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Novel microvascular invasion-based prognostic nomograms to predict survival outcomes in patients after R0 resection for hepatocellular carcinoma.
Journal of Cancer Research and Clinical Oncology 2017 Februrary
PURPOSE: To propose a novel histopathological classification system for microvascular invasion (MVI) and to establish nomograms to predict postoperative survival and early tumor recurrence in patients with hepatocellular carcinoma (HCC) after R0 liver resection.
METHODS: The clinicopathological and follow-up data of 686 consecutive patients with HCC who underwent R0 liver resection in our hospital between December 2009 and April 2010 were retrospectively reviewed. A classification system was established based on histological characteristics of MVI. Nomograms were then formulated using a multivariate Cox proportional hazards model to analyze. The results were validated using bootstrap resampling and a new 225-patient validation cohort operated in May and June 2010 at the same institution.
RESULTS: A 4-stratification classification system of MVI was established, which satisfactorily determined the risk of survival and early tumor recurrence. Then, an eight-factor nomogram for survival prediction and a seven-factor nomogram for prediction of early tumor recurrence were established. The concordance indices were 0.78 for the survival-prediction nomogram and 0.72 for the recurrence-prediction nomogram. These indices were both significantly higher than the following three commonly used staging systems: tumor-node-metastasis staging system (seventh edition, 0.67/0.65), Japan Integrated Staging System (0.58/0.58) and Chinese University Prognostic Index (0.52/0.51). The calibration curves showed good agreement between predictions by the nomograms and actual survival outcomes. These results were confirmed in the validation cohort.
CONCLUSIONS: The novel classification system of MVI and the nomograms enabled more accurate predictions of risk of tumor recurrence and overall survival in patients with HCC after R0 liver resection.
METHODS: The clinicopathological and follow-up data of 686 consecutive patients with HCC who underwent R0 liver resection in our hospital between December 2009 and April 2010 were retrospectively reviewed. A classification system was established based on histological characteristics of MVI. Nomograms were then formulated using a multivariate Cox proportional hazards model to analyze. The results were validated using bootstrap resampling and a new 225-patient validation cohort operated in May and June 2010 at the same institution.
RESULTS: A 4-stratification classification system of MVI was established, which satisfactorily determined the risk of survival and early tumor recurrence. Then, an eight-factor nomogram for survival prediction and a seven-factor nomogram for prediction of early tumor recurrence were established. The concordance indices were 0.78 for the survival-prediction nomogram and 0.72 for the recurrence-prediction nomogram. These indices were both significantly higher than the following three commonly used staging systems: tumor-node-metastasis staging system (seventh edition, 0.67/0.65), Japan Integrated Staging System (0.58/0.58) and Chinese University Prognostic Index (0.52/0.51). The calibration curves showed good agreement between predictions by the nomograms and actual survival outcomes. These results were confirmed in the validation cohort.
CONCLUSIONS: The novel classification system of MVI and the nomograms enabled more accurate predictions of risk of tumor recurrence and overall survival in patients with HCC after R0 liver resection.
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