Post-Progression Immunotherapy and Prognostic Factors in HER2-Negative Advanced Gastric Cancer: A Retrospective Analysis of 118 Cases

Post-Progression Immunotherapy and Prognostic Factors in HER2-Negative Advanced Gastric Cancer: A Retrospective Analysis of 118 Cases | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Post-Progression Immunotherapy and Prognostic Factors in HER2-Negative Advanced Gastric Cancer: A Retrospective Analysis of 118 Cases Zhirun Cai, Shusheng Wu, Haoyu Wang, Xudong Liu, Wenxi Dang, Zhihua Zhang, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7059672/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Purpose: Advanced gastric cancer (AGC) has a poor prognosis, and optimal management post-progression on immune checkpoint inhibitors (ICIs) remains undefined. This study evaluates survival outcomes of continuing ICIs beyond progression in HER2-negative AGC, focusing on progression patterns and biomarker correlates. Methods: A retrospective cohort of HER2-negative AGC patients treated with ICIs at Anhui Provincial Hospital (2018–2022) was analyzed. Eligible patients (n=118) had ≥3 months of stable disease before progression. Primary endpoints included progression-free survival (PFS1, PFS2) and overall survival (OS). Kaplan-Meier analysis, Cox regression, and biomarker assessments (neutrophil-to-lymphocyte ratio [NLR], Systemic Immune-Inflammation Index [SII]) were performed. Results: Median PFS1 was 6.8 months. Patients continuing ICIs post-progression (CIBP group) demonstrated significantly improved PFS2 (12.9 vs. 11.2 months, p=0.020) and OS (19.0 vs. 13.5 months, p=0.019) compared to discontinuers (DIBP). Systemic progression (SP) was predominant; patients with acquired resistance (ICI exposure >6 months) and systemic progression derived the greatest benefit from CIBP. Elevated NLR/SII predicted reduced post-progression efficacy. Conclusion: Continuing ICIs post-progression improves survival in HER2-negative AGC, particularly for SP with acquired resistance. Progression patterns and NLR/SII may guide clinical decisions. Prospective trials integrating dynamic biomarker monitoring are warranted to validate rechallenge strategies. retrospectively registered： IRB approval number:2025-XZY-01 Advanced Gastric Cancer immunotherapy treatment beyond progression Progression pattern Drugresistancepattern inflammatory biomarkers Figures Figure 1 Figure 2 Figure 3 INTRODUCTION AGC remains a major global health burden with extremely poor prognosis, particularly in East Asian countries (e.g., China, Japan, South Korea), where incidence and mortality rates are significantly higher compared to other regions [ 1 – 3 ] In recent years, ICIs have brought new hope to cancer treatment [ 4 – 5 ] . ICIs, by inhibiting programmed death-1 (PD-1) and its ligand PD-L1, activate the immune system to recognize and attack tumor cells, thus improving survival outcomes for patients. For HER2-negative AGC patients, the combination of ICIs with chemotherapy has revolutionized the first-line treatment standards [ 6 ] . The Keynote-859 study demonstrated a slight survival benefit when pembrolizumab was added to chemotherapy regimens (FP or Capox) compared to chemotherapy alone. In the CheckMate 649 study, nivolumab combined with chemotherapy significantly extended the median overall survival (mOS) to 14.4 months (vs. 11.1 months in the chemotherapy group, HR = 0.71) for patients with PD-L1 CPS ≥ 5, showing higher objective response rates across all CPS subgroups. Based on these findings, nivolumab combined with chemotherapy regimens (such as FOLFOX/XELOX) is recommended as a first-line treatment in NCCN, ESMO, and CSCO guidelines. Furthermore, the KEYNOTE-062 study indicated that pembrolizumab monotherapy was particularly beneficial for patients with PD-L1 CPS ≥ 10 (Shitara et al., 2020), highlighting the importance of biomarker-driven treatments. However, evidence-based consensus on optimal management strategies for AGC following disease progression remains critically lacking.Traditional second-line treatments continue to be dominated by chemotherapy drugs such as irinotecan and paclitaxel or combinations with ramucirumab, which are not based on the latest first-line treatments [ 7 – 8 ] . Although these can control tumor progression in the short term, their efficacy is often not sustainable, and the considerable side effects associated with chemotherapy hinder improvements in patient survival and quality of life. Currently, ICIs have become a research focus in the second-line and subsequent treatments for gastric cancer [ 9 – 10 ] . For example, Keynote-059 explored the impact of pembrolizumab in second-line and later treatments for advanced GC patients, where those with CPS>10 achieved better survival expectations than those treated solely with chemotherapy. In the ATTRACTION-2 study, significant survival benefits were observed in patients treated with nivolumab, regardless of PD-L1 expression. Thus, multiple studies have demonstrated the clinical efficacy of nivolumab and pembrolizumab, especially in patients with high PD-L1 expression [ 11 – 12 ] . Increasingly, research focuses on combining ICIs with chemotherapy, anti-angiogenic drugs, and other treatment modalities to enhance the immune system's anti-tumor effects and overcome the limitations of single treatment modalities [ 13 – 14 ] . In this context, exploring more effective treatments with fewer side effects, and identifying patient subgroups more likely to benefit from immunotherapy based on relapse patterns and inflammatory markers, has become a critical issue in the field of gastric cancer treatment. Despite existing studies showing significant clinical efficacy of ICIs in combination treatments for various cancers, their clinical value in HER2-negative AGC remains under-researched. Therefore, this study aims to explore the effectiveness of ICIs in second-line and subsequent treatments for HER2-negative AGC patients, assess their potential in combination with other drugs, and identify populations more likely to benefit from immunotherapy. Additionally, this study has revealed the predictive value of inflammatory markers (such as NLR, SII) in immunotherapy across lines, identified independent risk factors affecting patient prognosis, and provided a theoretical basis for personalized treatment. Through these studies, we not only aim to clarify the clinical value of immunotherapy in the treatment of HER2-negative AGC across treatment lines, but also to explore the optimal strategies for combining immunotherapy with other therapeutic modalities. By using precise biomarker screening, we aim to identify patients who are most likely to benefit from immunotherapy, thereby providing stronger support for clinical practice. METHODS AND MATERIALS This study is a single-center retrospective analysis that collected clinical data from patients with pathologically confirmed HER2-negative metastatic or advanced gastric and gastroesophageal junction adenocarcinoma treated at Anhui Provincial Hospital between November 2018 and November 2022. These patients had previously received immunotherapy combined with chemotherapy as a first-line standard treatment and experienced disease progression. The objective is to evaluate the efficacy of ICIs in a second-line treatment setting for patients with HER2-negative AGC, particularly in combination with other therapeutic modalities such as chemotherapy and anti-angiogenic drugs. Patient Eligibility : A total of 118 patients meeting the inclusion and exclusion criteria were selected for this study(Fig. 1 ). Inclusion criteria : 1).Patients pathologically or cytologically diagnosed with AGC (AGC) or gastroesophageal junction adenocarcinoma;2).Patients confirmed to have HER2-negative gastric cancer;3).Patients with disease progression or recurrence after first-line therapy failure;4).Patients who have received at least one cycle of an immune checkpoint inhibitor (such as nivolumab or pembrolizumab) as second-line or subsequent therapy;5).ECOG performance status score of 0–2 (indicating the ability to carry out daily activities without significant restrictions);6).At least one measurable lesion according to RECIST 1.1 criteria. Exclusion criteria : 1).Patients with other malignancies: those with past or concurrent malignancies (except for treated basal cell carcinoma of the skin, squamous cell carcinoma and/or treated in-situ cervical cancer and/or breast cancer), which may affect the assessment of treatment efficacy; 2).Patients positive for HER2 and using targeted drugs such as trastuzumab (Herceptin) or pertuzumab;3). Patients who have received any radiotherapy, chemotherapy, or antitumor treatment within four weeks before the first administration of the study drug;4).Patients participating in clinical trials that have not yet been unblinded. Treatment Methods In the case I studied, all patients were treated with ICIs as part of the standard treatment regimen during first-line treatment, and at second-line treatment, based on the data collected, the patients were divided into two groups, one group receiving immunotherapy and the other group receiving no immunotherapy. There were 61 patients who stopped immunotherapy during second-line therapy. Most of these patients received chemotherapy or a combination of chemotherapy and anti-angiogenic therapy. Chemotherapy is usually done according to the traditional gastric cancer treatment regimen, such as paclitaxel and platinum drugs, and anti-angiogenic therapy usually uses drugs such as apatinib. These drugs inhibit the blood supply to the tumor, which can slow the progression of the disease. Fifty-seven patients continued to receive immunotherapy during second-line therapy, mainly using ICIs in combination with chemotherapy, some of which included antiangiogenic agents. This treatment strategy combines the suppression of tumor immune evasion by immunotherapy, the cytotoxic effects of chemotherapy, and the vascular suppression effects of anti-angiogenic therapy with multiple mechanisms to improve the impact of therapy and delay the progression of the disease. Follow-up methods and primary outcomes : During the patient's treatment, we will monitor the patient's disease development and survival status according to the routine arrangement. The follow-up plan will be carried out according to the standard clinical practice, including imaging studies that can be used for evaluation, such as CT scan or MRI, and also carry out laboratory examinations. This is done to assess how the tumor is responding to treatment and for signs of disease progression. When the disease progresses or the patient dies, we will record the corresponding time, including PFS1, which is the time from the first immunotherapy cycle to the first progression, and PFS2, which is the time from the first immunotherapy cycle to the second progression or death of the patient, and OS, It is the time from the start of the first immunotherapy cycle to the date of death of the patient or the last follow-up of the survivor. The main endpoint of this study is OS. The deadline for follow-up investigation is set at June 1, 2024. For patients who are still alive at the last follow-up, we will confirm their survival status and review relevant data on the day of the last follow-up. Secondary endpoints : We analyzed the mechanisms of resistance to first-line immunotherapy and the progression patterns following resistance. Resistance patterns were classified into primary resistance and acquired resistance. Primary resistance was defined as patients with PFS ≤ 6 months after first-line treatment, while acquired resistance was defined as patients with PFS > 6 months after first-line treatment. Progression patterns included Mixed progression (MP) and SP. MP was defined as disease progression occurring in only one lesion (including target lesions, non-target lesions, or new lesions) in patients with 1–3 target lesions, or progression occurring in ≤ 2 lesions in patients with > 3 target lesions. SP was defined as progression in > 1 lesion (including target lesions, non-target lesions, or new lesions) in patients with 1–3 target lesions, or progression in > 2 lesions (including target lesions, non-target lesions, or new lesions) in patients with > 3 target lesions. Group Definition CIBP group: Patients who continued to receive immune checkpoint inhibitor therapy after disease progression following initial immunotherapy. DIBP group: Patients who ceased immunotherapy after disease progression and switched to other treatment modalities such as chemotherapy or anti-angiogenic drugs. This study used OS as the endpoint and determined the optimal cutoff values for continuous variables (such as inflammatory markers) by combining the receiver operating characteristic (ROC) curve with the Youden Index. The cutoff values for the four indicators were as follows:SII ≤ 213vs. >213,NLR ≥ 3 vs. < 3, Platelet-to-Lymphocyte Ratio PLR ≥ 106.46 vs. < 106.46, Lymphocyte-to-Monocyte Ratio (LMR) ≥ 5.87 vs. < 5.87. Research Methods and Statistical Analysis : This study employed a retrospective cohort design to evaluate the efficacy and predictive characteristics of immune checkpoint inhibitor (ICI) treatment beyond progression in HER2-negative AGC patients. First, the PFS1, PFS2 and OS were compared between the CIBP group and DIBP group using the Kaplan-Meier method. The differences between groups were assessed using the log-rank test, and the hazard ratios (HR) along with their 95% confidence intervals (CI) were calculated. The results demonstrated a significant survival benefit for patients receiving the continuation of immunotherapy. In order to identify the subgroups of patients who would benefit most from immunotherapy, subgroup analysis was conducted according to disease characteristics such as tumor location, pattern of progression, and type of drug resistance. The stratified Cox proportional risk model was used to calculate HR and 95% CI for each subgroup, and forest maps were generated. In this way, the HR and CI of each subgroup of CIBP treatment can be visually represented. Doing these things can help this paper identify subgroups with clear survival benefits. Finally, to identify meaningful clinical predictive features, Cox proportional hazards regression analysis was performed. Univariate analysis included factors such as gender, age, tumor location, ECOG score, progression pattern, resistance type, SII, NLR, PLR, LMR, and treatment strategy (CIBP vs. DIBP) as variables.Features with a p-value < 0.05 in univariate analysis were further included in the multivariate Cox model, and stepwise regression was applied to select independent prognostic factors. All statistical analyses were considered significant at a p-value of less than 0.05. RESULTS Patient Characteristics ： From November 2018 to November 2022, a total of 118 patients diagnosed with HER2-negative AGC and treated with immunotherapy were included in the study at Anhui Provincial Hospital. Patients who received more than two cycles of ICIs were categorized into two groups based on their treatment regimens: the DIBP group (N = 61, 51.60%) and the CIBP group (N = 57, 48.30%). All patients experienced disease progression after first-line immunotherapy, with 74 