Novel microvascular invasion-based prognostic nomograms to predict survival outcomes in patients after R0 resection for hepatocellular carcinoma
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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.
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.
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.
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.
KeywordsMicrovascular invasion Pathological type Classification Prognostic nomogram
We thank Doctor Ying Dong (Department of Preventive Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai) for guidance on the use of the R statistical software and Xue-Bo Yu and Wei Dong (Department of Pathology, Eastern Hepatobiliary Surgery Hospital, Shanghai) for their advice on the pathological techniques used in this study.
This study was funded by the Grants from the National Natural Science Foundation of China (Grant Nos. 81472278; 81272662) and Funds for Creative Research Groups of National Natural Science Foundation of China (Grant No. 81221061).
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflict of interest.
This article does not contain any studies with human participants or animals performed by any of the authors.
For this type of study formal consent is not required.
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