [12pt]{minimal}
				
				 
				 
				 
				
				
				
				
				$$\:Response\:rate=*100\%$$ ( i = EUS-area or EUS-diameter; EUS-area = the longest diameter * the longest rectangular diameter). Computed tomography (CT) assessment For primary gastric lesion(s), describe the tumor response by calculating the maximum thickness using CT before and after NACT. The thickness was measured after the layer with the largest tumor thickness was found in the cross-sectional, coronal, and sagittal planes, and the maximum value of the three was considered the tumor’s maximum thickness . A maximum thickness of the tumor lesion (CT-thickness) that decreased by more than 30% was defined as partial response (PR), and an increase of more than 20% was defined as progressive disease (PD), otherwise, it was defined as stable disease (SD). The tumor response rate was calculated as follows: [12pt]{minimal}
				
				 
				 
				 
				
				
				
				
				$$\:Response\:rate=*100\%$$ ( i = CT-thickness) For metastatic lymph node(s), the 8th edition of the American Joint Committee on Cancer TNM system was used for tumor N staging before and after therapy: Nx, regional lymph node(s) cannot be assessed; N0, no regional lymph node metastasis; N1, metastasis in one or two regional lymph nodes; N2, metastasis in three or six regional lymph nodes; N3, metastasis in seven or more regional lymph nodes. Diagnostic criteria for metastatic lymph node(s): the short axis of the enlarged lymph node(s) > 1 cm or, in case of lymph node conglomeration, N staging was determined by a multidisciplinary team . Through comparisons of N stage before and after NACT, the CT-N stage was divided into three categories, including downstage, stable and progressive. Pathological assessment According to the NCCN guidelines, the degree of tumor regression after NACT was evaluated as follows: grade 0 (complete response), no residual tumor cells; grade 1 (near-complete response), single cells or rare small groups of cancer cells; grade 2 (partial response), residual cancer cells with evident tumor regression but more than single cells or rare small groups of cancer cells; grade 3 (poor or no response), extensional residual cancer with no evident tumor regression. Based on the tumor regression grade, patients with TRG 0 and 1 tumors were grouped as ‘responders’, whereas TRG 2 and 3 were considered ‘non-responders’. Serum tumor markers (TMs) assessment Peripheral blood samples were obtained from the pre- and post-NACT patients. The tumor response rate was determined by comparing serum tumor marker (including AFP, CEA, CA125, CA19-9, CA72-4) changes before and after NACT. Abnormal positive results were indicated by AFP > 7 ng/ml, CEA > 5 ng/ml, CA72-4 > 6.7 U/ml, CA19-9 > 37 U/ml or CA242 > 20 U/ml. The evaluation criteria for TMs were defined as follows: Effective-abnormal TM(s) decreased or returned to normal levels after NACT; Ineffective-any previously abnormal TM(s) further increased, or new abnormal TM(s) emerged; Unclear-all TM(s) remained within the normal range both before and after NACT. Degree of symptomatic relief The four most common GC-related symptoms were selected to evaluate the degree of patient symptomatic relief, including abdominal pain, sour regurgitation, belching, and abdominal distension. Grades were defined as follows: all alleviated, all of the symptoms improved after NACT; partially alleviated, one to three symptoms improved after NACT; and none alleviated, none of the symptoms improved. Laparoscopic exploration Laparoscopic exploration was adopted before and after NACT to objectively evaluate the tumor response. The tumor response was classified as follows: downstage, the signs of serosal invasion disappeared after NACT; stable, the signs of serosal invasion remained unchanged before and after NACT; progressive, noninvasive gastric serosa turned to invasive serosa or intraperitoneal metastases developed (cytology-positive or metastatic lesions confirmed by biopsy pathology). Survival outcomes Postoperative follow-up was regularly conducted every 3 months for 3 years, and every 6 months for the following years. Overall survival (OS) was defined as the time from laparoscopic exploration to all-cause death or censoring, whichever came first. Recurrence-free survival (RFS) was defined as the time from laparoscopic exploration to cancer-related death, tumor recurrence (local, regional, or distant), or censoring, whichever came first. Statistical analyses Patient characteristics were described using means, standard deviations, frequencies, and percentages. The Chi-square test or Fisher’s exact test was performed as appropriate for categorical variables to correlate clinicopathological variables with different evaluation methods. Survival analyses were conducted with the Kaplan–Meier method, and differences between survival curves were compared using a log-rank test. A Cox proportion-hazards regression model was used to calculate Hazard Ratios (HRs) and 95% Confidence Interval (CI). The discrimination ability of the evaluation indicator was assessed using Harrell’s C statistic, with a C statistic value of > 0.6 as indicative of good discrimination in our study. The c-index was calculated and compared using the “survcomp” R package . Statistical analyses were conducted in Stata 15.0 (StataCorp, Texas) and program language R (version 3.6.1) with a two-sided p -value < 0.05 considered as statistically significant. 