patients (62.70%) presenting with SP. The objective response rate (ORR) of first-line treatment was 57.60% （Table 1). Table 1: Patient baseline demographic and clinical characteristics Variables Overall DIBP GROUP CIBP GROUP p-value N = 118 N = 61 N = 57 SEX, n(%) 0.2132 Female 31(26.27%) 19(31.15%) 12(21.05%) Male 87(73.73%) 42(68.85%) 45(78.95%) AGE, n(%) 0.9022 ≤60 49(41.53%) 25(40.98%) 24(42.11%) ＞60 69(58.47%) 36(59.02%) 33(57.89%) Location, n(%) 0.7522 CEGJ 50(42.37%) 25(40.98%) 25(43.86%) GC 68(57.63%) 36(59.02%) 32(56.14%) Tumor Differentiation, n(%) 0.5033 High 5(4.24%) 4(6.56%) 1(1.75%) Moderate 15(12.71%) 7(11.48%) 8(14.04%) Poor 98(83.05%) 50(81.97%) 48(84.21%) Best response to previous line, n(%) 0.240 CR+PR 68(57.60%) 32(52.50%) 36(63.20%) SD+PD 50(42.40%) 29(47.5%) 21(36.80%) ECOG, n(%) 0.206 0+1 76(64.40%） 36(59.00%) 40(70.205） 2 42（35.60%) 25(41.00%) 17(29.80%) Liver metastases, n(%) 0.678 yes 52(44.1%) 28（45.90%) 24(42.10%) no 66(55.0%) 33（54.10%） 33（57.90%） Lung metastases, n(%) 0.222 yes 16（13.60%） 6(9.80%) 10(17.50%） no 102（86.40%) 55(90.20%) 47（82.50%） Progression pattern, n(%) 0.776 MP 44(37.30%) 22(36.10%) 22(38.60%) SP 74(62.70%) 39(63.90%) 35(61.40%) Drug resistance pattern, n(%) 0.441 Primary resistance 54(45.8%) 30(49.20%) 24(42.10%) Acquired resistance 64(54.2%） 31(50.8%) 33(57.9%) Neoadjuvanttherapy, n(%) 0.651 yes 109（92.40%） 57（93.40%） 52（91.20%） no 9（7.60%） 4（6.60%） 5（8.80%） T, n(%) 0.7910 T1+2 47(39.80%) 25(41.0%) 22(38.60%) T3+4 71(60.2%) 36(59.0%) 35(61.40%) N, n(%) 0.4880 N0 26(22.00%) 15(24.60%) 11(19.30%) N1+2+3 92(72.00%) 46(75.40%) 46(80.70%) M, n(%) 0.109 M0 13（11.00%） 4(6.60)% 9(15.80%） M1 105（89.00%） 57（93.40%） 48（84.20%） SII, Median (Q1, Q3) 369.84 (243.28,583.71) 352.50 (234.98,695.51) 397.09 (247.93,566.25) 0.8357 NLR, Median (Q1, Q3) 2.53 (1.76,3.68) 2.51 (1.63-4.06) 2.63 (1.94,3.31) 0.8865 PLR, Median (Q1, Q3) 146.48 (100.34,195.83) 142.59 (92,75,215.32) 148.03 (107.06,194.67) 0.5482 LMR, Median (Q1, Q3) 2.80 (1.70,3.64) 2.52 (1.69,3.45) 3.02 (1.75,4.40) 0.1590 CEA, Median (Q1, Q3) 5.86 (3.02,23.17) 6.51 (3.01,20.81) 5.12 (3.09,24.29) 0.8504 CA199, Median (Q1, Q3) 19.34 (4.85,400.30) 28.91 (4.85,400.30) 17.82 (4.91,384.48) 0.7164 Hb, Mean ± SD Mean ± SD 108.32 ± 17.13 106.20 ± 15.45 110.60 ± 18.64 0.0864 BMI, Median (Q1, Q3) 20.67 (20.38, 20.76) 20.67 (20.67, 20.94) 20.67 (20.28, 20.67) 0.5864 Abbreviations: CR :Complete Response; PR :Partial Response; SD :Stable Disease; PD - Progressive Disease. Analysis of Progression-Free Survival and Overall Survival ： The Kaplan-Meier survival curve analysis showed that the median progression-free survival (mPFS1), second progression-free survival (mPFS2), and mOS for the entire cohort of 118 patients were 6.8 months (95% CI: 5.82-7.78), 11.8 months (95% CI: 10.59-12.95), and 14.5 months (95% CI: 11.62-17.38), respectively. Based on treatment strategies after progression, the mPFS1 for the CIBP group (n = 57) and the DIBP group (n = 61) were 6.87 months (95% CI: 5.83-7.92) and 6.30 months (95% CI: 4.54-8.06), respectively, with a log-rank P = 0.253. There was no significant difference in PFS1 between the two groups during the first-line treatment, indicating consistent efficacy of the initial immunotherapy across both groups. However, during the second-line and subsequent treatment phases, the mPFS2 for the CIBP group and the DIBP group were 12.9 months (95% CI: 10.4-15.3) and 11.2 months (95% CI: 9.1-13.3), respectively, with a log-rank P = 0.020. The mOS for the CIBP group and the DIBP group were 19.0 months (95% CI: 13.1-25.0) and 13.5 months (95% CI: 12.2-14.9), respectively, with a log-rank P = 0.019. These results suggest that continuing immunotherapy after progression improves survival outcomes (Figure 2). Subgroup Analysis: AGC patients were further stratified based on their disease progression type and resistance patterns. Initially, in the SP group, the mPFS2 for the CIBP group was 13.4 months (95% CI: 11.1-15.7 months), significantly higher than the 10.2 months (95% CI: 8.6-11.8 months) for the DIBP group (P = 0.02). Additionally, the mOS for the CIBP group was 21.4 months (95% CI: 17.8-25.0 months), compared to 15.5 months (95% CI: 13.3-17.7 months) for the DIBP group (P = 0.03), indicating that patients in the CIBP group had significantly better outcomes than those in the DIBP group. Immunotherapy beyond progression significantly extended both PFS2 and OS in patients with SP, demonstrating clear therapeutic benefits of continued immunotherapy in improving survival rates. However, in the mixed progression group, the difference in PFS2 and OS between the group that continued immunotherapy and the group that stopped immunotherapy was not statistically significant. For example, the median PFS2 in the CIBP group was 11.6 months, which was in the 95% CI range, that is, 9.4-13.8 months. The median PFS2 in the DIBP group was 10.9 months, and its 95% CI range was 8.5-13.3 months, where the P-value was 0.25. Similarly, the median OS of CIBP group and DIBP group is also available. The median OS of CIBP group is 14.2 months, and the 95% CI range is 12.2-16.2 months; the median OS of DIBP group is 13.7 months, and the 95% CI range is 11.5-15.9 months, and the P value here is 0.29. From these results, it can be seen that for patients with mixed progression, immunotherapy beyond progression does not significantly prolong PFS2 or OS. In this study, patients were divided into acquired resistance group and primary resistance group according to their resistance patterns to immunotherapy, and then the same analytical method was used to evaluate PFS2 and OS in these two groups. Among the acquired resistance groups, the CIBP group was significantly better than the DIBP group. The median PFS2 in the CIBP group was 12.3 months, and its 95% CI range was 10.1-14.5 months, which was significantly higher than the 9.8 months in the DIBP group, and the 95% CI range in the DIBP group was 7.7-11.9 months. The P value here is 0.01. Similarly, the median OS in the CIBP group was 18.8 months, with a 95% CI range of 14.6-23.0 months, while the median OS in the DIBP group was 14.2 months, with a 95% CI range of 12.4-16.0 months, with a P value of 0.04, as can be seen from these results. Immunotherapy beyond the advanced stage can significantly prolong PFS2 and OS in patients with acquired resistance, suggesting that continued immunotherapy may confer additional survival benefits in these patients. Among the primary drug resistance groups, there was no statistically significant difference in PFS2 and OS between the CIBP group and the DIBP group. The median PFS2 in the CIBP group was 8.6 months, and the 95% CI range was 6.4-10.8 months; the DIBP group was 7.9 months, and the 95% CI range was 5.6-10.2 months. The P value here is 0.32. Furthermore, the median OS for the CIBP and DIBP groups was 12.4 months, with a 95% CI range of 10.2-14.6 months, and 11.6 months, with a 95% CI range of 9.3-13.9 months, with a P value of 0.37. In the different subgroups distinguished by various inflammatory markers, higher SII, PLR, and lower NLR, LMR provided significant survival benefits for patients receiving CIBP. Overall, this study demonstrates significant subgroup differences in the efficacy of immunotherapy beyond progression for AGC patients, particularly in those with SP and acquired resistance, showing clear survival benefits. For patients with mixed progression and primary resistance, the effects of immunotherapy beyond progression were more limited (Figure 3). Cox Proportional Hazards Model Analysis ： To further explore independent predictors of survival and to identify which patients are more likely to benefit from immunotherapy beyond progression, this study utilized the Cox proportional hazards model to analyze multiple potential factors. The primary focus was on the independent predictors of OS. Hemoglobin levels,SII,NLR,PLR,LMR among other hematological indices, were derived from the most recent clinical assessments prior to second-line treatment for all patients who progressed after first-line therapy. Initial univariate analysis revealed that the SP, higher SII and NLR were independent risk factors for OS, while acquired resistance and higher hemoglobin levels were independent protective factors for OS. Among them, the progression pattern was significantly correlated with OS, indicating that the characteristics of disease progression play an important role in prognosis. Compared to MP, patients with SP had poorer prognosis and higher HR. Inflammatory markers such as SII and NLR were also associated with OS, indicating that inflammation-related biomarkers play an important role in cancer progression and patient survival.The results of the multivariate analysis further confirmed that the progression pattern (MP/SP, HR = 2.168, 95% CI [1.261-3.727]; p = 0.005), resistance pattern (Primary resistance/Acquired resistance, HR = 0.279, 95% CI [0.163-0.476]; p < 0.001), SII (HR = 3.201, 95% CI [1.348-7.604]; p = 0.008), and NLR (HR = 2.962, 95% CI [1.674-5.241]; p < 0.001) were identified as independent factors influencing OS. There was a significant difference between primary resistance and acquired resistance within the resistance pattern. Additionally, higher values of SII and NLR indicated poorer prognosis for the patients (Table 2). Table 2. Cox Univariate and Multivariate Analysis Table for Different Patient Characteristics Univariate analysis Multivariate analysis HR 95%CI P HR 95%CI P Sex 0.717 0.442-1.163 0.178 Age 0.729 0.466-1.141 0.167 Location 1.239 0.786-1.953 0.357 Tumor differentiation 1.533 0.837-2.806 0.166 Best response to previous line 0.823 0.519-1.304 0.406 Ecog 0.876 0.514-1.492 0.626 Liver metastases 0.809 0.513-1.276 0.362 Lung metastases 0.919 0.458-1.845 0.813 Progression pattern 2.057 1.247-3.394 0.005 2.168 1.261-3.727 0.005 Drugresistance pattern 0.256 0.159-0.412 <0.001 0.279 0.163-0.476 <0.001 Neoadjuvanttherapy 0.670 0.244-1.839 0.437 T 1.279 0.801-2.042 0.302 N 1.563 0.885-2.758 0.124 M 1.044 0.520-2.097 0.903 SII 2.985 1.367-6.521 0.006 3.201 1.348-7.604 0.008 NLR 5.084 3.065-8.434 <0.001 2.962 1.674-5.241 <0.001 PLR 0.945 0.998-1.002 1.000 LMR 1.236 0.497-3.072 0.648 CEA 1.000 1.000-1.001 0.528 CA199 1.000 1.000-1.000 0.845 Hb 0.986 0.974-0.999 0.029 0.99 0.976-1.004 0.149 BMI 0.954 0.880-1.035 0.260 GROUP 0.583 0.370-0.921 0.021 0.364 0.219-0.606 <0.001 DISCUSSION In recent years, ICIs have given new hope to the treatment of gastric cancer by blocking the interaction between programmed death receptor 1 and its ligand, programmed death ligand 1, or by preventing the B7 molecule on antigen-presenting cells from binding to the co-stimulatory receptor CD28 on CD4 + T cells. To activate the patient's own immune system, so that the immune system has the ability to recognize and eliminate tumor cells [15-17] . Ajani et al. conducted the CheckMate 649 trial in 2021, which evaluated nabuliumab in combination with chemotherapy as a first-line treatment for patients with advanced gastroesophageal cancer, including esophageal adenocarcinoma, and was a particularly key milestone in gastric cancer immunotherapy. It confirms the therapeutic efficacy of ICIs in patients with tumors that are positive for programmed death ligand 1 [18-19] . In addition, Sundar et al. studied the therapeutic effect of first-line ICIs in gastric cancer and esophageal adenocarcinoma patients with low expression of programmed death ligand 1 in 2022, and found that some patients could obtain clinical benefits from treatment, thus providing a basis for therapeutic strategies for this patient group [20] . Based on these critical findings, in April 2021, the U.S. Food and Drug Administration approved nabuliumab in combination with chemotherapy for the treatment of advanced or metastatic gastric cancer, gastroesophageal nodular cancer, and esophageal adenocarcinoma, regardless of programmed death ligand 1 expression status [21-22] . AGC is a rapidly progressing malignant tumor with generally poor prognosis. For HER2-negative AGC patients, traditional chemotherapy agents such as irinotecan and paclitaxel remain commonly used as second-line treatment options [23] . However, chemotherapy is often associated with significant adverse reactions and limited long-term efficacy, highlighting the urgent need for effective second-line and subsequent treatments after first-line therapy failure. In recent years, the PD-1 inhibitor nivolumab has demonstrated breakthrough potential in the treatment of AGC [24-25] . The pivotal ATTRACTION-2 trial confirmed that nivolumab provides significant survival benefits for Asian patients with AGC who have failed chemotherapy, establishing the foundation for the use of PD-1 inhibitors in second-line and subsequent treatments. Given that immunotherapy may continue to exert therapeutic effects by modulating tumor immune escape mechanisms even after initial disease progression, the strategy of continuing ICIs in second-line treatment after progression on first-line immunotherapy has become a key research focus [26] . This study systematically evaluated survival differences between patients receiving different second-line treatment strategies and different patient subgroups. The results showed that CIBP resulted in a significant improvement in survival outcomes. It also highlighted the heterogeneity of CIBP efficacy and identified subgroups of patients who were more likely to benefit from continuous immunotherapy. And to evaluate the outcome of treatment, which is a key direction for future research. In this study, CIBP patients showed significant improvements in both PFS2 and OS compared to DIBP patients, and these findings suggest that survival benefits may be achieved in certain patient populations by continuing immunotherapy after disease progression [27] . In contrast, for patients with MP, continued immunotherapy after disease progression did not significantly prolong their survival, indicating that these patients' response to continuous immunotherapy was relatively low [28-29] . Many studies have highlighted the critical role of the tumor immune microenvironment in influencing the pattern of tumor progression and the effect of immunotherapy. The interaction between tumor progression and the immune microenvironment is complex and dynamic. In general, infiltration and activation of cytotoxic T lymphocytes significantly affect tumor growth, metastasis, and response to therapy. In patients with AGC SP, tumors may undergo multiple stages of immune escape and immunosuppression. At this stage, the tumor immune microenvironment may show increased immune activity, which is specifically manifested as increased T cell infiltration, increased PD-1 / PD-L1 pathway activity, and the tumor is in an immune "hot" state. Under such an immune environment, ICIs can restore the effector function of T cells. Improve the immune system's ability to recognize and destroy tumor cells [30] . In patients with mixed-progression AGC, the tumor immune microenvironment may lack sufficient immune cell infiltration and effective cytotoxic T lymphocytes (ctl), and the tumor microenvironment may also contain a large number of immunosuppressive cells, such as regulatory T cells Tregs and myelogenic suppressor cells MDSCs. These