Novel microvascular invasion-based prognostic nomograms to predict survival outcomes in patients after R0 resection for hepatocellular carcinoma
- 1.2k Downloads
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.
- Bosman FT, Carneiro F, Hruban RH et al (2010) WHO classification of tumours of the digestive system, 4th edn. IARC, Lyon, p 197Google Scholar
- Chan AC, Fan ST, Poon RT et al (2013) Evaluation of the seventh edition of the American Joint Committee on Cancer tumour–node–metastasis (TNM) staging system for patients undergoing curative resection of hepatocellular carcinoma: implications for the development of a refined staging system. HPB (Oxford) 15:439–448. doi: 10.1111/j.1477-2574.2012.00617.x CrossRefGoogle Scholar
- Chinese Society of Liver Cancer, Chinese Anti-Cancer Association, Liver Cancer Study Group, Chinese Society of Hepatology, Chinese Medical Association, Chinese Society of Pathology, Chinese Anti-Cancer Association et al (2015) Evidence-based practice guidelines for standardized pathological diagnosis of primary liver cancer in China: (2015 edition). Zhonghua Gan Zang Bing Za Zhi 23:321–327. doi: 10.3760/cma.j.issn.1007-3418.2015.05.001 Google Scholar
- Chung H, Kudo M, Takahashi S et al (2008) Comparison of three current staging systems for hepatocellular carcinoma: Japan integrated staging score, new Barcelona Clinic Liver Cancer staging classification, and Tokyo score. J Gastroenterol Hepatol 23:445–452. doi: 10.1111/j.1440-1746.2007.05075.x CrossRefPubMedGoogle Scholar
- Harrell FE Jr (2011) Rms: regression modeling strategies. R Package version 2.13.2. https://cran.r-project.org/bin/windows/base/old/2.13.2. Accessed Sep 2011
- Kitai S, Kudo M, Minami Y et al (2008) Validation of a new prognostic staging system for hepatocellular carcinoma: a comparison of the biomarker-combined Japan Integrated Staging Score, the conventional Japan Integrated Staging Score and the BALAD Score. Oncology 75(Suppl 1):83–90. doi: 10.1159/000173428 CrossRefPubMedGoogle Scholar
- Leung TW, Tang AM, Zee B et al (2002) Construction of the Chinese University Prognostic Index for hepatocellular carcinoma and comparison with the TNM staging system, the Okuda staging system, and the Cancer of the Liver Italian Program staging system: a study based on 926 patients. Cancer 94:1760–1769CrossRefPubMedGoogle Scholar
- Theise ND, Curado MP, Franceschi S et al (2010) Hepatocellular carcinoma. In: Bosman FT, Carneiro F, Hruban RH, Theise ND (eds) WHO classification of tumours of the digestive system, 4th edn. Lyon, IARC, pp 205–216Google Scholar