This study was a post-hoc analysis of data collected during a single-center randomized controlled trial (NCT02404753) which aimed to assess laparoscopic distal gastrectomy after NACT for locally advanced GC . A total of 96 patients had histologically proven gastric adenocarcinoma with a clinical stage of cT2-4aN + M0 and received neoadjuvant chemotherapy from April 23, 2015, to November 16, 2017. Patients were randomized to undergo either laparoscopy-assisted distal gastrectomy with D2 lymphadenectomy or open distal gastrectomy with D2 lymphadenectomy. The primary endpoint was a 3-year recurrence-free survival rate. Almost all patients received standard pre- and post-surgery chemotherapy except an inoperable patient because of rapid disease progression, and a series of efficacy-related examinations on eligible patients were carried out during the chemotherapy course. Detailed comprehensive treatment regimens can be found in our previous publication . All participants from the original study were included in this post-hoc analysis. This post-hoc analysis focuses on tumor response to NACT reflected by examinations, including imaging data, pathological parameters, serum tumor markers, and patient-reported outcomes. The study design was approved by the Peking University Cancer Hospital Ethics Committee. Written informed consent was obtained from each patient for the use of clinical information. Baseline characteristics of eligible patients are shown in Table . The study workflow is shown in Figure . 

The assessment of tumor response to NACT includes endoscopic ultrasonography (EUS), computed tomography (CT), pathology, serum tumor markers (TMs), degree of symptomatic relief, and laparoscopic exploration (LE). The details of assessment methods are as follows. Endoscopic ultrasonography (EUS) assessment The cross-sectional area (EUS-area) and cross-sectional longest diameter (EUS-diameter) of the primary tumor lesion before and after NACT were detected by EUS to evaluate the tumor response. At least a 50% decrease in EUS-area or at least a 30% decrease in the EUS-diameter of tumor lesions was defined as partial response (PR). At least a 25% increase in EUS-area or EUS-diameter of tumor lesions was considered progressive disease (PD). Otherwise, it was defined as stable disease (SD). The tumor response rate was calculated as follows : [12pt]{minimal}
				
				 
				 
				 
				
				
				
				
				$$\:Response\:rate=*100\%$$ ( i = EUS-area or EUS-diameter; EUS-area = the longest diameter * the longest rectangular diameter). Computed tomography (CT) assessment For primary gastric lesion(s), describe the tumor response by calculating the maximum thickness using CT before and after NACT. The thickness was measured after the layer with the largest tumor thickness was found in the cross-sectional, coronal, and sagittal planes, and the maximum value of the three was considered the tumor’s maximum thickness . A maximum thickness of the tumor lesion (CT-thickness) that decreased by more than 30% was defined as partial response (PR), and an increase of more than 20% was defined as progressive disease (PD), otherwise, it was defined as stable disease (SD). The tumor response rate was calculated as follows: [12pt]{minimal}
				
				 
				 
				 
				
				
				