immunosuppressive cells suppress the immune response, thus limiting the therapeutic effectiveness of ICIs. Tumors characterized by MP exhibit more complex growth patterns. In these tumors, some areas are responsive to immunotherapy, while other areas are resistant to immunotherapy. This intratumoral heterogeneity complicates the effective targeting of immunotherapy, suggesting that the role of SP in gastric cancer may be related to different immune escape mechanisms [31] . Instead, it only increased the tumor burde [32-33] . The specific mechanism by which tumor immune microenvironment and immune escape mechanism affect immunotherapy is the focus of future research. Our findings highlight the clinical heterogeneity of immunotherapy efficacy in AGC patients with different progression modes. In previous studies, most patients with gastric cancer showed limited sensitivity to single-drug ICI, after their disease had progressed. Overcoming resistance to ICIs and developing more effective combination therapy has become the core challenge in systemic treatment of gastric cancer. Relevant studies have been mentioned in literature [34-35] . In this study, the CIBP regimen significantly improved PFS2 and OS in patients who developed acquired resistance to first-line immunotherapy, and patients in the CIBP group survived longer than those in the DIBP group. These findings suggest that patients with acquired resistance are more likely to benefit from immune rechallenge therapy for survival. Different from patients with acquired drug resistance, the survival rate of patients with primary drug resistance has not been significantly improved after receiving immunotherapy. Previous studies have shown that primary drug resistant tumors generally show strong intrinsic resistance to immunotherapy from the very beginning. This reflects its inherent genetic characteristics, high tumor heterogeneity, and immune "cold" TME. Immune "cold" TME is characterized by a greater number of bone marrow cells and a lack of interferon-gamma (IFN-γ) signaling pathways, factors that impede effective immune activation, possibly due to insufficient tumor antigenicity, or defects in antigen presentation to T cells, and primary drug-resistant tumors that may have an overactive immune checkpoint pathway [36] . For example, high PD-L1 expression, which directly inhibits t cell activity. The immunosuppressive microenvironment, characterized by resistance to dense fibrosis, low T-cell infiltration, and high levels of immunosuppressive cytokines, can limit the function of immune effectors, as described in the literature , suggesting that the immune system has not effectively "trained" itself to recognize and attack tumors, making a sustained immune response more difficult [37] .There is a particular need for comprehensive research to improve immunotherapy outcomes in patients with primary drug resistance. Compared with other conditions, patients with acquired drug resistance generally experience a longer period of immune selection pressure, which was defined as PFS1 >6 months in our study, and their tumor microenvironment may retain some immune reactivity. It's like there's dynamic PD-L1 expression or there's tumor-infiltrated lymphocyte infiltration. Continuous ICI therapy can reverse the T-cell exhaustion by inhibiting LAG-3 / TIM-3, or by increasing antigen presentation, like upregating mhc-1 to reactivate anti-tumor immunity. If combination therapy is to be developed, It should be based on some understanding of the mechanisms by which immune regulation and drug resistance may exist, rather than randomly combining existing treatments. Exploring new immune checkpoint targets, such as LAG-3, VISTA, TIM-3, and TIGIT, and developing treatments for them are promising ways to overcome resistance. In our study, NLR was identified as an independent risk factor for OS, as was the case for hepatocellular carcinoma and colorectal cancer. These results indicate that markers of systemic inflammation can be used as prognostic indicators for various cancer types, which are also related in reference [38-39] . Chronic inflammation will promote tumor growth and metastasis, and cause drug resistance to treatment, which indicates that adjusting the immune microenvironment may be the key to overcoming drug resistance and improving the therapeutic effect of ICI. Future studies should combine liquid biopsy techniques, such as circulating tumor DNA analysis to monitor clonal evolution, with spatial transcriptomics to dynamically characterize the process of tumor microenvironment remodeling. Although there are some valuable findings in this study, there are also some shortcomings. Due to the retrospective and single-center design, the sample size is relatively small, which may limit the universality of our findings. Large-scale, multicenter prospective studies are necessary to validate our observations and to determine the best treatment strategy for patients with AGC receiving immunotherapy, as mentioned in references, and although the pattern of progression and type of resistance are identified as key determining factors of treatment effect [40-41] . But this study did not explore other possible biomarkers, such as tumor mutation load and microsatellite instability. These factors may give more accurate predictive information, and can also help optimize the selection of patients for immunotherapy. The mechanism of primary drug resistance is not fully understood, and future research should make elucidation of the molecular and immunological basis of primary drug resistance a priority, and promote the development of innovative strategies to overcome drug resistance. Such as using ICI in combination with other immunomodulators, or targeting immunosuppressive cells in the tumor microenvironment. Our study provides new evidence to support the use of ICIs in the treatment of AGC after progression. In particular, continued immunotherapy significantly extended PFS and OS in patients with hyperprogression and acquired resistance. In addition, the results of our study highlight the clinical value of systemic inflammatory markers as prognostic indicators, and emphasize the importance of personalized treatment and patient selection. Conversely, the limited benefit of immunotherapy in patients with mixed progression patterns and primary resistance points to the need to study the mechanisms of resistance and develop new combination treatment strategies. As the field of immunotherapy continues to evolve, future research should focus on perfecting treatment protocols and finding ways to improve clinical outcomes in patients with AGC. And the advantages of immunotherapy after the disease has progressed may also be applied to other malignancies, giving hope to patients who have few treatment options. Declarations Acknowledgments: We appreciate all the authors for their valuable contributions to the completion of this study. Funding :The authors declare that no funds, grants, or other support were received during the preparation of this manuscript. Competing Interests :The authors have no relevant financial or non-financial interests to disclose. Author Contributions :All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Zhirun Cai, Haoyu Wang and Shusheng Wu. The first draft of the manuscript was written by Zhirun Cai and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Zhirun Cai,Shusheng Wu and Haoyu Wang contributed equally to this work and should be considered co-first authors. Data Availability :The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request. Ethics approval :This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of The First Affiliated Hospital of University of Science and Technology of China (2025-XZY-01).The clinical data used in the study were obtained from the routine medical records of the patients, and all patients provided written informed consent upon admission, authorizing the use of their medical data for scientific research. The research data will be used solely for scientific analysis and will not be used for any commercial purposes or other unauthorized objectives. References Yang WJ, Zhao HP, Yu Y, et al. Updates on global epidemiology, risk and prognostic factors of gastric cancer. World J Gastroenterol. 2023;29(16):2452-2468. doi:10.3748/wjg.v29.i16.2452 Wu SL, Zhang Y, Fu Y, Li J, Wang JS. Gastric cancer incidence, mortality and burden in adolescents and young adults: a time-trend analysis and comparison among China, South Korea, Japan and the USA. BMJ Open . 2022;12(7):e061038. doi:10.1136/bmjopen-2022-061038 Yang H, Zhou S, Wang W, et al. The Trends of Gastric Cancer in China From 1990 to 2019 and Predictions to 2040: A Bayesian Age-Period-Cohort Prediction Study. Cancer Control . 2024;31:10732748241293982. doi:10.1177/10732748241293982 Shiravand Y, Khodadadi F, Kashani SMA, et al. Immune Checkpoint Inhibitors in Cancer Therapy. Curr Oncol . 2022;29:3044-3060. doi:10.3390/curroncol29050247 Bagchi S, Yuan R, Engleman EG. Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. Annu Rev Pathol: Mech Dis . 2021;16(1):223-249. doi:10.1146/annurev-pathol-042020-042741 Ren J, Wang K, Meng Q, et al. A multicenter retrospective study of the combination of immune checkpoint inhibitors and chemotherapy regimens with or without liver metastasis for the first-line treatment of advanced gastric cancer. Ther Adv Med Oncol . 2024;16:17588359241308389. doi:10.1177/17588359241308389 Kawamoto Y, Yuki S, Sawada K, et al. Phase II Study of Ramucirumab Plus Irinotecan Combination Therapy as Second-Line Treatment in Patients with Advanced Gastric Cancer: HGCSG1603. Oncologist . 2022;27(8):e642-e649. doi:10.1093/oncolo/oyac086 Sato Y, Yamashita H, Yagi K, Nomura S, Seto Y. Ramucirumab Beyond Disease Progression After Paclitaxel Plus Ramucirumab in Gastric Cancer: A Phase II Trial. Anticancer Res . 2024;44(7):3125-3131. doi:10.21873/anticanres.17126 Nie C, Xu W, Lv H, et al. Tailoring second-line or above therapy for patients with advanced or metastatic gastric cancer: A multicenter real-world study. Front Pharmacol . 2022;13:1043217. doi:10.3389/fphar.2022.1043217 Denlinger CS, Matkowskyj KA, Mulcahy MF. Gastric and Esophageal Cancers: Guidelines Updates. J Natl Compr Canc Netw . 2021;19(5.5):639-643. doi:10.6004/jnccn.2021.5006 Lin SY, Yang CY, Liao BC, et al. Tumor PD-L1 Expression and Clinical Outcomes in Advanced-stage Non-Small Cell Lung Cancer Patients Treated with Nivolumab or Pembrolizumab: Real-World Data in Taiwan. J Cancer . 2018;9(10):1813-1820. doi:10.7150/jca.24985 Xiong L, Cai Y, Zhou X, et al. Optimum Immunotherapy Method According to PD-L1 Expression in Advanced Lung Cancer: A Network Metac-Analysis. Future Oncol . 2022;18(7):883-896. doi:10.2217/fon-2021-1217 Lee WS, Yang H, Chon HJ, Kim C. Combination of anti-angiogenic therapy and immune checkpoint blockade normalizes vascular-immune crosstalk to potentiate cancer immunity. Exp Mol Med . 2020;52(9):1475-1485. doi:10.1038/s12276-020-00500-y Song Y, Fu Y, Xie Q, Zhu B, Wang J, Zhang B. Anti-angiogenic Agents in Combination With Immune Checkpoint Inhibitors: A Promising Strategy for Cancer Treatment. Front Immunol. 2020;11:1956. doi:10.3389/fimmu.2020.01956 Lao Y, Shen D, Zhang W, He R, Jiang M. Immune Checkpoint Inhibitors in Cancer Therapy—How to Overcome Drug Resistance? Cancers . 2022;14(15):3575. doi:10.3390/cancers14153575 Qiu J, Cheng Z, Jiang Z, Gan L, Zhang Z, Xie Z. Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment. Int J Mol Sci . 2024;25(10):5490. doi:10.3390/ijms25105490 Nagasaki J, Ishino T, Togashi Y. Mechanisms of resistance to immune checkpoint inhibitors. Cancer Sci . 2022;113(10):3303-3312. doi:10.1111/cas.15497 Janjigian YY, Ajani JA, Moehler M, et al. LBA7 Nivolumab (NIVO) plus chemotherapy (Chemo) or ipilimumab (IPI) vs chemo as first-line (1L) treatment for advanced gastric cancer/gastroesophageal junction cancer/esophageal adenocarcinoma (GC/GEJC/EAC): CheckMate 649 study. Ann Oncol. 2021;32:S1329-S1330. doi:10.1016/j.annonc.2021.08.2131 Noori M, Fayyaz F, Zali MR, Bashash D. Predictive value of PD-L1 expression in response to immune checkpoint inhibitors for gastric cancer treatment: a systematic review and meta-analysis. Expert Rev Anticancer Ther. 2023;23(9):1029-1039. doi:10.1080/14737140.2023.2238896 Zhao JJ, Yap DWT, Chan YH, et al. Low Programmed Death-Ligand 1–Expressing Subgroup Outcomes of First-Line Immune Checkpoint Inhibitors in Gastric or Esophageal Adenocarcinoma. J Clin Oncol. 2022;40(4):392-402. doi:10.1200/JCO.21.01862 Sugarman R, Betts KA, Nie X, Hartman J, Nguyen H. Nivolumab Plus Chemotherapy for Advanced Gastric, Gastroesophageal Junction, and Esophageal Adenocarcinoma: Analysis of Number Needed To Treat and Number Needed To Harm. Clin Ther. 2023;45(11):1155-1158. doi:10.1016/j.clinthera.2023.08.014 Janjigian YY, Shitara K, Moehler M, et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet. 2021;398(10294):27-40. doi:10.1016/S0140-6736(21)00797-2 Ishiguro A, Kawamoto Y, Yuki S, et al. HGCSG 1603: Phase II study of ramucirumab and irinotecan combination therapy as second-line treatment in patients with metastatic or advanced gastric cancer. J Clin Oncol. 2019;37(4_suppl):TPS183-TPS183. doi:10.1200/JCO.2019.37.4_suppl.TPS183 Takei S, Kawazoe A, Shitara K. The New Era of Immunotherapy in Gastric Cancer. Cancers. 2022;14(4):1054. doi:10.3390/cancers14041054 Kono K, Nakajima S, Mimura K. Current status of immune checkpoint inhibitors for gastric cancer. Gastric Cancer. 2020;23(4):565-578. doi:10.1007/s10120-020-01090-4 Lefebvre C, Martin E, Hendriks LEL, et al. Immune checkpoint inhibitors versus second line chemotherapy for patients with lung cancer refractory to first line chemotherapy. Respir Med Res. 2020;78:100788. doi:10.1016/j.resmer.2020.100788 Rouhani SJ, Bestvina CM. Immunotherapy partners after progression: Right place, right time? Cancer. 2023;129(2):181-183. doi:10.1002/cncr.34558 Lv J, Yan W, Zhang R, et al. Progressive Disease with Mixed Response After Immunotherapy in Non-Small Cell Lung Cancer. J Inflammation Res. 2024;Volume 17:6317-6327. doi:10.2147/JIR.S477244 Ge X, Zhang Z, Zhang S, et al. Immunotherapy beyond progression in patients with advanced non-small cell lung cancer. Transl Lung Cancer Res . 2020;9(6):2391-2400. doi:10.21037/tlcr-20-1252 Binnewies M, Roberts EW, Kersten K, et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med. 2018;24(5):541-550. doi:10.1038/s41591-018-0014-x Vitale I, Shema E, Loi S, Galluzzi L. Intratumoral heterogeneity in cancer progression and response to immunotherapy. Nat Med. 2021;27(2):212-224. doi:10.1038/s41591-021-01233-9 Li B, Liang L, Chen Y, et al. Circ_0008287 promotes immune escape of gastric cancer cells through impairing microRNA-548c-3p-dependent inhibition of CLIC1. Int Immunopharmacol. 2022;111:108918. doi:10.1016/j.intimp.2022.108918 Ma ES, Wang ZX, Zhu MQ, Zhao J. Immune evasion mechanisms and therapeutic strategies in gastric cancer. World J Gastrointest Oncol. 2022;14(1):216-229. doi:10.4251/wjgo.v14.i1.216 Baxter MA, Middleton F, Cagney HP, Petty RD. Resistance to immune checkpoint inhibitors in advanced gastro-oesophageal cancers. Br J Cancer. 