Analysis of Prognostic Factors and Design of Prognosis Model for Patients with Stage IV Gastric Cancer Following First-Line Palliative Chemotherapy

Zhou, Qiyin; Lan, Xi; Li, Ni; Yuan, Daozu; Zhang, Jiliang

doi:10.2147/cmar.s263320

Cited by 10 publications

(7 citation statements)

References 32 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In this study, we found that pretreatment serum CEA levels and tumor metastasis status were two major predictors of anti-PD-1 treatment outcomes. Serum CEA has been the most common tumor marker of gastrointestinal tumors, and an elevated level of serum CEA indicates the presence of tumor progression and relapse [ 22 , 23 ]. A change in the CEA level after treatment is an indicator of treatment response, although the accuracy and clinical relevance are low [ 23 , 24 ].…”

Section: Discussionmentioning

confidence: 99%

“…Serum CEA has been the most common tumor marker of gastrointestinal tumors, and an elevated level of serum CEA indicates the presence of tumor progression and relapse [ 22 , 23 ]. A change in the CEA level after treatment is an indicator of treatment response, although the accuracy and clinical relevance are low [ 23 , 24 ]. Consistent with previous reports, we demonstrated that patients with elevated CEA levels were more likely to benefit from anti-PD-1 treatment than those with normal CEA levels before treatment.…”

Section: Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A radiomics model predicts the response of patients with advanced gastric cancer to PD-1 inhibitor treatment

Liang

Huang

Wang

et al. 2022

Aging

View full text Add to dashboard Cite

Programmed cell death 1 (PD1) inhibitors have shown promising treatment effects in advanced gastric cancer, the beneficiary population not definite. This study aimed to construct an individualized radiomics model to predict the treatment benefits of PD-1 inhibitors in gastric cancer. Patients with advanced gastric cancer treated with PD-1 inhibitors were randomly divided into a training set (n = 58) and a validation set (n = 29). CT imaging data were extracted from medical records, and an individual radiomics nomogram was generated based on the imaging features and clinicopathological risk factors. Discrimination performance was evaluated by Harrell’s c-index and receiver operator characteristic (ROC) curve analyses. The areas under the ROC curves (AUCs) were analyzed to predict anti-PD-1 efficacy and survival. We found that the radiomics nomogram could predict the response of gastric cancer to anti-PD-1 treatment. The AUC was 0.865 with a 95% CI of 0.812-0.828 in the training set, while the AUC was 0.778 with a 95% CI of 0.732–0.776 in the validation set. The diagnostic performance of the radiomics was significantly higher than that of the clinical factors ( p < 0.01). Patients with a low risk of disease progression discriminated by the radiomics nomogram had longer progression-free survival than those with a high risk (6.5 vs. 3.2 months, HR 1.99, 95% CI: 1.19-3.31, p = 0.009). The radiomics nomogram based on CT imaging features and clinical risk factors could predict the treatment benefits of PD-1 inhibitors in advanced gastric cancer, enabling it to guide decision-making regarding clinical treatment.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A radiomics model predicts the response of patients with advanced gastric cancer to PD-1 inhibitor treatment

Liang

Huang

Wang

et al. 2022

Aging

View full text Add to dashboard Cite

show abstract

“…Gastric cancer (GC) is considered as the third leading cause of tumor-associated death worldwide, remaining a global health problem [ 1 , 2 ]. Despite advances in comprehensive therapies, including surgery, adjuvant chemotherapy and radiation interventions, the prognosis of GC patients remains poor primarily ascribed to uncontrolled metastasis [ 3 , 4 ]. Therefore, having a better understanding the molecular mechanisms associated with GC pathogenesis will be of great importance to improve the clinical outcomes of GC patients.…”