				
				$$\:Response\:rate=*100\%$$ ( i = CT-thickness) For metastatic lymph node(s), the 8th edition of the American Joint Committee on Cancer TNM system was used for tumor N staging before and after therapy: Nx, regional lymph node(s) cannot be assessed; N0, no regional lymph node metastasis; N1, metastasis in one or two regional lymph nodes; N2, metastasis in three or six regional lymph nodes; N3, metastasis in seven or more regional lymph nodes. Diagnostic criteria for metastatic lymph node(s): the short axis of the enlarged lymph node(s) > 1 cm or, in case of lymph node conglomeration, N staging was determined by a multidisciplinary team . Through comparisons of N stage before and after NACT, the CT-N stage was divided into three categories, including downstage, stable and progressive. Pathological assessment According to the NCCN guidelines, the degree of tumor regression after NACT was evaluated as follows: grade 0 (complete response), no residual tumor cells; grade 1 (near-complete response), single cells or rare small groups of cancer cells; grade 2 (partial response), residual cancer cells with evident tumor regression but more than single cells or rare small groups of cancer cells; grade 3 (poor or no response), extensional residual cancer with no evident tumor regression. Based on the tumor regression grade, patients with TRG 0 and 1 tumors were grouped as ‘responders’, whereas TRG 2 and 3 were considered ‘non-responders’. Serum tumor markers (TMs) assessment Peripheral blood samples were obtained from the pre- and post-NACT patients. The tumor response rate was determined by comparing serum tumor marker (including AFP, CEA, CA125, CA19-9, CA72-4) changes before and after NACT. Abnormal positive results were indicated by AFP > 7 ng/ml, CEA > 5 ng/ml, CA72-4 > 6.7 U/ml, CA19-9 > 37 U/ml or CA242 > 20 U/ml. The evaluation criteria for TMs were defined as follows: Effective-abnormal TM(s) decreased or returned to normal levels after NACT; Ineffective-any previously abnormal TM(s) further increased, or new abnormal TM(s) emerged; Unclear-all TM(s) remained within the normal range both before and after NACT. Degree of symptomatic relief The four most common GC-related symptoms were selected to evaluate the degree of patient symptomatic relief, including abdominal pain, sour regurgitation, belching, and abdominal distension. Grades were defined as follows: all alleviated, all of the symptoms improved after NACT; partially alleviated, one to three symptoms improved after NACT; and none alleviated, none of the symptoms improved. Laparoscopic exploration Laparoscopic exploration was adopted before and after NACT to objectively evaluate the tumor response. The tumor response was classified as follows: downstage, the signs of serosal invasion disappeared after NACT; stable, the signs of serosal invasion remained unchanged before and after NACT; progressive, noninvasive gastric serosa turned to invasive serosa or intraperitoneal metastases developed (cytology-positive or metastatic lesions confirmed by biopsy pathology). 

The cross-sectional area (EUS-area) and cross-sectional longest diameter (EUS-diameter) of the primary tumor lesion before and after NACT were detected by EUS to evaluate the tumor response. At least a 50% decrease in EUS-area or at least a 30% decrease in the EUS-diameter of tumor lesions was defined as partial response (PR). At least a 25% increase in EUS-area or EUS-diameter of tumor lesions was considered progressive disease (PD). Otherwise, it was defined as stable disease (SD). The tumor response rate was calculated as follows : [12pt]{minimal}
				
				 
				 
				 
				
				
				
				
				$$\:Response\:rate=*100\%$$ ( i = EUS-area or EUS-diameter; EUS-area = the longest diameter * the longest rectangular diameter). 

For primary gastric lesion(s), describe the tumor response by calculating the maximum thickness using CT before and after NACT. The thickness was measured after the layer with the largest tumor thickness was found in the cross-sectional, coronal, and sagittal planes, and the maximum value of the three was considered the tumor’s maximum thickness . A maximum thickness of the tumor lesion (CT-thickness) that decreased by more than 30% was defined as partial response (PR), and an increase of more than 20% was defined as progressive disease (PD), otherwise, it was defined as stable disease (SD). The tumor response rate was calculated as follows: [12pt]{minimal}
				
				 
				 
				 
				
				
				
				
				$$\:Response\:rate=*100\%$$ ( i = CT-thickness) For metastatic lymph node(s), the 8th edition of the American Joint Committee on Cancer TNM system was used for tumor N staging before and after therapy: Nx, regional lymph node(s) cannot be assessed; N0, no regional lymph node metastasis; N1, metastasis in one or two regional lymph nodes; N2, metastasis in three or six regional lymph nodes; N3, metastasis in seven or more regional lymph nodes. Diagnostic criteria for metastatic lymph node(s): the short axis of the enlarged lymph node(s) > 1 cm or, in case of lymph node conglomeration, N staging was determined by a multidisciplinary team . Through comparisons of N stage before and after NACT, the CT-N stage was divided into three categories, including downstage, stable and progressive. 

According to the NCCN guidelines, the degree of tumor regression after NACT was evaluated as follows: grade 0 (complete response), no residual tumor cells; grade 1 (near-complete response), single cells or rare small groups of cancer cells; grade 2 (partial response), residual cancer cells with evident tumor regression but more than single cells or rare small groups of cancer cells; grade 3 (poor or no response), extensional residual cancer with no evident tumor regression. Based on the tumor regression grade, patients with TRG 0 and 1 tumors were grouped as ‘responders’, whereas TRG 2 and 3 were considered ‘non-responders’. 

Peripheral blood samples were obtained from the pre- and post-NACT patients. The tumor response rate was determined by comparing serum tumor marker (including AFP, CEA, CA125, CA19-9, CA72-4) changes before and after NACT. Abnormal positive results were indicated by AFP > 7 ng/ml, CEA > 5 ng/ml, CA72-4 > 6.7 U/ml, CA19-9 > 37 U/ml or CA242 > 20 U/ml. The evaluation criteria for TMs were defined as follows: Effective-abnormal TM(s) decreased or returned to normal levels after NACT; Ineffective-any previously abnormal TM(s) further increased, or new abnormal TM(s) emerged; Unclear-all TM(s) remained within the normal range both before and after NACT. 