2021;125(8):1068-1079. doi:10.1038/s41416-021-01425-7 He P, Ma L, Xu B, et al. Research progress and future directions of immune checkpoint inhibitor combination therapy in advanced gastric cancer. Ther Adv Med Oncol. 2024;16:17588359241266156. doi:10.1177/17588359241266156 Jhunjhunwala S, Hammer C, Delamarre L. Antigen presentation in cancer: insights into tumour immunogenicity and immune evasion. Nat Rev Cancer. 2021;21(5):298-312. doi:10.1038/s41568-021-00339-z Haist M, Stege H, Grabbe S, Bros M. The Functional Crosstalk between Myeloid-Derived Suppressor Cells and Regulatory T Cells within the Immunosuppressive Tumor Microenvironment. Cancers. 2021;13(2):210. doi:10.3390/cancers13020210 Dolan RD, Laird BJA, Horgan PG, McMillan DC. The prognostic value of the systemic inflammatory response in randomised clinical trials in cancer: A systematic review. Crit Rev Oncol Hematol. 2018;132:130-137. doi:10.1016/j.critrevonc.2018.09.016 Kim MR, Kim AS, Choi HI, Jung JH, Park JY, Ko HJ. Inflammatory markers for predicting overall survival in gastric cancer patients: A systematic review and meta-analysis. Coelho-Filho OR, ed. PLOS One. 2020;15(7):e0236445. doi:10.1371/journal.pone.0236445 Coutzac C, Pernot S, Chaput N, Zaanan A. Immunotherapy in advanced gastric cancer, is it the future? Crit Rev Oncol Hematol . 2019;133:25-32. doi:10.1016/j.critrevonc.2018.10.007 Zhao Y, Bai Y, Shen M, Li Y. Therapeutic strategies for gastric cancer targeting immune cells: Future directions. Front Immunol. 2022;13:992762. doi:10.3389/fimmu.2022.992762 Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7059672","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":481742424,"identity":"2deca18a-6020-4efc-99ee-871c7f88ed6b","order_by":0,"name":"Zhirun Cai","email":"","orcid":"","institution":"Wannan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Zhirun","middleName":"","lastName":"Cai","suffix":""},{"id":481742426,"identity":"b76feb52-e3ce-4c0e-bdcb-e67ed760b64d","order_by":1,"name":"Shusheng Wu","email":"","orcid":"","institution":"The First Affiliated Hospital of University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Shusheng","middleName":"","lastName":"Wu","suffix":""},{"id":481742427,"identity":"7577033f-1644-4132-8aa0-c440d46a4307","order_by":2,"name":"Haoyu Wang","email":"","orcid":"","institution":"University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Haoyu","middleName":"","lastName":"Wang","suffix":""},{"id":481742428,"identity":"46cf1ce3-268c-4362-9a6a-52433862fb45","order_by":3,"name":"Xudong Liu","email":"","orcid":"","institution":"Wannan Medical College","correspondingAuthor":false,"prefix":"","firstName":"Xudong","middleName":"","lastName":"Liu","suffix":""},{"id":481742429,"identity":"d63e45dd-d741-41aa-8851-fca2fc2fa732","order_by":4,"name":"Wenxi Dang","email":"","orcid":"","institution":"Anhui Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenxi","middleName":"","lastName":"Dang","suffix":""},{"id":481742430,"identity":"72bfefef-3080-40d8-8583-b4ce5e194e31","order_by":5,"name":"Zhihua Zhang","email":"","orcid":"","institution":"University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Zhihua","middleName":"","lastName":"Zhang","suffix":""},{"id":481742439,"identity":"ff1b5e25-007b-4f44-889a-3b457f544692","order_by":6,"name":"Wen Li","email":"","orcid":"","institution":"University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Wen","middleName":"","lastName":"Li","suffix":""},{"id":481742440,"identity":"663a399b-fa1b-403e-9686-e5ddf2cd75c4","order_by":7,"name":"Mengge Li","email":"","orcid":"","institution":"The First Affiliated Hospital of University of Science and Technology of China","correspondingAuthor":false,"prefix":"","firstName":"Mengge","middleName":"","lastName":"Li","suffix":""},{"id":481742442,"identity":"ee657ed2-0351-492f-912f-8995dfdcbcc6","order_by":8,"name":"Yifu He","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA9ElEQVRIiWNgGAWjYDACZsYHzAwMNvzIYgYEtDAbALWkSTYgqSaghQGs5TAJWgyOM7NJF1Scl5CfkWPAzPPnjzwDe/M2CYaaO7i1HAZqmXHmtoTBDaAW3jYDwwaeY2USDMee4dHCf0yat+12nYEESEuDQQKDRI6ZBGPDYfy28P47B3MYUIv8G2K0NByQYAA5jIcNZAsPfi2Sh5mZrXmOJUsYnHlWcHBum7FhG09asUXCMdxa+M4fZrzNU2MnId+evPHBmz9y8vzshzfe+FCDW4vCARhLIMMAzGYDEQk4NTAwyDfAWPzHH+BRNwpGwSgYBSMZAACwgUqZyZQv5wAAAABJRU5ErkJggg==","orcid":"","institution":"The First Affiliated Hospital of University of Science and Technology of China","correspondingAuthor":true,"prefix":"","firstName":"Yifu","middleName":"","lastName":"He","suffix":""}],"badges":[],"createdAt":"2025-07-06 19:53:09","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7059672/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7059672/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86298914,"identity":"3000b75c-a340-4c48-bcad-bd7282a4e6fb","added_by":"auto","created_at":"2025-07-09 05:58:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":176519,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Study Population Screening\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-7059672/v1/113c66115577937fa4b59426.png"},{"id":86298912,"identity":"967883fa-1fc2-46a5-be0d-3f4f8a078328","added_by":"auto","created_at":"2025-07-09 05:58:55","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":124220,"visible":true,"origin":"","legend":"\u003cp\u003eKaplan-Meier curves of the PFS1, PFS2, and OS of patients with CIBP and DIBP. Note: (a) The mPFS1 were 6.87and 6.30 months in patients with CIBP and DIBP , respectively (p = 0.253). (b) The mPFS2 were 12.9 and 11.2 months in patients with CIBP and DIBP , respectively (p = 0.020). (c) The m0S were 19.0 and 13.5 months in patients with CIBP and DIBP , respectively (p = 0.019).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-7059672/v1/ba59c8d9a6abd1ec23d4808a.png"},{"id":86298913,"identity":"8b71d61d-68c8-4f86-a010-637ab4b5cf80","added_by":"auto","created_at":"2025-07-09 05:58:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":228102,"visible":true,"origin":"","legend":"\u003cp\u003eSubgroup Analysis Forest Plot of the PFS2 (a) and OS (b) of patients with CIBP and DIBP.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-7059672/v1/5200212c163e4b889d1011c1.png"},{"id":86647896,"identity":"64c61228-f17b-4334-8513-b0f4fcf25fa2","added_by":"auto","created_at":"2025-07-14 09:09:35","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1510553,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7059672/v1/7f86702c-e0fa-45f6-aaae-a8f2b1c9f1b9.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Post-Progression Immunotherapy and Prognostic Factors in HER2-Negative Advanced Gastric Cancer: A Retrospective Analysis of 118 Cases","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eAGC remains a major global health burden with extremely poor prognosis, particularly in East Asian countries (e.g., China, Japan, South Korea), where incidence and mortality rates are significantly higher compared to other regions\u003csup\u003e[\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e–\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]\u003c/sup\u003e\u003c/p\u003e\u003cp\u003eIn recent years, ICIs have brought new hope to cancer treatment\u003csup\u003e[\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e–\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]\u003c/sup\u003e. ICIs, by inhibiting programmed death-1 (PD-1) and its ligand PD-L1, activate the immune system to recognize and attack tumor cells, thus improving survival outcomes for patients. For HER2-negative AGC patients, the combination of ICIs with chemotherapy has revolutionized the first-line treatment standards\u003csup\u003e[\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]\u003c/sup\u003e. The Keynote-859 study demonstrated a slight survival benefit when pembrolizumab was added to chemotherapy regimens (FP or Capox) compared to chemotherapy alone. In the CheckMate 649 study, nivolumab combined with chemotherapy significantly extended the median overall survival (mOS) to 14.4 months (vs. 11.1 months in the chemotherapy group, HR = 0.71) for patients with PD-L1 CPS ≥ 5, showing higher objective response rates across all CPS subgroups. Based on these findings, nivolumab combined with chemotherapy regimens (such as FOLFOX/XELOX) is recommended as a first-line treatment in NCCN, ESMO, and CSCO guidelines. Furthermore, the KEYNOTE-062 study indicated that pembrolizumab monotherapy was particularly beneficial for patients with PD-L1 CPS ≥ 10 (Shitara et al., 2020), highlighting the importance of biomarker-driven treatments.\u003c/p\u003e\u003cp\u003eHowever, evidence-based consensus on optimal management strategies for AGC following disease progression remains critically lacking.Traditional second-line treatments continue to be dominated by chemotherapy drugs such as irinotecan and paclitaxel or combinations with ramucirumab, which are not based on the latest first-line treatments\u003csup\u003e[\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e–\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]\u003c/sup\u003e. Although these can control tumor progression in the short term, their efficacy is often not sustainable, and the considerable side effects associated with chemotherapy hinder improvements in patient survival and quality of life.\u003c/p\u003e\u003cp\u003eCurrently, ICIs have become a research focus in the second-line and subsequent treatments for gastric cancer\u003csup\u003e[\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e–\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]\u003c/sup\u003e. For example, Keynote-059 explored the impact of pembrolizumab in second-line and later treatments for advanced GC patients, where those with CPS\u0026gt;10 achieved better survival expectations than those treated solely with chemotherapy. In the ATTRACTION-2 study, significant survival benefits were observed in patients treated with nivolumab, regardless of PD-L1 expression. Thus, multiple studies have demonstrated the clinical efficacy of nivolumab and pembrolizumab, especially in patients with high PD-L1 expression\u003csup\u003e[\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e–\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]\u003c/sup\u003e. Increasingly, research focuses on combining ICIs with chemotherapy, anti-angiogenic drugs, and other treatment modalities to enhance the immune system's anti-tumor effects and overcome the limitations of single treatment modalities\u003csup\u003e[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e–\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]\u003c/sup\u003e. In this context, exploring more effective treatments with fewer side effects, and identifying patient subgroups more likely to benefit from immunotherapy based on relapse patterns and inflammatory markers, has become a critical issue in the field of gastric cancer treatment.\u003c/p\u003e\u003cp\u003eDespite existing studies showing significant clinical efficacy of ICIs in combination treatments for various cancers, their clinical value in HER2-negative AGC remains under-researched. Therefore, this study aims to explore the effectiveness of ICIs in second-line and subsequent treatments for HER2-negative AGC patients, assess their potential in combination with other drugs, and identify populations more likely to benefit from immunotherapy. Additionally, this study has revealed the predictive value of inflammatory markers (such as NLR, SII) in immunotherapy across lines, identified independent risk factors affecting patient prognosis, and provided a theoretical basis for personalized treatment.\u003c/p\u003e\u003cp\u003eThrough these studies, we not only aim to clarify the clinical value of immunotherapy in the treatment of HER2-negative AGC across treatment lines, but also to explore the optimal strategies for combining immunotherapy with other therapeutic modalities. By using precise biomarker screening, we aim to identify patients who are most likely to benefit from immunotherapy, thereby providing stronger support for clinical practice.\u003c/p\u003e"},{"header":"METHODS AND MATERIALS","content":"\u003cp\u003eThis study is a single-center retrospective analysis that collected clinical data from patients with pathologically confirmed HER2-negative metastatic or advanced gastric and gastroesophageal junction adenocarcinoma treated at Anhui Provincial Hospital between November 2018 and November 2022. These patients had previously received immunotherapy combined with chemotherapy as a first-line standard treatment and experienced disease progression. The objective is to evaluate the efficacy of ICIs in a second-line treatment setting for patients with HER2-negative AGC, particularly in combination with other therapeutic modalities such as chemotherapy and anti-angiogenic drugs.\u003c/p\u003e\u003cp\u003e\u003cb\u003ePatient Eligibility\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eA total of 118 patients meeting the inclusion and exclusion criteria were selected for this study(Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003cp\u003e\u003cb\u003eInclusion criteria\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e1).Patients pathologically or cytologically diagnosed with AGC (AGC) or gastroesophageal junction adenocarcinoma;2).Patients confirmed to have HER2-negative gastric cancer;3).Patients with disease progression or recurrence after first-line therapy failure;4).Patients who have received at least one cycle of an immune checkpoint inhibitor (such as nivolumab or pembrolizumab) as second-line or subsequent therapy;5).ECOG performance status score of 0–2 (indicating the ability to carry out daily activities without significant restrictions);6).At least one measurable lesion according to RECIST 1.1 criteria.\u003c/p\u003e\u003cp\u003e\u003cb\u003eExclusion criteria\u003c/b\u003e:\u003c/p\u003e\u003cp\u003e1).Patients with other malignancies: those with past or concurrent malignancies (except for treated basal cell carcinoma of the skin, squamous cell carcinoma and/or treated in-situ cervical cancer and/or breast cancer), which may affect the assessment of treatment efficacy; 2).Patients positive for HER2 and using targeted drugs such as trastuzumab (Herceptin) or pertuzumab;3). Patients who have received any radiotherapy, chemotherapy, or antitumor treatment within four weeks before the first administration of the study drug;4).Patients participating in clinical trials that have not yet been unblinded.\u003c/p\u003e\u003cp\u003e\u003cb\u003eTreatment Methods\u003c/b\u003e\u003c/p\u003e\u003cp\u003eIn the case I studied, all patients were treated with ICIs as part of the standard treatment regimen during first-line treatment, and at second-line treatment, based on the data collected, the patients were divided into two groups, one group receiving immunotherapy and the other group receiving no immunotherapy. There were 61 patients who stopped immunotherapy during second-line therapy. Most of these patients received chemotherapy or a combination of chemotherapy and anti-angiogenic therapy. Chemotherapy is usually done according to the traditional gastric cancer treatment regimen, such as paclitaxel and platinum drugs, and anti-angiogenic therapy usually uses drugs such as apatinib. These drugs inhibit the blood supply to the tumor, which can slow the progression of the disease. Fifty-seven patients continued to receive immunotherapy during second-line therapy, mainly using ICIs in combination with chemotherapy, some of which included antiangiogenic agents. This treatment strategy combines the suppression of tumor immune evasion by immunotherapy, the cytotoxic effects of chemotherapy, and the vascular suppression effects of anti-angiogenic therapy with multiple mechanisms to improve the impact of therapy and delay the progression of the disease.