A novel nomogram integrated with PDL1 and CEA to predict the prognosis of patients with gastric cancer

Di, Tian; Lai, Yuerong; Luo, Qiuyun; Chen, Zhigang; Du, Yong; Lin, Run-Duan; Zhang, Lin; Sun, Jian

doi:10.1007/s12094-023-03132-6

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…The values of AUC at 1, 3, and 5 years were 0.62, 0.69, and 0.68, respectively. Additionally, Di et al [ 23 ] developed a novel nomogram integrated with PDL1 and CEA to predict the prognosis of patients with gastric cancer, and the C-index was 0.763 (95% CI 0.740–0.787). To our knowledge, our model parameters are superior to most of the prognostic models for gastric cancer, and we have identified specific metabolic features that play a crucial role in the prognosis of gastric cancer.…”

Section: Discussionmentioning

confidence: 99%

Prognostic Implication of Plasma Metabolites in Gastric Cancer

Cao

Lyu

Chen

et al. 2023

IJMS

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Gastric cancer (GC) typically carries a poor prognosis as it is often diagnosed at a late stage. Altered metabolism has been found to impact cancer outcomes and affect patients’ quality of life, and the role of metabolites in gastric cancer prognosis has not been sufficiently understood. We aimed to establish a prognostic prediction model for GC patients based on a metabolism-associated signature and identify the unique role of metabolites in the prognosis of GC. Thus, we conducted untargeted metabolomics to detect the plasma metabolites of 218 patients with gastric adenocarcinoma and explored the metabolites related to the survival of patients with gastric cancer. Firstly, we divided patients into two groups based on the cutoff value of the abundance of each of the 60 metabolites and compared the differences using Kaplan–Meier (K-M) survival analysis. As a result, 23 metabolites associated with gastric cancer survival were identified. To establish a risk score model, we performed LASSO regression and Cox regression analysis on the 60 metabolites and identified 8 metabolites as an independent prognostic factor. Furthermore, a nomogram incorporating clinical parameters and the metabolic signature was constructed to help individualize outcome predictions. The results of the ROC curve and nomogram plot showed good predictive performance of metabolic risk features. Finally, we performed pathway analysis on the 24 metabolites identified in the two parts, and the results indicated that purine metabolism and arachidonic acid metabolism play important roles in gastric cancer prognosis. Our study highlights the important role of metabolites in the progression of gastric cancer and newly identified metabolites could be potential biomarkers or therapeutic targets for gastric cancer patients.

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Section: Discussionmentioning

confidence: 99%

Prognostic Implication of Plasma Metabolites in Gastric Cancer

Cao

Lyu

Chen

et al. 2023

IJMS

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“…[ 22 , 23 ] Although CEA levels have limited value as an independent prognostic factor, some research has shown that the combinations of CEA levels and other indicators can increase their prognostic sensitivity. [ 24 , 25 ]…”

Section: Introductionmentioning

confidence: 99%

Pretreatment controlling nutritional status (CONUT) score and carcinoembryonic antigen level provide tumor progression and prognostic information in gastric cancer: A retrospective study

Chen,

Huang

et al. 2023

Medicine

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This study explores the role of combining the controlling nutritional status (CONUT) score and the carcinoembryonic antigen (CEA) level on predicting tumor stage and prognosis in gastric cancer (GC) patients. A total of 682 GC patients were included in this retrospective study. CONUT scores and CEA levels were combined to establish a new scoring system: CONUT-CEA score. cutoff values for distinguishing patients between stage IV and non-stage IV were established by receiver operating characteristic curves. cutoff values for predicting prognosis were determined by maximum χ2 method. The CONUT and CEA cutoff values for discriminating stage IV patients from non-stage IV patients were 2.0 and 5.58 ng/mL, respectively. Logistic regression model demonstrated that high CONUT-CEA score was related to advanced tumor stage. Among non-stage IV patients, CONUT and CEA cutoff values of 2.0 and 9.50 ng/mL predicted overall survival (OS), respectively. The Cox proportional risk model revealed that high CONUT-CEA score was notable related to decreased OS (2 vs 0: hazard ratios (HR) = 2.358, 95% confidence intervals (CI) = 1.412–3.940, P = .001) and decreased disease-free survival (2 vs 0: HR = 1.980, 95% CI = 1.072–3.656, P = .003). The CONUT-CEA score may be a good biomarker for predicting tumor stage and prognosis in GC patients.

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A novel nomogram integrated with PDL1 and CEA to predict the prognosis of patients with gastric cancer

Cited by 2 publications

References 19 publications

Prognostic Implication of Plasma Metabolites in Gastric Cancer

Prognostic Implication of Plasma Metabolites in Gastric Cancer

Pretreatment controlling nutritional status (CONUT) score and carcinoembryonic antigen level provide tumor progression and prognostic information in gastric cancer: A retrospective study

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