International Journal of Biological Sciences · 2020 · 12 citations · 22 references
MedicineOncologySurgeryGastrointestinal OncologyMetastasisSurvival AnalysisCancer Survival AnalysisGastric CancerPrognostic AssessmentSurvival ModelingSurvival OutcomesSurvival PredictionCalibration Curve AnalysisCancer Prognostic ModelingIndependent Cohort ValidationLymph Node Metastasis PrognosisPredictive NomogramsPrognostic Factors AnalysisSurvival Endpoints ValidationTnm Staging System
Gastric cancer (GC) with lymph node metastasis (LNM) at diagnosis is associated with a unstable prognosis and indefinite survival times. The aim of the present study was to construct and validate a model for the Overall survival (OS) estimation for patients with LNM. The nomogram was constructed to predict the OS for LNM-positive GC using the primary group of 836 patients and validated using an independent cohort of 411 patients. Factors in the nomogram were identified by multivariate Cox hazard analysis. The predictive capability of nomogram was evaluated by calibration analysis and decision curve analysis. Multivariate analysis suggested that eight pre-treatment characteristics were used for developing the nomogram. In the primary cohort, the C-index for OS prediction was 0.788 (95% CI: 0.753-0.823), while in validation cohort, the C-index for OS prediction was 0.769 (95% CI: 0. 720-0.818). The calibration plot for the probability of OS and decision curve analyses showed an optimal agreement. Based on the nomogram, we could divided patients into three groups: low-risk group, middle-risk group and a high-risk group(p <0.001).Taken together, we have provided an easy-to-used and accurate tool for predicting OS, furthermore could be used for risk stratification of OS of LNM-positive GC patients.
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Cancer statistics in China, 2015
Wanqing Chen, Rongshou Zheng, Peter D. Baade et al. · CA A Cancer Journal for Clinicians · 2016 · 18K citations · Full text
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Medicine, Cancer Biology, Oncology +17
Robert L. Camp, Marisa Dolled‐Filhart, David L. Rimm · Clinical Cancer Research · 2004 · 3.9K citations
Medicine, Biostatistics, Oncology +17