\u003c/p\u003e\u003cp\u003e\u003cb\u003eFollow-up methods and primary outcomes\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eDuring the patient's treatment, we will monitor the patient's disease development and survival status according to the routine arrangement. The follow-up plan will be carried out according to the standard clinical practice, including imaging studies that can be used for evaluation, such as CT scan or MRI, and also carry out laboratory examinations. This is done to assess how the tumor is responding to treatment and for signs of disease progression. When the disease progresses or the patient dies, we will record the corresponding time, including PFS1, which is the time from the first immunotherapy cycle to the first progression, and PFS2, which is the time from the first immunotherapy cycle to the second progression or death of the patient, and OS, It is the time from the start of the first immunotherapy cycle to the date of death of the patient or the last follow-up of the survivor. The main endpoint of this study is OS. The deadline for follow-up investigation is set at June 1, 2024. For patients who are still alive at the last follow-up, we will confirm their survival status and review relevant data on the day of the last follow-up.\u003c/p\u003e\u003cp\u003e\u003cb\u003eSecondary endpoints\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eWe analyzed the mechanisms of resistance to first-line immunotherapy and the progression patterns following resistance. Resistance patterns were classified into primary resistance and acquired resistance. Primary resistance was defined as patients with PFS ≤ 6 months after first-line treatment, while acquired resistance was defined as patients with PFS \u0026gt; 6 months after first-line treatment. Progression patterns included Mixed progression (MP) and SP. MP was defined as disease progression occurring in only one lesion (including target lesions, non-target lesions, or new lesions) in patients with 1–3 target lesions, or progression occurring in ≤ 2 lesions in patients with \u0026gt; 3 target lesions. SP was defined as progression in \u0026gt; 1 lesion (including target lesions, non-target lesions, or new lesions) in patients with 1–3 target lesions, or progression in \u0026gt; 2 lesions (including target lesions, non-target lesions, or new lesions) in patients with \u0026gt; 3 target lesions.\u003c/p\u003e\u003cp\u003e\u003cb\u003eGroup Definition\u003c/b\u003e\u003c/p\u003e\u003cp\u003eCIBP group: Patients who continued to receive immune checkpoint inhibitor therapy after disease progression following initial immunotherapy. DIBP group: Patients who ceased immunotherapy after disease progression and switched to other treatment modalities such as chemotherapy or anti-angiogenic drugs. This study used OS as the endpoint and determined the optimal cutoff values for continuous variables (such as inflammatory markers) by combining the receiver operating characteristic (ROC) curve with the Youden Index. The cutoff values for the four indicators were as follows:SII ≤ 213vs. \u0026gt;213,NLR ≥ 3 vs. \u0026lt; 3, Platelet-to-Lymphocyte Ratio PLR ≥ 106.46 vs. \u0026lt; 106.46, Lymphocyte-to-Monocyte Ratio (LMR) ≥ 5.87 vs. \u0026lt; 5.87.\u003c/p\u003e\u003cp\u003e\u003cb\u003eResearch Methods and Statistical Analysis\u003c/b\u003e:\u003c/p\u003e\u003cp\u003eThis study employed a retrospective cohort design to evaluate the efficacy and predictive characteristics of immune checkpoint inhibitor (ICI) treatment beyond progression in HER2-negative AGC patients. First, the PFS1, PFS2 and OS were compared between the CIBP group and DIBP group using the Kaplan-Meier method. The differences between groups were assessed using the log-rank test, and the hazard ratios (HR) along with their 95% confidence intervals (CI) were calculated. The results demonstrated a significant survival benefit for patients receiving the continuation of immunotherapy.\u003c/p\u003e\u003cp\u003eIn order to identify the subgroups of patients who would benefit most from immunotherapy, subgroup analysis was conducted according to disease characteristics such as tumor location, pattern of progression, and type of drug resistance. The stratified Cox proportional risk model was used to calculate HR and 95% CI for each subgroup, and forest maps were generated. In this way, the HR and CI of each subgroup of CIBP treatment can be visually represented. Doing these things can help this paper identify subgroups with clear survival benefits.\u003c/p\u003e\u003cp\u003eFinally, to identify meaningful clinical predictive features, Cox proportional hazards regression analysis was performed. Univariate analysis included factors such as gender, age, tumor location, ECOG score, progression pattern, resistance type, SII, NLR, PLR, LMR, and treatment strategy (CIBP vs. DIBP) as variables.Features with a p-value \u0026lt; 0.05 in univariate analysis were further included in the multivariate Cox model, and stepwise regression was applied to select independent prognostic factors. All statistical analyses were considered significant at a p-value of less than 0.05.\u003c/p\u003e"},{"header":"RESULTS","content":"\u003cp\u003e\u003cstrong\u003ePatient Characteristics\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFrom November 2018 to November 2022, a total of 118 patients diagnosed with HER2-negative AGC and treated with immunotherapy were included in the study at Anhui Provincial Hospital. Patients who received more than two cycles of ICIs were categorized into two groups based on their treatment regimens: the DIBP group (N = 61, 51.60%) and the CIBP group (N = 57, 48.30%). All patients experienced disease progression after first-line immunotherapy, with 74 patients (62.70%) presenting with SP. The objective response rate (ORR) of first-line treatment was 57.60%\u0026nbsp;（Table 1).\u003c/p\u003e\n\u003cp\u003eTable 1:\u0026nbsp;Patient baseline demographic and clinical characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eVariables\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eOverall\u003c/strong\u003e \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDIBP GROUP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCIBP GROUP\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ep-value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eN = 118\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eN = 61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003eN = 57\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSEX, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.2132\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eFemale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e31(26.27%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e19(31.15%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e12(21.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eMale\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e87(73.73%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e42(68.85%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e45(78.95%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eAGE, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.9022\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u0026le;60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e49(41.53%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e25(40.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e24(42.11%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e＞60\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e69(58.47%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e36(59.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e33(57.89%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLocation, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.7522\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eCEGJ\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e50(42.37%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e25(40.98%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e25(43.86%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eGC\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e68(57.63%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e36(59.02%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e32(56.14%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eTumor Differentiation, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.5033\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eHigh\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5(4.24%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4(6.56%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e1(1.75%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eModerate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15(12.71%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e7(11.48%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e8(14.04%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003ePoor\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e98(83.05%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e50(81.97%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e48(84.21%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBest response to previous line, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.240\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eCR+PR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e68(57.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e32(52.50%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e36(63.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eSD+PD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e50(42.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e29(47.5%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e21(36.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eECOG, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.206\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e0+1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e76(64.40%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e36(59.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e40(70.205）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e42（35.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e25(41.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e17(29.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLiver metastases, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.678\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e52(44.1%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e28（45.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e24(42.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e66(55.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e33（54.10%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e33（57.90%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLung metastases, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.222\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e16（13.60%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e6(9.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e10(17.50%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e102（86.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e55(90.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e47（82.50%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eProgression pattern, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.776\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eMP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e44(37.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e22(36.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e22(38.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eSP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e74(62.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e39(63.90%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e35(61.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eDrug resistance pattern, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.441\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003ePrimary resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e54(45.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e30(49.20%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e24(42.10%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eAcquired resistance\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e64(54.2%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e31(50.8%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e33(57.9%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNeoadjuvanttherapy, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 60px;\"\u003e\n \u003cp\u003e0.651\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eyes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e109（92.40%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e57（93.40%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e52（91.20%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eno\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e9（7.60%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e4（6.60%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5（8.80%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eT, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.7910\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eT1+2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e47(39.80%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e25(41.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e22(38.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eT3+4\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e71(60.2%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e36(59.0%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e35(61.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eN, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.4880\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eN0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e26(22.