Journal of Cancer Research and Clinical Oncology

, Volume 143, Issue 2, pp 293–303 | Cite as

Novel microvascular invasion-based prognostic nomograms to predict survival outcomes in patients after R0 resection for hepatocellular carcinoma

  • Long-Hai Feng
  • Hui Dong
  • Wan-Yee Lau
  • Hua Yu
  • Yu-Yao Zhu
  • Yun Zhao
  • Yu-Xi Lin
  • Jia Chen
  • Meng-Chao Wu
  • Wen-Ming Cong
Original Article – Clinical Oncology

Abstract

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.

Keywords

Microvascular invasion Pathological type Classification Prognostic nomogram 

Notes

Acknowledgments

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.

Funding

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.

Ethical approval

This article does not contain any studies with human participants or animals performed by any of the authors.

Informed consent

For this type of study formal consent is not required.

Supplementary material

432_2016_2286_MOESM1_ESM.pdf (986 kb)
Supplementary material 1 (PDF 985 kb)

References

  1. Bosman FT, Carneiro F, Hruban RH et al (2010) WHO classification of tumours of the digestive system, 4th edn. IARC, Lyon, p 197Google Scholar
  2. 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
  3. 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
  4. 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
  5. Cong WM, Wu MC (2015) New insights into molecular diagnostic pathology of primary liver cancer: advances and challenges. Cancer Lett 368:14–19. doi: 10.1016/j.canlet.2015.07.043 CrossRefPubMedGoogle Scholar
  6. Du M, Chen L, Zhao J et al (2014) Microvascular invasion (MVI) is a poorer prognostic predictor for small hepatocellular carcinoma. BMC Cancer 14:38. doi: 10.1186/1471-2407-14-38 CrossRefPubMedPubMedCentralGoogle Scholar
  7. Fan ST, Poon RT, Yeung C et al (2011) Outcome after partial hepatectomy for hepatocellular cancer within the Milan criteria. Br J Surg 98:1292–1300. doi: 10.1002/bjs.7583 CrossRefPubMedGoogle Scholar
  8. Forner A, Reig ME, de Lope CR et al (2010) Current strategy for staging and treatment: the BCLC update and future prospects. Semin Liver Dis 30:61–74. doi: 10.1055/s-0030-1247133 CrossRefPubMedGoogle Scholar
  9. Gantt CL (1981) Red blood cells for cancer patients. Lancet 2:363CrossRefPubMedGoogle Scholar
  10. Harrell FE Jr (2015) Regression modeling strategies: with applications to linear models, logistic and ordinal regression, and survival analysis, 2nd edn. Springer, BerlinCrossRefGoogle Scholar
  11. 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
  12. Hirokawa F, Hayashi M, Miyamoto Y et al (2014) Outcomes and predictors of microvascular invasion of solitary hepatocellular carcinoma. Hepatol Res 44:846–853. doi: 10.1111/hepr.12196 CrossRefPubMedGoogle Scholar
  13. Kim Y, Margonis GA, Prescott JD et al (2015) Nomograms to predict recurrence-free and overall survival after curative resection of adrenocortical carcinoma. JAMA Surg. doi: 10.1001/jamasurg.2015.4516 Google Scholar
  14. 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
  15. Lei Z, Li J, Wu D et al (2015) Nomogram for preoperative estimation of microvascular invasion risk in hepatitis B virus-related hepatocellular carcinoma within the milan criteria. JAMA Surg. doi: 10.1001/jamasurg.2015.4257 Google Scholar
  16. 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
  17. Lu XY, Xi T, Lau WY et al (2011) Pathobiological features of small hepatocellular carcinoma: correlation between tumor size and biological behavior. J Cancer Res Clin Oncol 137:567–575. doi: 10.1007/s00432-010-0909-5 CrossRefPubMedGoogle Scholar
