ArticleRisk management and healthcare policy2023
Prognostic Model of D2 Radical Gastrectomy Combined with Neoadjuvant Chemotherapy for Gastric Cancer.
Article in Risk management and healthcare policy, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers, 1 of them a synthesis that pooled it.
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Who cites it
7 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Correlation between neutrophil-to-lymphocyte ratio and platelet-to-lymphocyte ratio with prognosis in gastric cancer patients undergoing neoadjuvant chemotherapy: a meta-analysis.BMC gastroenterology · 2025Pooled it
- Diagnostic value of peripheral blood inflammatory indices for clinicopathological profile of colorectal cancer: a retrospective observational study.BMC gastroenterology · 2025Observational
- Development of a Prognostic Nomogram for Overall Survival in Gastric Cancer Patients Who Underwent Adjuvant Chemoradiotherapy.Journal of gastrointestinal cancer · 2025Article
- Analysis of the efficacy and safety of extended lymph node dissection in gastric cancer surgery: association with dissection quantity, inflammatory response, and complications.American journal of translational research · 2025Article
- Comparison of efficacy and safety of nab-paclitaxel and oxaliplatin + S-1 and standard S-1 and oxaliplatin chemotherapy regimens for treatment of gastric cancer.World journal of gastrointestinal surgery · 2024Article
- Predictive Significance of Systemic Immune-Inflammation Index in Patients with Breast Cancer: A Retrospective Cohort Study.OncoTargets and therapy · 2023Article
- Developing a Prognostic Model for Intrahepatic Cholangiocarcinoma Patients With Elevated Preoperative Carbohydrate Antigen 19-9 Levels: Volume-Adjusted CA19-9 (VACA) as a Novel Biomarker.Cancer control : journal of the Moffitt Cancer CenterArticle
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7 authors.
Funding
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Abstract
Purpose: The AJCC (the American Joint Committee on Cancer) ypTNM (post-neoadjuvant pathologic stage group) staging was established based on patients with lymphadenectomy scope less than D2 and did not include ypT0N0 patients with pathologically complete response (PCR). The purpose of this study was to construct a survival predictive model for gastric cancer patients after neoadjuvant chemotherapy and gastrectomy combined with D2 lymphadenectomy. Patients and Methods: The multicenter data of 838 gastric cancer patients who received neoadjuvant chemotherapy and gastrectomy combined with D2 lymphadenectomy were analyzed retrospectively. These dual center patients were divided into training (n = 671, the Affiliated Hospital of Qingdao University) and validation (n = 167, Qingdao West Coast New Area Central Hospital) cohorts. Based on training cohort, univariate and multivariable COX regression analyses were performed to select the clinicopathological characteristics significantly correlating with overall survival and construct a nomogram. Based on training and validation cohorts, the distinguishing and calibrating capabilities of nomogram was evaluated by the receiver operating characteristic (ROC) curve, Harrell's concordance index (C-index), decision curve analysis (DCA) curve and calibration curve. Results: Platelet-to-lymphocyte ratio (PLR), pathologic stage after neoadjuvant treatment: ypT and ypN stage, tumor regression grade (TRG) became independent variables intimately related to the prognosis and was used to construct nomograms of 3/5-year prognosis. The nomograms showed an accuracy in predicting OS (overall survival) rate, with area under the ROC curve (AUC) of 0.818 (95% CI = 0.753~0.883) and C-index of 0.801 (95% CI = 0.744~0.858) in validation cohort. Calibration curves showed satisfactory agreement between nomogram prediction and actual result, and DCA curves indicated the large positive net benefit and excellent clinical usefulness of nomogram. Conclusion: This study successfully developed a nomogram to predict overall survival of gastric cancer patients after neoadjuvant chemotherapy and gastrectomy combined with D2 lymphadenectomy, which might have excellent predictive performance and clinical application value.
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