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e15(24.60%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e11(19.30%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eN1+2+3\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e92(72.00%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e46(75.40%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e46(80.70%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eM, n(%)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.109\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eM0\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e13（11.00%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 88px;\"\u003e\n \u003cp\u003e4(6.60)%\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e9(15.80%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003eM1\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e105（89.00%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e57（93.40%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e48（84.20%）\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eSII, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e369.84\u0026nbsp;(243.28,583.71)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e352.50 (234.98,695.51)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e397.09 (247.93,566.25)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.8357\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eNLR, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.53 (1.76,3.68)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.51 (1.63-4.06)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.63 (1.94,3.31)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.8865\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003ePLR, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e146.48 (100.34,195.83)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e142.59 (92,75,215.32)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e148.03 (107.06,194.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.5482\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eLMR, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.80 (1.70,3.64)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e2.52 (1.69,3.45)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e3.02 (1.75,4.40)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.1590\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCEA, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.86 (3.02,23.17)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e6.51 (3.01,20.81)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e5.12 (3.09,24.29)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.8504\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eCA199, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e19.34 (4.85,400.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e28.91 (4.85,400.30)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e17.82 (4.91,384.48)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.7164\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eHb, Mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;SD Mean\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003e\u0026plusmn;\u003c/strong\u003e\u003cstrong\u003e\u0026nbsp;SD\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e108.32\u0026nbsp;\u0026plusmn;\u0026nbsp;17.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e106.20\u0026nbsp;\u0026plusmn;\u0026nbsp;15.45\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e110.60\u0026nbsp;\u0026plusmn;\u0026nbsp;18.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.0864\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\" style=\"width: 196px;\"\u003e\n \u003cp\u003e\u003cstrong\u003eBMI, Median (Q1, Q3)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e20.67 (20.38, 20.76)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e20.67 (20.67, 20.94)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 88px;\"\u003e\n \u003cp\u003e20.67 (20.28, 20.67)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 60px;\"\u003e\n \u003cp\u003e0.5864\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eAbbreviations:\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eCR\u003c/strong\u003e:Complete Response;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePR\u003c/strong\u003e:Partial Response;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003eSD\u003c/strong\u003e:Stable Disease;\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003cstrong\u003ePD\u003c/strong\u003e - Progressive Disease.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAnalysis of Progression-Free Survival and Overall Survival\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe Kaplan-Meier survival curve analysis showed that the median progression-free survival (mPFS1), second progression-free survival (mPFS2), and mOS for the entire cohort of 118 patients were 6.8 months (95% CI: 5.82-7.78), 11.8 months (95% CI: 10.59-12.95), and 14.5 months (95% CI: 11.62-17.38), respectively. Based on treatment strategies after progression, the mPFS1 for the CIBP group (n = 57) and the DIBP group (n = 61) were 6.87 months (95% CI: 5.83-7.92) and 6.30 months (95% CI: 4.54-8.06), respectively, with a log-rank P = 0.253. There was no significant difference in PFS1 between the two groups during the first-line treatment, indicating consistent efficacy of the initial immunotherapy across both groups. However, during the second-line and subsequent treatment phases, the mPFS2 for the CIBP group and the DIBP group were 12.9 months (95% CI: 10.4-15.3) and 11.2 months (95% CI: 9.1-13.3), respectively, with a log-rank P = 0.020. The mOS for the CIBP group and the DIBP group were 19.0 months (95% CI: 13.1-25.0) and 13.5 months (95% CI: 12.2-14.9), respectively, with a log-rank P = 0.019. These results suggest that continuing immunotherapy after progression improves survival outcomes (Figure 2).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSubgroup Analysis:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAGC patients were further stratified based on their disease progression type and resistance patterns. Initially, in the SP group, the mPFS2 for the CIBP group was 13.4 months (95% CI: 11.1-15.7 months), significantly higher than the 10.2 months (95% CI: 8.6-11.8 months) for the DIBP group (P = 0.02). Additionally, the mOS for the CIBP group was 21.4 months (95% CI: 17.8-25.0 months), compared to 15.5 months (95% CI: 13.3-17.7 months) for the DIBP group (P = 0.03), indicating that patients in the CIBP group had significantly better outcomes than those in the DIBP group. Immunotherapy beyond progression significantly extended both PFS2 and OS in patients with SP, demonstrating clear therapeutic benefits of continued immunotherapy in improving survival rates.\u003c/p\u003e\n\u003cp\u003eHowever, in the mixed progression group, the difference in PFS2 and OS between the group that continued immunotherapy and the group that stopped immunotherapy was not statistically significant. For example, the median PFS2 in the CIBP group was 11.6 months, which was in the 95% CI range, that is, 9.4-13.8 months. The median PFS2 in the DIBP group was 10.9 months, and its 95% CI range was 8.5-13.3 months, where the P-value was 0.25. Similarly, the median OS of CIBP group and DIBP group is also available. The median OS of CIBP group is 14.2 months, and the 95% CI range is 12.2-16.2 months; the median OS of DIBP group is 13.7 months, and the 95% CI range is 11.5-15.9 months, and the P value here is 0.29. From these results, it can be seen that for patients with mixed progression, immunotherapy beyond progression does not significantly prolong PFS2 or OS.\u003c/p\u003e\n\u003cp\u003eIn this study, patients were divided into acquired resistance group and primary resistance group according to their resistance patterns to immunotherapy, and then the same analytical method was used to evaluate PFS2 and OS in these two groups. Among the acquired resistance groups, the CIBP group was significantly better than the DIBP group. The median PFS2 in the CIBP group was 12.3 months, and its 95% CI range was 10.1-14.5 months, which was significantly higher than the 9.8 months in the DIBP group, and the 95% CI range in the DIBP group was 7.7-11.9 months. The P value here is 0.01. Similarly, the median OS in the CIBP group was 18.8 months, with a 95% CI range of 14.6-23.0 months, while the median OS in the DIBP group was 14.2 months, with a 95% CI range of 12.4-16.0 months, with a P value of 0.04, as can be seen from these results. Immunotherapy beyond the advanced stage can significantly prolong PFS2 and OS in patients with acquired resistance, suggesting that continued immunotherapy may confer additional survival benefits in these patients. Among the primary drug resistance groups, there was no statistically significant difference in PFS2 and OS between the CIBP group and the DIBP group. The median PFS2 in the CIBP group was 8.6 months, and the 95% CI range was 6.4-10.8 months; the DIBP group was 7.9 months, and the 95% CI range was 5.6-10.2 months. The P value here is 0.32. Furthermore, the median OS for the CIBP and DIBP groups was 12.4 months, with a 95% CI range of 10.2-14.6 months, and 11.6 months, with a 95% CI range of 9.3-13.9 months, with a P value of 0.37.\u003c/p\u003e\n\u003cp\u003eIn the different subgroups distinguished by various inflammatory markers, higher SII, PLR, and lower NLR, LMR provided significant survival benefits for patients receiving CIBP. Overall, this study demonstrates significant subgroup differences in the efficacy of immunotherapy beyond progression for AGC patients, particularly in those with SP and acquired resistance, showing clear survival benefits. For patients with mixed progression and primary resistance, the effects of immunotherapy beyond progression were more limited (Figure 3).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCox Proportional Hazards Model Analysis\u003c/strong\u003e\u003cstrong\u003e：\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo further explore independent predictors of survival and to identify which patients are more likely to benefit from immunotherapy beyond progression, this study utilized the Cox proportional hazards model to analyze multiple potential factors. The primary focus was on the independent predictors of OS. Hemoglobin levels,SII,NLR,PLR,LMR among other hematological indices, were derived from the most recent clinical assessments prior to second-line treatment for all patients who progressed after first-line therapy. Initial univariate analysis revealed that the SP, higher SII and NLR were independent risk factors for OS, while acquired resistance and higher hemoglobin levels were independent protective factors for OS. Among them, the progression pattern was significantly correlated with OS, indicating that the characteristics of disease progression play an important role in prognosis. Compared to MP, patients with SP had poorer prognosis and higher HR. Inflammatory markers such as SII and NLR were also associated with OS, indicating that inflammation-related biomarkers play an important role in cancer progression and patient survival.The results of the multivariate analysis further confirmed that the progression pattern (MP/SP, HR = 2.168, 95% CI [1.261-3.727]; p = 0.005), resistance pattern (Primary resistance/Acquired resistance, HR = 0.279, 95% CI [0.163-0.476]; p \u0026lt; 0.001), SII (HR = 3.201, 95% CI [1.348-7.604]; p = 0.008), and NLR (HR = 2.962, 95% CI [1.674-5.241]; p \u0026lt; 0.001) were identified as independent factors influencing OS. There was a significant difference between primary resistance and acquired resistance within the resistance pattern. Additionally, higher values of SII and NLR indicated poorer prognosis for the patients (Table 2).\u003c/p\u003e\n\u003cp\u003eTable 2.\u0026nbsp;Cox Univariate and Multivariate Analysis Table for Different Patient Characteristics\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" width=\"559\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 211px;\"\u003e\n \u003cp\u003eUnivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd colspan=\"3\" style=\"width: 182px;\"\u003e\n \u003cp\u003eMultivariate analysis\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003eHR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e95%CI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003eP\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eSex\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.717\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.442-1.163\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.178\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eAge\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.729\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.466-1.141\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.167\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eLocation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.239\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.786-1.953\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 62px;\"\u003e\n \u003cp\u003e0.357\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eTumor differentiation\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.533\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.837-2.806\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.166\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eBest response to previous line\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.823\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.519-1.304\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.406\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eEcog\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.876\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.514-1.492\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.626\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eLiver metastases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.809\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.513-1.276\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.362\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eLung metastases\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.919\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.458-1.