  18. Mazzaferro V, Llovet JM, Miceli R et al (2009) Predicting survival after liver transplantation in patients with hepatocellular carcinoma beyond the Milan criteria: a retrospective, exploratory analysis. Lancet Oncol 10:35–43. doi: 10.1016/S1470-2045(08)70284-5 CrossRefPubMedGoogle Scholar
  19. Roayaie S, Blume IN, Thung SN et al (2009) A system of classifying microvascular invasion to predict outcome after resection in patients with hepatocellular carcinoma. Gastroenterology 137:850–855. doi: 10.1053/j.gastro.2009.06.003 CrossRefPubMedPubMedCentralGoogle Scholar
  20. Rodriguez-Peralvarez M, Luong TV, Andreana L et al (2013) A systematic review of microvascular invasion in hepatocellular carcinoma: diagnostic and prognostic variability. Ann Surg Oncol 20:325–339. doi: 10.1245/s10434-012-2513-1 CrossRefPubMedGoogle Scholar
  21. Shirabe K, Toshima T, Kimura K et al (2014) New scoring system for prediction of microvascular invasion in patients with hepatocellular carcinoma. Liver Int 34:937–941. doi: 10.1111/liv.12459 CrossRefPubMedGoogle Scholar
  22. Shuqun C, Mengchao W, Han C et al (2007) Tumor thrombus types influence the prognosis of hepatocellular carcinoma with the tumor thrombi in the portal vein. Hepatogastroenterology 54:499–502PubMedGoogle Scholar
  23. Sumie S, Nakashima O, Okuda K et al (2014) The significance of classifying microvascular invasion in patients with hepatocellular carcinoma. Ann Surg Oncol 21:1002–1009. doi: 10.1245/s10434-013-3376-9 CrossRefPubMedGoogle Scholar
  24. 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
  25. Toyosaka A, Okamoto E, Mitsunobu M et al (1996) Intrahepatic metastases in hepatocellular carcinoma: evidence for spread via the portal vein as an efferent vessel. Am J Gastroenterol 91:1610–1615PubMedGoogle Scholar
  26. Vamvakas EC (2014) Allogeneic blood transfusion and cancer recurrence: 20 years later. Transfusion 54:2149–2153. doi: 10.1111/trf.12689 CrossRefPubMedGoogle Scholar
  27. Wang Y, Li J, Xia Y et al (2013) Prognostic nomogram for intrahepatic cholangiocarcinoma after partial hepatectomy. J Clin Oncol 31:1188–1195. doi: 10.1200/JCO.2012.41.5984 CrossRefPubMedGoogle Scholar
  28. Yamamoto Y, Ikoma H, Morimura R et al (2015) Post-hepatectomy survival in advanced hepatocellular carcinoma with portal vein tumor thrombosis. World J Gastroenterol 21:246–253. doi: 10.3748/wjg.v21.i1.246 CrossRefPubMedPubMedCentralGoogle Scholar
  29. Yang P, Qiu J, Li J et al (2016) Nomograms for pre- and postoperative prediction of long-term survival for patients who underwent hepatectomy for multiple hepatocellular carcinomas. Ann Surg 263:778–786. doi: 10.1097/SLA.0000000000001339 CrossRefPubMedGoogle Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2016

Authors and Affiliations

  • Long-Hai Feng
    • 1
    • 2
  • Hui Dong
    • 1
  • Wan-Yee Lau
    • 3
    • 4
  • Hua Yu
    • 1
  • Yu-Yao Zhu
    • 1
  • Yun Zhao
    • 1
  • Yu-Xi Lin
    • 5
  • Jia Chen
    • 1
  • Meng-Chao Wu
    • 3
  • Wen-Ming Cong
    • 1
  1. 1.Department of Pathology, Eastern Hepatobiliary Surgery HospitalThe Second Military Medical UniversityShanghaiChina
  2. 2.Department of Pathology, Changhai HospitalThe Second Military Medical UniversityShanghaiChina
  3. 3.Department of Surgery, Eastern Hepatobiliary Surgery HospitalThe Second Military Medical UniversityShanghaiChina
  4. 4.Faculty of MedicineThe Chinese University of Hong KongShatinHong Kong SAR, China
  5. 5.Department of Laboratory Medicines234 Military Hospital of ChinaChaoyangChina

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