The four most common GC-related symptoms were selected to evaluate the degree of patient symptomatic relief, including abdominal pain, sour regurgitation, belching, and abdominal distension. Grades were defined as follows: all alleviated, all of the symptoms improved after NACT; partially alleviated, one to three symptoms improved after NACT; and none alleviated, none of the symptoms improved. 

Laparoscopic exploration was adopted before and after NACT to objectively evaluate the tumor response. The tumor response was classified as follows: downstage, the signs of serosal invasion disappeared after NACT; stable, the signs of serosal invasion remained unchanged before and after NACT; progressive, noninvasive gastric serosa turned to invasive serosa or intraperitoneal metastases developed (cytology-positive or metastatic lesions confirmed by biopsy pathology). 

Postoperative follow-up was regularly conducted every 3 months for 3 years, and every 6 months for the following years. Overall survival (OS) was defined as the time from laparoscopic exploration to all-cause death or censoring, whichever came first. Recurrence-free survival (RFS) was defined as the time from laparoscopic exploration to cancer-related death, tumor recurrence (local, regional, or distant), or censoring, whichever came first. 

Patient characteristics were described using means, standard deviations, frequencies, and percentages. The Chi-square test or Fisher’s exact test was performed as appropriate for categorical variables to correlate clinicopathological variables with different evaluation methods. Survival analyses were conducted with the Kaplan–Meier method, and differences between survival curves were compared using a log-rank test. A Cox proportion-hazards regression model was used to calculate Hazard Ratios (HRs) and 95% Confidence Interval (CI). The discrimination ability of the evaluation indicator was assessed using Harrell’s C statistic, with a C statistic value of > 0.6 as indicative of good discrimination in our study. The c-index was calculated and compared using the “survcomp” R package . Statistical analyses were conducted in Stata 15.0 (StataCorp, Texas) and program language R (version 3.6.1) with a two-sided p -value < 0.05 considered as statistically significant. 