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.813\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eProgression pattern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.057\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.247-3.394\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2.168\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.261-3.727\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0.005\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eDrugresistance pattern\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.256\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.159-0.412\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.163-0.476\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eNeoadjuvanttherapy\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.670\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.244-1.839\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.437\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eT\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.279\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.801-2.042\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.302\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eN\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.563\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.885-2.758\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.124\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eM\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.044\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.520-2.097\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.903\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eSII\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e2.985\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.367-6.521\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e3.201\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.348-7.604\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eNLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e5.084\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e3.065-8.434\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e2.962\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.674-5.241\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003ePLR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.945\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.998-1.002\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eLMR\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.236\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.497-3.072\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.648\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eCEA\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000-1.001\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.528\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eCA199\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e1.000-1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.845\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eHb\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.986\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.974-0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.029\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.976-1.004\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e0.149\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eBMI\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 58px;\"\u003e\n \u003cp\u003e0.954\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.880-1.035\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.260\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd style=\"width: 114px;\"\u003e\n \u003cp\u003eGROUP\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\" style=\"width: 58px;\"\u003e\n \u003cp\u003e0.583\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.370-0.921\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 62px;\"\u003e\n \u003cp\u003e0.021\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 51px;\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 64px;\"\u003e\n \u003cp\u003e0.364\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 90px;\"\u003e\n \u003cp\u003e0.219-0.606\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd style=\"width: 28px;\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"DISCUSSION","content":"\u003cp\u003eIn recent years, ICIs have given new hope to the treatment of gastric cancer by blocking the interaction between programmed death receptor 1 and its ligand, programmed death ligand 1, or by preventing the B7 molecule on antigen-presenting cells from binding to the co-stimulatory receptor CD28 on CD4 + T cells. To activate the patient's own immune system, so that the immune system has the ability to recognize and eliminate tumor cells \u003csup\u003e[15-17]\u003c/sup\u003e. Ajani et al. conducted the CheckMate 649 trial in 2021, which evaluated nabuliumab in combination with chemotherapy as a first-line treatment for patients with advanced gastroesophageal cancer, including esophageal adenocarcinoma, and was a particularly key milestone in gastric cancer immunotherapy. It confirms the therapeutic efficacy of ICIs in patients with tumors that are positive for programmed death ligand 1 \u003csup\u003e[18-19]\u003c/sup\u003e. In addition, Sundar et al. studied the therapeutic effect of first-line ICIs in gastric cancer and esophageal adenocarcinoma patients with low expression of programmed death ligand 1 in 2022, and found that some patients could obtain clinical benefits from treatment, thus providing a basis for therapeutic strategies for this patient group \u003csup\u003e[20]\u003c/sup\u003e. Based on these critical findings, in April 2021, the U.S. Food and Drug Administration approved nabuliumab in combination with chemotherapy for the treatment of advanced or metastatic gastric cancer, gastroesophageal nodular cancer, and esophageal adenocarcinoma, regardless of programmed death ligand 1 expression status \u003csup\u003e[21-22]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eAGC is a rapidly progressing malignant tumor with generally poor prognosis. For HER2-negative AGC patients, traditional chemotherapy agents such as irinotecan and paclitaxel remain commonly used as second-line treatment options\u003csup\u003e[23]\u003c/sup\u003e. However, chemotherapy is often associated with significant adverse reactions and limited long-term efficacy, highlighting the urgent need for effective second-line and subsequent treatments after first-line therapy failure. In recent years, the PD-1 inhibitor nivolumab has demonstrated breakthrough potential in the treatment of AGC\u003csup\u003e\u0026nbsp;[24-25]\u003c/sup\u003e. The pivotal ATTRACTION-2 trial confirmed that nivolumab provides significant survival benefits for Asian patients with AGC who have failed chemotherapy, establishing the foundation for the use of PD-1 inhibitors in second-line and subsequent treatments. Given that immunotherapy may continue to exert therapeutic effects by modulating tumor immune escape mechanisms even after initial disease progression, the strategy of continuing ICIs in second-line treatment after progression on first-line immunotherapy has become a key research focus\u003csup\u003e[26]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eThis study systematically evaluated survival differences between patients receiving different second-line treatment strategies and different patient subgroups. The results showed that CIBP resulted in a significant improvement in survival outcomes. It also highlighted the heterogeneity of CIBP efficacy and identified subgroups of patients who were more likely to benefit from continuous immunotherapy. And to evaluate the outcome of treatment, which is a key direction for future research. In this study, CIBP patients showed significant improvements in both PFS2 and OS compared to DIBP patients, and these findings suggest that survival benefits may be achieved in certain patient populations by continuing immunotherapy after disease progression\u003csup\u003e[27]\u003c/sup\u003e.\u003c/p\u003e\n\u003cp\u003eIn contrast, for patients with MP, continued immunotherapy after disease progression did not significantly prolong their survival, indicating that these patients' response to continuous immunotherapy was relatively low\u003csup\u003e[28-29]\u003c/sup\u003e. Many studies have highlighted the critical role of the tumor immune microenvironment in influencing the pattern of tumor progression and the effect of immunotherapy. The interaction between tumor progression and the immune microenvironment is complex and dynamic. In general, infiltration and activation of cytotoxic T lymphocytes significantly affect tumor growth, metastasis, and response to therapy. In patients with AGC SP, tumors may undergo multiple stages of immune escape and immunosuppression. At this stage, the tumor immune microenvironment may show increased immune activity, which is specifically manifested as increased T cell infiltration, increased PD-1 / PD-L1 pathway activity, and the tumor is in an immune \"hot\" state. Under such an immune environment, ICIs can restore the effector function of T cells. Improve the immune system's ability to recognize and destroy tumor cells\u003csup\u003e[30]\u003c/sup\u003e .\u003c/p\u003e\n\u003cp\u003eIn patients with mixed-progression AGC, the tumor immune microenvironment may lack sufficient immune cell infiltration and effective cytotoxic T lymphocytes (ctl), and the tumor microenvironment may also contain a large number of immunosuppressive cells, such as regulatory T cells Tregs and myelogenic suppressor cells MDSCs. These immunosuppressive cells suppress the immune response, thus limiting the therapeutic effectiveness of ICIs. Tumors characterized by MP exhibit more complex growth patterns. In these tumors, some areas are responsive to immunotherapy, while other areas are resistant to immunotherapy. This intratumoral heterogeneity complicates the effective targeting of immunotherapy, suggesting that the role of SP in gastric cancer may be related to different immune escape mechanisms\u003csup\u003e[31]\u003c/sup\u003e. Instead, it only increased the tumor burde\u003csup\u003e[32-33]\u003c/sup\u003e. The specific mechanism by which tumor immune microenvironment and immune escape mechanism affect immunotherapy is the focus of future research. Our findings highlight the clinical heterogeneity of immunotherapy efficacy in AGC patients with different progression modes.\u003c/p\u003e\n\u003cp\u003eIn previous studies, most patients with gastric cancer showed limited sensitivity to single-drug ICI, after their disease had progressed. Overcoming resistance to ICIs and developing more effective combination therapy has become the core challenge in systemic treatment of gastric cancer. Relevant studies have been mentioned in literature\u003csup\u003e[34-35]\u003c/sup\u003e. In this study, the CIBP regimen significantly improved PFS2 and OS in patients who developed acquired resistance to first-line immunotherapy, and patients in the CIBP group survived longer than those in the DIBP group. These findings suggest that patients with acquired resistance are more likely to benefit from immune rechallenge therapy for survival.\u003c/p\u003e\n\u003cp\u003eDifferent from patients with acquired drug resistance, the survival rate of patients with primary drug resistance has not been significantly improved after receiving immunotherapy. Previous studies have shown that primary drug resistant tumors generally show strong intrinsic resistance to immunotherapy from the very beginning. This reflects its inherent genetic characteristics, high tumor heterogeneity, and immune \"cold\" TME. Immune \"cold\" TME is characterized by a greater number of bone marrow cells and a lack of interferon-gamma (IFN-γ) signaling pathways, factors that impede effective immune activation, possibly due to insufficient tumor antigenicity, or defects in antigen presentation to T cells, and primary drug-resistant tumors that may have an overactive immune checkpoint pathway\u003csup\u003e[36]\u003c/sup\u003e. For example, high PD-L1 expression, which directly inhibits t cell activity. The immunosuppressive microenvironment, characterized by resistance to dense fibrosis, low T-cell infiltration, and high levels of immunosuppressive cytokines, can limit the function of immune effectors, as described in the literature , suggesting that the immune system has not effectively \"trained\" itself to recognize and attack tumors, making a sustained immune response more difficult\u003csup\u003e[37]\u003c/sup\u003e.There is a particular need for comprehensive research to improve immunotherapy outcomes in patients with primary drug resistance.\u003c/p\u003e\n\u003cp\u003eCompared with other conditions, patients with acquired drug resistance generally experience a longer period of immune selection pressure, which was defined as PFS1 \u0026gt;6 months in our study, and their tumor microenvironment may retain some immune reactivity. It's like there's dynamic PD-L1 expression or there's tumor-infiltrated lymphocyte infiltration. Continuous ICI therapy can reverse the T-cell exhaustion by inhibiting LAG-3 / TIM-3, or by increasing antigen presentation, like upregating mhc-1 to reactivate anti-tumor immunity. If combination therapy is to be developed, It should be based on some understanding of the mechanisms by which immune regulation and drug resistance may exist, rather than randomly combining existing treatments. Exploring new immune checkpoint targets, such as LAG-3, VISTA, TIM-3, and TIGIT, and developing treatments for them are promising ways to overcome resistance.\u003c/p\u003e\n\u003cp\u003eIn our study, NLR was identified as an independent risk factor for OS, as was the case for hepatocellular carcinoma and colorectal cancer. These results indicate that markers of systemic inflammation can be used as prognostic indicators for various cancer types, which are also related in reference\u003csup\u003e[38-39]\u003c/sup\u003e. Chronic inflammation will promote tumor growth and metastasis, and cause drug resistance to treatment, which indicates that adjusting the immune microenvironment may be the key to overcoming drug resistance and improving the therapeutic effect of ICI. Future studies should combine liquid biopsy techniques, such as circulating tumor DNA analysis to monitor clonal evolution, with spatial transcriptomics to dynamically characterize the process of tumor microenvironment remodeling.\u003c/p\u003e\n\u003cp\u003eAlthough there are some valuable findings in this study, there are also some shortcomings. Due to the retrospective and single-center design, the sample size is relatively small, which may limit the universality of our findings. Large-scale, multicenter prospective studies are necessary to validate our observations and to determine the best treatment strategy for patients with AGC receiving immunotherapy, as mentioned in references, and although the pattern of progression and type of resistance are identified as key determining factors of treatment effect\u003csup\u003e[40-41]\u003c/sup\u003e . But this study did not explore other possible biomarkers, such as tumor mutation load and microsatellite instability. These factors may give more accurate predictive information, and can also help optimize the selection of patients for immunotherapy. The mechanism of primary drug resistance is not fully understood, and future research should make elucidation of the molecular and immunological basis of primary drug resistance a priority, and promote the development of innovative strategies to overcome drug resistance. Such as using ICI in combination with other immunomodulators, or targeting immunosuppressive cells in the tumor microenvironment.\u003c/p\u003e\n\u003cp\u003eOur study provides new evidence to support the use of ICIs in the treatment of AGC after progression. In particular, continued immunotherapy significantly extended PFS and OS in patients with hyperprogression and acquired resistance. In addition, the results of our study highlight the clinical value of systemic inflammatory markers as prognostic indicators, and emphasize the importance of personalized treatment and patient selection. Conversely, the limited benefit of immunotherapy in patients with mixed progression patterns and primary resistance points to the need to study the mechanisms of resistance and develop new combination treatment strategies. As the field of immunotherapy continues to evolve, future research should focus on perfecting treatment protocols and finding ways to improve clinical outcomes in patients with AGC. And the advantages of immunotherapy after the disease has progressed may also be applied to other malignancies, giving hope to patients who have few treatment options.