Section: Introductionmentioning

confidence: 99%

Targeting kinesin family member 21B by miR-132-3p represses cell proliferation, migration and invasion in gastric cancer

et al. 2022

View full text Add to dashboard Cite

Recently, kinesin family member 21B (KIF21B) has been reported to be an oncogene in non-small cell lung cancer and hepatocellular carcinoma. However, the functional role of KIF21B and related molecular mechanisms in gastric cancer (GC) remain largely uncovered. In this study, online bioinformatics analysis showed that KIF21B was overexpression in GC and predicted poor prognosis. Consistently, we found that the protein expression of KIF21B was upregulated in GC tissues compared with adjacent tissues by immunohistochemistry. Knockdown of KIF21B significantly suppressed cell proliferation, migration and invasion in GC cell lines (AGS and SNU-5) using Cell counting kit‑8 (CCK-8) assay, colony formation and transwell assay. KIF21B was confirmed as the target of miR-132-3p in GC cells by luciferase reporter assay. Moreover, miR-132-3p was down-regulated and KIF21B expression was upregulated in GC tissues. Overexpression of KIF21B reversed the miR-132-3p-mediated suppressive effects on GC cell proliferation, migration and invasion. Furthermore, miR-132-3p overexpression downregulated the protein levels of Wnt1, c-Myc, β-catenin, proliferating cell nuclear antigen (PCNA) and N-cadherin, and upregulated E-cadherin expression in GC cells, which were all alleviated after KIF21B overexpression. In conclusion, our findings indicate that down-regulation of KIF21B by miR-132-3p suppresses cellular functions in GC, which might be linked to reduced Wnt/β-catenin signaling.

show abstract

“…More than one-third of all GC patients have distant metastasis (stage IV) at diagnosis. The survival time of these patients is short, rarely more than one year, and the treatment options are limited, including palliative chemotherapy, immunotherapy, and targeted therapy [2][3][4] .…”

Section: Introductionmentioning

confidence: 99%

Identifying Benefit Factors Associated With Primary Tumor Resection in Patients With Stage IV Gastric Cancer: a Propensity Score-matched Analysis

Yan

Liu

2021

Preprint

View full text Add to dashboard Cite

Background: At present, the beneficial factors related to surgery at the primary tumor site in patients with stage IV gastric cancer (GC) are unclear. We developed a new selection process to determine the beneficial factors associated with primary tumor surgery.Methods: Patients with stage IV GC were screened from the Surveillance, Epidemiology, and End Results (SEER) database and were divided into surgery and non-surgery groups. The Kaplan-Meier method was used to estimate the survival curve before and after the propensity score-matched analysis (PSM). We believe that patients in the surgery group who have a longer median cancer-specific survival (CSS) time than those in the non-surgery group can benefit from surgery. Use Multivariate Logistic regression analysis to determine the benefit factors related to surgery.Results: A total of 7259 patients with stage IV GC were included, of which 29.95% (2174) underwent primary tumor surgery. After PSM, the median CSS of the surgery group and the non-surgery group was 12 months and 7 months, respectively (p < 0.001). Multivariate COX regression analysis showed that age, T stage, primary tumor site, histological classification, histological grade, and chemotherapy were independently correlated with CSS. We included the independent related factors affecting CSS in COX analysis in the multivariate Logistics regression model. The results showed that T stage, histological grade, and chemotherapy were related to surgical benefit.Conclusion: The surgery to the primary tumor site can prolong the survival time of patients with stage IV GC, and surgeons should screen patients before surgery. Our results show that patients with T stage T4b and histological grade GIII/GIV do not benefit from surgery, while patients receiving chemotherapy can benefit from surgery.

show abstract

Analysis of Prognostic Factors and Design of Prognosis Model for Patients with Stage IV Gastric Cancer Following First-Line Palliative Chemotherapy

Cited by 10 publications

References 32 publications

A radiomics model predicts the response of patients with advanced gastric cancer to PD-1 inhibitor treatment

A radiomics model predicts the response of patients with advanced gastric cancer to PD-1 inhibitor treatment

Targeting kinesin family member 21B by miR-132-3p represses cell proliferation, migration and invasion in gastric cancer

Identifying Benefit Factors Associated With Primary Tumor Resection in Patients With Stage IV Gastric Cancer: a Propensity Score-matched Analysis

Contact Info

Product

Resources

About