Patient characteristics From April 2015 to November 2017, 96 patients were enrolled in the randomized controlled trial (NCT02404753), in which patients were treated with preoperative treatment plus either laparoscopic gastrectomy or open gastrectomy. One patient in the laparoscopic group had rapid disease progression and did not receive any surgical treatment. Table shows the patient characteristics of the remaining 95 patients. The study population was predominantly male (69.5%), and the mean age was 58 years. The majority of study participants had adenocarcinoma (91.6%) and received R0 resection (96.8%). Primary screening for prognosis-related assessment methods in univariate analysis The efficacy of NACT was evaluated by comparing the examination results obtained before and after NACT, and the long-term efficacy of NACT was assessed using OS and RFS. Univariate analysis was performed to primary screen for prognosis-related assessment methods (Table ). Considering that the primary lesion could not be considered a target lesion in the RECIST system, we calculated the maximum thickness changes of primary lesions and used 30% shrinkage of thickness as the cutoff point. We also calculated the EUS area and diameter according to the JCGC criteria to evaluate tumor response to NACT . In the univariate analysis, only CT-thickness and TMs were significantly associated with OS ( P = 0.033 and P = 0.048). Unexpectedly, the HRs for EUS- area and EUS-diameter in the SD/PD group were significantly lower than those observed in the PR group, with statistical significance. This finding implies a more favorable prognosis for the SD/PD group, which is inconsistent with established clinical expectations. Consequently, EUS-area and EUS-diameter were excluded from further analyses. Tumor response evaluation based on CT scan In our cohort, only 3% (3/95) of patients were identified as having metastatic lymph nodes with a short-axis diameter exceeding 15 mm, which could be considered target lesions for evaluation under the RECIST criteria. Therefore, we calculated the change in the thickness of primary lesions and compared OS and RFS between the groups stratified by CT-thickness. The results showed that the no-response (PD) group identified by CT-thickness had significantly worse OS ( P = 0.017, Fig. A) and relatively worse RFS ( P = 0.053, Fig. B) which indicated that CT-thickness was associated with prognosis. Moreover, ypT and ypN are both known to act as important prognostic markers in GC patients after NACT (Figure ), SD/PD patients identified by CT-thickness after NACT tend to have larger tumors ( P < 0.001, Table ), higher ypT stage ( P = 0.013, Table ) and higher ypTNM stage ( P = 0.007, Table ). Tumor response evaluation based on TMs Given the prognostic value of serum tumor markers (TMs) and their role in feedback for residual tumor load immediately post-NACT , we analyzed the correlation between serum TMs and disease outcomes. Compared with the TM ineffective group, the effective group showed better OS and RFS ( P = 0.037 and P = 0.158, Fig. A- B ). A higher proportion of TMs-effective patients were distributed in the PR, TRG 0–1, and no recurrence group which correlated with response to NACT (Fig. C). Moreover, patients with residual TMs within 3 months following surgery had significantly worse OS and RFS ( P = 0.003 and P < 0.001, Figure S3A-B). Of note, the proportion of patients with residual TMs was significantly higher in the TM-ineffective group (Figure S3C). No clinicopathologic variables were found to be significantly correlated with TM-based efficacy evaluation (Table ). Tumor response evaluation based on TRG In clinical practice, the responses to NACT could manifest in various forms, as shown in Fig. A. Subsequent analysis of the collected data revealed that 43 out of 59 (72.9%) non-responders (assessed by CT-thickness) exhibited no disease progression. Among these, 10 (23.3%) patients were identified as TRG 0–1. This finding suggested that TRG scores could further enhance discrimination performance in identifying responders. As is shown in Fig. B, only a few responders presented with both TRG 0–1 and CT-thickness PR, and most responders manifested either TRG 0–1 or CT-thickness PR. These results suggested that a combination of TRG scores with CT-thickness could identify more responders to NACT, thereby increasing the sensitivity of tumor response evaluation. However, the TRG was not identified as a prognostic factor according to our univariate analysis (Table ), possibly due to the small sample size. Given the TRG scores are widely used in NACT response evaluation, and the prognostic ability was demonstrated by several studies previously , we therefore detected the predictive ability of TRG for long-term efficacy using Kaplan-Meier survival curves. Results showed that TRG scores could distinguish groups with different OS and RFS, but the difference was not statistically significant (Fig. C- ). Moreover, patients with positive vascular and neural invasion predominated in the TRG 2–3 group ( P = 0.007 and P < 0.001, Table ), and TRG scores had a significant association with ypT and ypTNM stage (both P < 0.001, Table ). Comprehensive tumor response evaluation with a combination of CT-thickness, TRG, and TMs While the combination of CT-thickness and TRG could improve responders’ discrimination further, the prognostic differences between responders (defined as CT-thickness PR or TRG 0/1) and non-responders have not yet achieved statistical significance (Figure S4A). Given that TMs presented significant prognostic value (Fig. A- ), we added ineffective TMs as an exclusion criterion for responders. Finally, we established a comprehensive response evaluation method for NACT including CT-thickness, TRG, and TMs, as shown in Fig. A. Specifically, the patients were identified as responders if they showed effectiveness in either CT-thickness or TRG with TM-ineffective as the exclusion criteria. When these three evaluation methods were pooled together, we achieved significant differences between responders and non-responders in OS ( P = 0.013, Fig. B) as well as RFS ( P = 0.012, Fig. C). This combination evaluation could discriminate almost all recurrent patients except two discordant cases and one patient with rapid disease progression after chemotherapy (Fig. D). Laparoscopic exploration demonstrated that responders identified by combination evaluation had a higher proportion of T downstaging than other evaluation approaches (Figure S4B). Moreover, this combination was able to identify all positive conversion of intraperitoneal lavage cytology, which was considered a disease progressive factor, and almost all of the recurrent patients were determined as non-responders according to the comprehensive evaluation (Figure S4C). To assess the predictive accuracies of various evaluation methods, we employed Harrell ’s C -index, a widely recognized metric for measuring predictive accuracy in survival models . Compared with CT-thickness, TRG, or tumor markers alone, the combination of CT-thickness, TRG, and TMs exhibited the best discrimination performance (C-index = 0.637 and P = 0.027 for OS; C-index = 0.625 and P = 0.026 for RFS, Table ). Further analysis revealed that patients classified as responders by the integrated assessment had notably smaller tumor volumes, fewer vascular thrombi, less neural invasion, and lower ypT, ypN, and ypTNM stages (all P < 0.05, Table ). 

From April 2015 to November 2017, 96 patients were enrolled in the randomized controlled trial (NCT02404753), in which patients were treated with preoperative treatment plus either laparoscopic gastrectomy or open gastrectomy. One patient in the laparoscopic group had rapid disease progression and did not receive any surgical treatment. Table shows the patient characteristics of the remaining 95 patients. The study population was predominantly male (69.5%), and the mean age was 58 years. The majority of study participants had adenocarcinoma (91.6%) and received R0 resection (96.8%). 