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments:\u003c/strong\u003eWe appreciate all the authors for their valuable contributions to the completion of this study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e:The authors declare that no funds, grants, or other support were received during the preparation of this manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting Interests\u003c/strong\u003e:The authors have no relevant financial or non-financial interests to disclose.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor Contributions\u003c/strong\u003e:All authors contributed to the study conception and design. Material preparation, data collection and analysis were performed by Zhirun Cai, Haoyu Wang and Shusheng Wu. The first draft of the manuscript was written by Zhirun Cai and all authors commented on previous versions of the manuscript. All authors read and approved the final manuscript. Zhirun Cai,Shusheng Wu and Haoyu Wang contributed equally to this work and should be considered co-first authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e:The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e:This study was performed in line with the principles of the Declaration of Helsinki. Approval was granted by the Ethics Committee of The First Affiliated Hospital of University of Science and Technology of China (2025-XZY-01).The clinical data used in the study were obtained from the routine medical records of the patients, and all patients provided written informed consent upon admission, authorizing the use of their medical data for scientific research. The research data will be used solely for scientific analysis and will not be used for any commercial purposes or other unauthorized objectives.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eYang WJ, Zhao HP, Yu Y, et al. Updates on global epidemiology, risk and prognostic factors of gastric cancer. World J Gastroenterol. 2023;29(16):2452-2468. doi:10.3748/wjg.v29.i16.2452\u003c/li\u003e\n\u003cli\u003eWu SL, Zhang Y, Fu Y, Li J, Wang JS. Gastric cancer incidence, mortality and burden in adolescents and young adults: a time-trend analysis and comparison among China, South Korea, Japan and the USA. \u003cem\u003eBMJ Open\u003c/em\u003e. 2022;12(7):e061038. doi:10.1136/bmjopen-2022-061038\u003c/li\u003e\n\u003cli\u003eYang H, Zhou S, Wang W, et al. The Trends of Gastric Cancer in China From 1990 to 2019 and Predictions to 2040: A Bayesian Age-Period-Cohort Prediction Study. \u003cem\u003eCancer Control\u003c/em\u003e. 2024;31:10732748241293982. doi:10.1177/10732748241293982\u003c/li\u003e\n\u003cli\u003eShiravand Y, Khodadadi F, Kashani SMA, et al. Immune Checkpoint Inhibitors in Cancer Therapy. \u003cem\u003eCurr Oncol\u003c/em\u003e. 2022;29:3044-3060. doi:10.3390/curroncol29050247\u003c/li\u003e\n\u003cli\u003eBagchi S, Yuan R, Engleman EG. Immune Checkpoint Inhibitors for the Treatment of Cancer: Clinical Impact and Mechanisms of Response and Resistance. \u003cem\u003eAnnu Rev Pathol: Mech Dis\u003c/em\u003e. 2021;16(1):223-249. doi:10.1146/annurev-pathol-042020-042741\u003c/li\u003e\n\u003cli\u003eRen J, Wang K, Meng Q, et al. A multicenter retrospective study of the combination of immune checkpoint inhibitors and chemotherapy regimens with or without liver metastasis for the first-line treatment of advanced gastric cancer. \u003cem\u003eTher Adv Med Oncol\u003c/em\u003e. 2024;16:17588359241308389. doi:10.1177/17588359241308389\u003c/li\u003e\n\u003cli\u003eKawamoto Y, Yuki S, Sawada K, et al. Phase II Study of Ramucirumab Plus Irinotecan Combination Therapy as Second-Line Treatment in Patients with Advanced Gastric Cancer: HGCSG1603. \u003cem\u003eOncologist\u003c/em\u003e. 2022;27(8):e642-e649. doi:10.1093/oncolo/oyac086\u003c/li\u003e\n\u003cli\u003eSato Y, Yamashita H, Yagi K, Nomura S, Seto Y. Ramucirumab Beyond Disease Progression After Paclitaxel Plus Ramucirumab in Gastric Cancer: A Phase II Trial. \u003cem\u003eAnticancer Res\u003c/em\u003e. 2024;44(7):3125-3131. doi:10.21873/anticanres.17126\u003c/li\u003e\n\u003cli\u003eNie C, Xu W, Lv H, et al. Tailoring second-line or above therapy for patients with advanced or metastatic gastric cancer: A multicenter real-world study. \u003cem\u003eFront Pharmacol\u003c/em\u003e. 2022;13:1043217. doi:10.3389/fphar.2022.1043217\u003c/li\u003e\n\u003cli\u003eDenlinger CS, Matkowskyj KA, Mulcahy MF. Gastric and Esophageal Cancers: Guidelines Updates. \u003cem\u003eJ Natl Compr Canc Netw\u003c/em\u003e. 2021;19(5.5):639-643. doi:10.6004/jnccn.2021.5006\u003c/li\u003e\n\u003cli\u003eLin SY, Yang CY, Liao BC, et al. Tumor PD-L1 Expression and Clinical Outcomes in Advanced-stage Non-Small Cell Lung Cancer Patients Treated with Nivolumab or Pembrolizumab: Real-World Data in Taiwan. \u003cem\u003eJ Cancer\u003c/em\u003e. 2018;9(10):1813-1820. doi:10.7150/jca.24985\u003c/li\u003e\n\u003cli\u003eXiong L, Cai Y, Zhou X, et al. Optimum Immunotherapy Method According to PD-L1 Expression in Advanced Lung Cancer: A Network Metac-Analysis. \u003cem\u003eFuture Oncol\u003c/em\u003e. 2022;18(7):883-896. doi:10.2217/fon-2021-1217\u003c/li\u003e\n\u003cli\u003eLee WS, Yang H, Chon HJ, Kim C. Combination of anti-angiogenic therapy and immune checkpoint blockade normalizes vascular-immune crosstalk to potentiate cancer immunity. \u003cem\u003eExp Mol Med\u003c/em\u003e. 2020;52(9):1475-1485. doi:10.1038/s12276-020-00500-y\u003c/li\u003e\n\u003cli\u003eSong Y, Fu Y, Xie Q, Zhu B, Wang J, Zhang B. Anti-angiogenic Agents in Combination With Immune Checkpoint Inhibitors: A Promising Strategy for Cancer Treatment. Front Immunol. 2020;11:1956. doi:10.3389/fimmu.2020.01956\u003c/li\u003e\n\u003cli\u003eLao Y, Shen D, Zhang W, He R, Jiang M. Immune Checkpoint Inhibitors in Cancer Therapy\u0026mdash;How to Overcome Drug Resistance? \u003cem\u003eCancers\u003c/em\u003e. 2022;14(15):3575. doi:10.3390/cancers14153575\u003c/li\u003e\n\u003cli\u003eQiu J, Cheng Z, Jiang Z, Gan L, Zhang Z, Xie Z. Immunomodulatory Precision: A Narrative Review Exploring the Critical Role of Immune Checkpoint Inhibitors in Cancer Treatment. \u003cem\u003eInt J Mol Sci\u003c/em\u003e. 2024;25(10):5490. doi:10.3390/ijms25105490\u003c/li\u003e\n\u003cli\u003eNagasaki J, Ishino T, Togashi Y. Mechanisms of resistance to immune checkpoint inhibitors. \u003cem\u003eCancer Sci\u003c/em\u003e. 2022;113(10):3303-3312. doi:10.1111/cas.15497\u003c/li\u003e\n\u003cli\u003eJanjigian YY, Ajani JA, Moehler M, et al. LBA7 Nivolumab (NIVO) plus chemotherapy (Chemo) or ipilimumab (IPI) vs chemo as first-line (1L) treatment for advanced gastric cancer/gastroesophageal junction cancer/esophageal adenocarcinoma (GC/GEJC/EAC): CheckMate 649 study. Ann Oncol. 2021;32:S1329-S1330. doi:10.1016/j.annonc.2021.08.2131\u003c/li\u003e\n\u003cli\u003eNoori M, Fayyaz F, Zali MR, Bashash D. Predictive value of PD-L1 expression in response to immune checkpoint inhibitors for gastric cancer treatment: a systematic review and meta-analysis. Expert Rev Anticancer Ther. 2023;23(9):1029-1039. doi:10.1080/14737140.2023.2238896\u003c/li\u003e\n\u003cli\u003eZhao JJ, Yap DWT, Chan YH, et al. Low Programmed Death-Ligand 1\u0026ndash;Expressing Subgroup Outcomes of First-Line Immune Checkpoint Inhibitors in Gastric or Esophageal Adenocarcinoma. J Clin Oncol. 2022;40(4):392-402. doi:10.1200/JCO.21.01862 \u003c/li\u003e\n\u003cli\u003eSugarman R, Betts KA, Nie X, Hartman J, Nguyen H. Nivolumab Plus Chemotherapy for Advanced Gastric, Gastroesophageal Junction, and Esophageal Adenocarcinoma: Analysis of Number Needed To Treat and Number Needed To Harm. Clin Ther. 2023;45(11):1155-1158. doi:10.1016/j.clinthera.2023.08.014\u003c/li\u003e\n\u003cli\u003eJanjigian YY, Shitara K, Moehler M, et al. First-line nivolumab plus chemotherapy versus chemotherapy alone for advanced gastric, gastro-oesophageal junction, and oesophageal adenocarcinoma (CheckMate 649): a randomised, open-label, phase 3 trial. Lancet. 2021;398(10294):27-40. doi:10.1016/S0140-6736(21)00797-2\u003c/li\u003e\n\u003cli\u003eIshiguro A, Kawamoto Y, Yuki S, et al. HGCSG 1603: Phase II study of ramucirumab and irinotecan combination therapy as second-line treatment in patients with metastatic or advanced gastric cancer. J Clin Oncol. 2019;37(4_suppl):TPS183-TPS183. doi:10.1200/JCO.2019.37.4_suppl.TPS183\u003c/li\u003e\n\u003cli\u003eTakei S, Kawazoe A, Shitara K. The New Era of Immunotherapy in Gastric Cancer. Cancers. 2022;14(4):1054. doi:10.3390/cancers14041054\u003c/li\u003e\n\u003cli\u003eKono K, Nakajima S, Mimura K. Current status of immune checkpoint inhibitors for gastric cancer. Gastric Cancer. 2020;23(4):565-578. doi:10.1007/s10120-020-01090-4\u003c/li\u003e\n\u003cli\u003eLefebvre C, Martin E, Hendriks LEL, et al. Immune checkpoint inhibitors versus second line chemotherapy for patients with lung cancer refractory to first line chemotherapy. Respir Med Res. 2020;78:100788. doi:10.1016/j.resmer.2020.100788\u003c/li\u003e\n\u003cli\u003eRouhani SJ, Bestvina CM. Immunotherapy partners after progression: Right place, right time? Cancer. 2023;129(2):181-183. doi:10.1002/cncr.34558\u003c/li\u003e\n\u003cli\u003eLv J, Yan W, Zhang R, et al. Progressive Disease with Mixed Response After Immunotherapy in Non-Small Cell Lung Cancer. J Inflammation Res. 2024;Volume 17:6317-6327. doi:10.2147/JIR.S477244\u003c/li\u003e\n\u003cli\u003eGe X, Zhang Z, Zhang S, et al. Immunotherapy beyond progression in patients with advanced non-small cell lung cancer. \u003cem\u003eTransl Lung Cancer Res\u003c/em\u003e. 2020;9(6):2391-2400. doi:10.21037/tlcr-20-1252\u003c/li\u003e\n\u003cli\u003eBinnewies M, Roberts EW, Kersten K, et al. Understanding the tumor immune microenvironment (TIME) for effective therapy. Nat Med. 2018;24(5):541-550. doi:10.1038/s41591-018-0014-x\u003c/li\u003e\n\u003cli\u003eVitale I, Shema E, Loi S, Galluzzi L. Intratumoral heterogeneity in cancer progression and response to immunotherapy. Nat Med. 2021;27(2):212-224. doi:10.1038/s41591-021-01233-9 \u003c/li\u003e\n\u003cli\u003eLi B, Liang L, Chen Y, et al. Circ_0008287 promotes immune escape of gastric cancer cells through impairing microRNA-548c-3p-dependent inhibition of CLIC1. Int Immunopharmacol. 2022;111:108918. doi:10.1016/j.intimp.2022.108918\u003c/li\u003e\n\u003cli\u003eMa ES, Wang ZX, Zhu MQ, Zhao J. Immune evasion mechanisms and therapeutic strategies in gastric cancer. World J Gastrointest Oncol. 2022;14(1):216-229. doi:10.4251/wjgo.v14.i1.216\u003c/li\u003e\n\u003cli\u003eBaxter MA, Middleton F, Cagney HP, Petty RD. Resistance to immune checkpoint inhibitors in advanced gastro-oesophageal cancers. Br J Cancer. 2021;125(8):1068-1079. doi:10.1038/s41416-021-01425-7\u003c/li\u003e\n\u003cli\u003eHe P, Ma L, Xu B, et al. Research progress and future directions of immune checkpoint inhibitor combination therapy in advanced gastric cancer. Ther Adv Med Oncol. 2024;16:17588359241266156. doi:10.1177/17588359241266156\u003c/li\u003e\n\u003cli\u003eJhunjhunwala S, Hammer C, Delamarre L. Antigen presentation in cancer: insights into tumour immunogenicity and immune evasion. Nat Rev Cancer. 2021;21(5):298-312. doi:10.1038/s41568-021-00339-z\u003c/li\u003e\n\u003cli\u003eHaist M, Stege H, Grabbe S, Bros M. The Functional Crosstalk between Myeloid-Derived Suppressor Cells and Regulatory T Cells within the Immunosuppressive Tumor Microenvironment. Cancers. 2021;13(2):210. doi:10.3390/cancers13020210\u003c/li\u003e\n\u003cli\u003eDolan RD, Laird BJA, Horgan PG, McMillan DC. The prognostic value of the systemic inflammatory response in randomised clinical trials in cancer: A systematic review. Crit Rev Oncol Hematol. 2018;132:130-137. doi:10.1016/j.critrevonc.2018.09.016\u003c/li\u003e\n\u003cli\u003eKim MR, Kim AS, Choi HI, Jung JH, Park JY, Ko HJ. Inflammatory markers for predicting overall survival in gastric cancer patients: A systematic review and meta-analysis. Coelho-Filho OR, ed. PLOS One. 2020;15(7):e0236445. doi:10.1371/journal.pone.0236445\u003c/li\u003e\n\u003cli\u003eCoutzac C, Pernot S, Chaput N, Zaanan A. Immunotherapy in advanced gastric cancer, is it the future? \u003cem\u003eCrit Rev Oncol Hematol\u003c/em\u003e. 2019;133:25-32. doi:10.1016/j.critrevonc.2018.10.007\u003c/li\u003e\n\u003cli\u003eZhao Y, Bai Y, Shen M, Li Y. Therapeutic strategies for gastric cancer targeting immune cells: Future directions. Front Immunol. 2022;13:992762. doi:10.3389/fimmu.2022.992762 \u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Advanced Gastric Cancer, immunotherapy, treatment beyond progression, Progression pattern, Drugresistancepattern, inflammatory biomarkers","lastPublishedDoi":"10.21203/rs.3.rs-7059672/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7059672/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003ePurpose: \u003c/strong\u003eAdvanced gastric cancer (AGC) has a poor prognosis, and optimal management post-progression on immune checkpoint inhibitors (ICIs) remains undefined. This study evaluates survival outcomes of continuing ICIs beyond progression in HER2-negative AGC, focusing on progression patterns and biomarker correlates.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA retrospective cohort of HER2-negative AGC patients treated with ICIs at Anhui Provincial Hospital (2018–2022) was analyzed. Eligible patients (n=118) had ≥3 months of stable disease before progression. Primary endpoints included progression-free survival (PFS1, PFS2) and overall survival (OS). Kaplan-Meier analysis, Cox regression, and biomarker assessments (neutrophil-to-lymphocyte ratio [NLR], Systemic Immune-Inflammation Index [SII]) were performed.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults: \u003c/strong\u003eMedian PFS1 was 6.8 months. Patients continuing ICIs post-progression (CIBP group) demonstrated significantly improved PFS2 (12.9 vs. 11.2 months, p=0.020) and OS (19.0 vs. 13.5 months, p=0.019) compared to discontinuers (DIBP). Systemic progression (SP) was predominant; patients with acquired resistance (ICI exposure \u0026gt;6 months) and systemic progression derived the greatest benefit from CIBP. Elevated NLR/SII predicted reduced post-progression efficacy.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion: \u003c/strong\u003eContinuing ICIs post-progression improves survival in HER2-negative AGC, particularly for SP with acquired resistance. Progression patterns and NLR/SII may guide clinical decisions. Prospective trials integrating dynamic biomarker monitoring are warranted to validate rechallenge strategies.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eretrospectively registered：\u003c/strong\u003eIRB approval number:2025-XZY-01\u003c/p\u003e","manuscriptTitle":"Post-Progression Immunotherapy and Prognostic Factors in HER2-Negative Advanced Gastric Cancer: A Retrospective Analysis of 118 Cases","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-09 05:58:39","doi":"10.21203/rs.3.rs-7059672/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"44f4d1c3-8765-4011-9e57-fff0a2d8c099","owner":[],"postedDate":"July 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-14T09:09:06+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-09 05:58:39","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7059672","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7059672","identity":"rs-7059672","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}