The efficacy of NACT was evaluated by comparing the examination results obtained before and after NACT, and the long-term efficacy of NACT was assessed using OS and RFS. Univariate analysis was performed to primary screen for prognosis-related assessment methods (Table ). Considering that the primary lesion could not be considered a target lesion in the RECIST system, we calculated the maximum thickness changes of primary lesions and used 30% shrinkage of thickness as the cutoff point. We also calculated the EUS area and diameter according to the JCGC criteria to evaluate tumor response to NACT . In the univariate analysis, only CT-thickness and TMs were significantly associated with OS ( P = 0.033 and P = 0.048). Unexpectedly, the HRs for EUS- area and EUS-diameter in the SD/PD group were significantly lower than those observed in the PR group, with statistical significance. This finding implies a more favorable prognosis for the SD/PD group, which is inconsistent with established clinical expectations. Consequently, EUS-area and EUS-diameter were excluded from further analyses. 

In our cohort, only 3% (3/95) of patients were identified as having metastatic lymph nodes with a short-axis diameter exceeding 15 mm, which could be considered target lesions for evaluation under the RECIST criteria. Therefore, we calculated the change in the thickness of primary lesions and compared OS and RFS between the groups stratified by CT-thickness. The results showed that the no-response (PD) group identified by CT-thickness had significantly worse OS ( P = 0.017, Fig. A) and relatively worse RFS ( P = 0.053, Fig. B) which indicated that CT-thickness was associated with prognosis. Moreover, ypT and ypN are both known to act as important prognostic markers in GC patients after NACT (Figure ), SD/PD patients identified by CT-thickness after NACT tend to have larger tumors ( P < 0.001, Table ), higher ypT stage ( P = 0.013, Table ) and higher ypTNM stage ( P = 0.007, Table ). 

Given the prognostic value of serum tumor markers (TMs) and their role in feedback for residual tumor load immediately post-NACT , we analyzed the correlation between serum TMs and disease outcomes. Compared with the TM ineffective group, the effective group showed better OS and RFS ( P = 0.037 and P = 0.158, Fig. A- B ). A higher proportion of TMs-effective patients were distributed in the PR, TRG 0–1, and no recurrence group which correlated with response to NACT (Fig. C). Moreover, patients with residual TMs within 3 months following surgery had significantly worse OS and RFS ( P = 0.003 and P < 0.001, Figure S3A-B). Of note, the proportion of patients with residual TMs was significantly higher in the TM-ineffective group (Figure S3C). No clinicopathologic variables were found to be significantly correlated with TM-based efficacy evaluation (Table ). 

In clinical practice, the responses to NACT could manifest in various forms, as shown in Fig. A. Subsequent analysis of the collected data revealed that 43 out of 59 (72.9%) non-responders (assessed by CT-thickness) exhibited no disease progression. Among these, 10 (23.3%) patients were identified as TRG 0–1. This finding suggested that TRG scores could further enhance discrimination performance in identifying responders. As is shown in Fig. B, only a few responders presented with both TRG 0–1 and CT-thickness PR, and most responders manifested either TRG 0–1 or CT-thickness PR. These results suggested that a combination of TRG scores with CT-thickness could identify more responders to NACT, thereby increasing the sensitivity of tumor response evaluation. However, the TRG was not identified as a prognostic factor according to our univariate analysis (Table ), possibly due to the small sample size. Given the TRG scores are widely used in NACT response evaluation, and the prognostic ability was demonstrated by several studies previously , we therefore detected the predictive ability of TRG for long-term efficacy using Kaplan-Meier survival curves. Results showed that TRG scores could distinguish groups with different OS and RFS, but the difference was not statistically significant (Fig. C- ). Moreover, patients with positive vascular and neural invasion predominated in the TRG 2–3 group ( P = 0.007 and P < 0.001, Table ), and TRG scores had a significant association with ypT and ypTNM stage (both P < 0.001, Table ). 

While the combination of CT-thickness and TRG could improve responders’ discrimination further, the prognostic differences between responders (defined as CT-thickness PR or TRG 0/1) and non-responders have not yet achieved statistical significance (Figure S4A). Given that TMs presented significant prognostic value (Fig. A- ), we added ineffective TMs as an exclusion criterion for responders. Finally, we established a comprehensive response evaluation method for NACT including CT-thickness, TRG, and TMs, as shown in Fig. A. Specifically, the patients were identified as responders if they showed effectiveness in either CT-thickness or TRG with TM-ineffective as the exclusion criteria. When these three evaluation methods were pooled together, we achieved significant differences between responders and non-responders in OS ( P = 0.013, Fig. B) as well as RFS ( P = 0.012, Fig. C). This combination evaluation could discriminate almost all recurrent patients except two discordant cases and one patient with rapid disease progression after chemotherapy (Fig. D). Laparoscopic exploration demonstrated that responders identified by combination evaluation had a higher proportion of T downstaging than other evaluation approaches (Figure S4B). Moreover, this combination was able to identify all positive conversion of intraperitoneal lavage cytology, which was considered a disease progressive factor, and almost all of the recurrent patients were determined as non-responders according to the comprehensive evaluation (Figure S4C). To assess the predictive accuracies of various evaluation methods, we employed Harrell ’s C -index, a widely recognized metric for measuring predictive accuracy in survival models . Compared with CT-thickness, TRG, or tumor markers alone, the combination of CT-thickness, TRG, and TMs exhibited the best discrimination performance (C-index = 0.637 and P = 0.027 for OS; C-index = 0.625 and P = 0.026 for RFS, Table ). Further analysis revealed that patients classified as responders by the integrated assessment had notably smaller tumor volumes, fewer vascular thrombi, less neural invasion, and lower ypT, ypN, and ypTNM stages (all P < 0.05, Table ). 

Through the incorporation of neoadjuvant therapy, significant progress has been made in perioperative treatment for LAGC . Neoadjuvant therapy presents several potential advantages, including diminishing tumor burden and improving the R0 section rates. More importantly, it offers the opportunity to test a tumor response to a specific therapeutic regimen and subsequently tailor adjuvant therapy based on this response, thereby improving overall efficacy. Therefore, refining a robust system for evaluating the NACT efficacy in GC has become a critically important clinical concern. Although the 2018 NCCN guidelines introduced “response evaluation” after NACT, comprehensive assessments of tumor response post-NACT were not conducted in major perioperative chemotherapy studies for GC. For instance, the MAGIC trial provided no specific explanation , and the FNCLCC/FFCD 9703 trial employed CT scans to assess disease progression after the final cycle of preoperative chemotherapy. However, it explicitly stated that the WHO or RECIST criteria were not employed for efficacy evaluation . According to RECIST criteria, the stomach, as a non-solid organ, is considered to have non-measurable lesions, while lymph nodes are measurable only if their short axis is ≥ 1.5 cm. However, a substantial proportion of LAGC cases do not exhibit lymph nodes with a short axis ≥ 1.5 cm, rendering radiological efficacy evaluation unfeasible . This limitation may also explain why major clinical studies on perioperative chemotherapy for GC have not adopted RECIST criteria for response assessment. Notably, studies attempting to use RECIST criteria for efficacy evaluation have reported markedly inconsistent results . Furthermore, our results align with previous studies, indicating that ypTNM staging, especially ypT and ypN, has significant prognostic value . However, inaccurate pretreatment clinical tumor staging renders the evaluation of tumor downstaging methods unreliable . Currently, the most commonly used evaluation method is TRG scores, while it is difficult to always perform well according to previous studies as well as this study . Of note, in this study, a considerable proportion of TRG 3 patients were deemed identified as responders through CT-thickness evaluation and demonstrated favorable prognoses. This finding highlights the limited sensitivity of the TRG scoring system. It is evident that there is a lack of standardized criteria for evaluating the efficacy of NACT in GC, and the reproducibility and prognostic predictive value of current evaluation systems are inadequate. To address this issue, based on our prospective clinical study, we conducted a post-hoc analysis to evaluate the efficacy of NACT from various perspectives by considering quality-of-life scales, EUS, CT scan, pathological evaluation, tumor markers, and LE to explore the best assessment method in clinical practice. One of the strengths of this study is that we implemented almost all easily accessible clinical evaluation methods, contributing to the comprehensiveness and reliability of our results. This study utilized recurrence, metastasis, and disease outcomes as indicators of long-term efficacy to compare the accuracy of different efficacy evaluation methods. Significant differences in prognosis were observed among the PR, SD, and PD patients identified by CT-thickness, and further analysis showed that compared with SD/PD patients, PR patients exhibited significantly lower ypT and ypTNM stages and smaller tumor sizes. This result suggested that thickness shrinkage could reflect primary tumor regression and downstaging, usually accompanied by metastatic lymph node regression and downstaging. The CT-thickness evaluation method used in our study requires only the maximum thickness that would be reported in the medical records by most hospitals, which endows CT-thickness with high accessibility and repeatability. Notably, the high heterogeneity of GC leads to varying treatment responses following NACT, such as discrepancies between morphological changes and pathological alterations. In our study, 10 patients assessed as non-responders based on CT-thickness were identified as responders through TRG scoring, thereby enhancing the sensitivity of responder identification. Although TRG scoring did not demonstrate significant prognostic value in our univariate analysis, likely due to the small sample size, its prognostic utility has been well-documented in numerous previous studies. Considering that TRG scoring is another widely adopted method for evaluating NACT efficacy and is the only approach recommended by the NCCN guidelines for GC, we incorporated TRG grading alongside CT-thickness for identifying responders. Consistent with previous studies, univariate analysis revealed that TM is also a strong prognostic factor. Unexpectedly, the C-index for TMs was even higher than that of the integrated evaluation method. Fluctuations in TM levels frequently occur in patients following NACT. In addition to the tumor’s intrinsic chemosensitivity, TM levels are influenced by other confounders surrounding NACT settings, such as chemotherapy duration, dosage, and the patient’s tolerance. The relatively high C-index for TMs observed in this study may lack reproducibility. Furthermore, nearly half of the patients were classified as unevaluable based on TMs, highlighting the challenges of using TMs alone for efficacy evaluation due to the low incidence of positive events and insufficient sample size. Of note, the TM-ineffective group had many more patients with residual TMs within 3 months following surgery and had significantly worse OS and RFS. Thus, we infer that TM evaluation has the advantage of identifying chemoresistant or progressive patients during NACT. Among all efficacy evaluation methods, unexpectedly, the results of EUS evaluation showed an opposing trend that better HRs in the SD/PD group compared to the PR group, which is counterintuitive from a clinical perspective. Stable or progressive disease is typically associated with worse outcomes. This discrepancy likely arises from the inherent limitations of endoscopic ultrasonography (EUS) in post-treatment evaluation. Tissue fibrosis and edema induced by chemoradiotherapy often present as hypoechoic signals on EUS, which may result in responders being misclassified into the SD/PD group. So far, the inherent limitations of CT and pathological evaluation have prompted many researchers to explore and optimize these methods to achieve more accurate assessments of therapeutic efficacy. However, most prior studies have focused on technical improvements within a single evaluation approach. A key innovation of our study lies in the first-time integration of CT-thickness, TRG, and TMs, enabling tumor response to be assessed from three complementary perspectives: tumor morphology, pathology, and clinical biomarkers. It improves sensitivity through the combination of CT-thickness and TRG, which identified more responders, and increases specificity through the adoption of the TM evaluation method, which removed potential chemoresistant patients. This multi-dimensional approach provides a more comprehensive and objective evaluation compared to methods relying on a single parameter. Another significant strength of this study lies in its use of routine, widely accessible examinations in most hospitals to maximize the accuracy of treatment response evaluation. This strategy avoids the need for high costs, specialized equipment, or advanced computational techniques, ensuring its feasibility and scalability in diverse clinical settings. The guiding role of neoadjuvant therapy in shaping postoperative treatment strategies for patients cannot be overlooked. Accurately evaluating the efficacy of NACT is an urgent clinical challenge. For non-responders, the evaluation results can prompt early consideration of alternative treatment strategies or participation in clinical trials, thus avoiding prolonged exposure to potentially ineffective therapies. Furthermore, given the low response rate to NACT in GC, there is currently intense exploration of efficacy-related biomarkers and the development of targeted therapies. In this context, a definitive NACT efficacy is a key prerequisite for the exploration of efficacy-related biomarkers, thus advancing personalized and precision treatment. The integrated evaluation tool we propose may provide enhanced utility in such studies relative to the exclusive application of TRG scoring. Yet, we have to acknowledge that there were some limitations to our study. First, only the CT and EUS were compared in this study, although the predictive and prognostic capacity of PET-CT, MRI, and deep learning-based image analysis has been confirmed by several studies . However, we excluded these imaging methods because of their high cost and poor popularity; Second, this study is a post-hoc analysis of data from our previous prospective clinical study (NCT02404753) which included only GC located in the distal stomach and the sample size of 96 patients is relatively small. Although the result is promising, external validation including GC on the upper stomach and in other centers is highly needed to confirm its feasibility. 

Collectively, we constructed a simple, accessible, reproducible efficacy evaluation method, including CT-thickness, TRG, and tumor markers, with both high sensitivity and specificity. As a simple but cost-effective method, this combination tool not only facilitates early consideration of alternative treatment strategies for patients who do not respond to NACT, thereby improving overall treatment efficacy, but also plays a foundational role in exploring efficacy biomarkers and the development of targeted therapies. Limited by its small sample size, our issues serve as the triggers of yet prospective population-based studies to refine our criteria in the future. 

Below is the link to the electronic supplementary material. Supplementary Material 1 

