Skip to main content
Log in

Prognostic Significance of Preoperative Controlling Nutritional Status (CONUT) Score in Patients Undergoing Hepatic Resection for Hepatocellular Carcinoma

  • Original Scientific Report
  • Published:
World Journal of Surgery Aims and scope Submit manuscript

Abstract

Background

The Controlling Nutritional Status (CONUT) score is an objective tool widely used to assess nutritional status in patients with inflammatory disease, chronic heart failure, and chronic liver disease. The relationship between CONUT score and prognosis in patients who have undergone hepatic resection, however, has not been evaluated.

Methods

Data were retrospectively collected for 357 consecutive patients with hepatocellular carcinoma (HCC) who had undergone hepatic resection with curative intent between January 2004 and December 2015. The patients were assigned to two groups, those with preoperative CONUT scores ≤3 (low CONUT score) and >3 (high CONUT score), and their clinicopathological characteristics, surgical outcomes, and long-term survival were compared.

Results

Of the 357 patients, 69 (19.3%) had high (>3) and 288 (80.7%) had low (≤3) preoperative CONUT scores. High CONUT score was significantly associated with HCV infection, low serum albumin and cholesterol concentrations, low lymphocyte count, shorter prothrombin time, Child–Pugh B and liver damage B scores, and blood transfusion. Multivariate analysis identified six factors prognostic of poor overall survival (older age, liver damage B score, high CONUT score, poor tumor differentiation, the presence of intrahepatic metastases, and blood transfusion) and five factors prognostic of reduced recurrence-free survival (older age, higher ICGR15, larger tumor size, presence of intrahepatic metastasis, and blood transfusion).

Conclusions

In patients with HCC, preoperative CONUT scores are predictive of poorer overall survival, even after adjustments for other known predictors.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Alberino F, Gatta A, Amodio P et al (2001) Nutrition and survival in patients with liver cirrhosis. Nutrition 17:445–450

    Article  CAS  PubMed  Google Scholar 

  2. Caregaro L, Alberino F, Amodio P et al (1996) Malnutrition in alcoholic and virus-related cirrhosis. Am J Clin Nutr 63:602–609

    CAS  PubMed  Google Scholar 

  3. Takenaka K, Kawahara N, Yamamoto K et al (1996) Results of 280 liver resections for hepatocellular carcinoma. Arch Surg 131:71–76

    Article  CAS  PubMed  Google Scholar 

  4. Taketomi A, Kitagawa D, Itoh S et al (2007) Trends in morbidity and mortality after hepatic resection for hepatocellular carcinoma: an institute’s experience with 625 patients. J Am Coll Surg 204:580–587

    Article  PubMed  Google Scholar 

  5. Yamashita Y, Taketomi A, Itoh S et al (2007) Longterm favorable results of limited hepatic resections for patients with hepatocellular carcinoma: 20 years of experience. J Am Coll Surg 205:19–26

    Article  PubMed  Google Scholar 

  6. Lien YC, Hsieh CC, Wu YC et al (2004) Preoperative serum albumin level is a prognostic indicator for adenocarcinoma of the gastric cardia. J Gastointest Surg 8:1041–1048

    Article  Google Scholar 

  7. Ray-Coquard I, Cropet C, Van Glabbeke M et al (2009) Lymphopenia as a prognostic factor for overall in advanced carcinomas, sarcomas, and lymphomas. Cancer Res 69:5383–5391

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Schwegler I, von Holzen A, Gutzwiller JP et al (2010) Nutritional risk is a clinical predictor of postoperative mortality and morbidity in surgery for colorectal cancer. Br J Surg 97:92–97

    Article  CAS  PubMed  Google Scholar 

  9. de Ulibarri Perez JI, Gonzalez-Madrono A, de Villar NG et al (2005) CONUT: a tool for Controlling Nutritional Status. First validation in a hospital population. Nutr Hosp 20:38–45

    Google Scholar 

  10. Ueno T, Hirayama S, Ito M et al (2013) Albumin concentration determined by the modified bromocresol purple method is superior to that by the bromocresol green method for assessing nutritional status in malnourished patients with inflammation. Ann Clin Biochem 50:576–584

    Article  PubMed  Google Scholar 

  11. Nakagomi A, Kohashi K, Morisawa T et al (2016) Nutritional status is associated with inflammation and predicts a poor outcome in patients with chronic heart failure. J Atheroscler Thromb 23(6):713–727

    Article  CAS  PubMed  Google Scholar 

  12. Narumi T, Arimoto T, Funayama A et al (2013) Prognostic importance of objective nutritional indexes in patients with chronic heart failure. J Cardiol 62:307–313

    Article  PubMed  Google Scholar 

  13. Taniguchi E, Kawaguchi T, Otsuka M et al (2013) Nutritional assessments for ordinary medical care in patients with chronic liver disease. Hepatol Res 43:192–199

    Article  CAS  PubMed  Google Scholar 

  14. Lopez-Larramona G, Lucendo AJ, Tenias JM (2015) Association between nutritional screening via the controlling nutritional status index and bone mineral density in chronic liver disease of various etiologies. Hepatol Res 45:618–628

    Article  CAS  PubMed  Google Scholar 

  15. Iseki Y, Shibutani M, Maeda K et al (2014) Impact of the preoperative controlling nutritional status (CONUT) score on the survival after curative surgery for colorectal cancer. PLoS ONE 10:e0132488

    Article  Google Scholar 

  16. Hirahara N, Matsubara T, Hayashi H et al (2016) Prognostic importance of controlling nutritional status in patients undergoing curative thoracoscopic esophagectomy for esophageal cancer. Am J Ther. doi:10.1097/MJT.0000000000000414

    PubMed  Google Scholar 

  17. Liver cancer study group of Japan (2003) General rules for the clinical and pathological study of primary liver cancer, Second English edition edn. Kanehara & Co, Tokyo, pp 34–35

    Google Scholar 

  18. Dindo D, Demartines N, Clavien PA (2004) Classification of surgical complications: a new proposal with evaluation in a cohort of 6336 patients and results of a survey. Ann Surg 240:205–213

    Article  PubMed  PubMed Central  Google Scholar 

  19. Youden WJ (1950) Index for rating diagnostic tests. Cancer 3:32–35

    Article  CAS  PubMed  Google Scholar 

  20. Shimada M, Takenaka K, Gion T et al (1996) Prognosis of recurrent hepatocellular carcinoma: a 10-year surgical experience in Japan. Gastroenterology 111:720–726

    Article  CAS  PubMed  Google Scholar 

  21. Rahbari NN, Koch M, Mehabi A et al (2009) Portal triad clamping versus vascular exclusion for vascular control during hepatic resection: a systematic review and meta-analysis. J Gastrointest Surg 13:558–568

    Article  PubMed  Google Scholar 

  22. de Ulibarri Perez JI, Femandez G, Rodriguez Salvanes F et al (2014) Nutritional screening control of clinical undernutrition with analytical parameters. Nutr Hosp 29:797–811

    PubMed  Google Scholar 

  23. Yoshida N, Baba Y, Shigaki H, Harada K et al (2016) Preoperative nutritional assessment by controlling nutritional status (CONUT) is useful to estimate postoperative morbidity after esophagectomy for esophageal cancer. World J Surg 40(8):1910–1917. doi:10.1007/s00423-017-1553-1

    Article  PubMed  Google Scholar 

  24. Harimoto N, Shirabe K, Ikegami T et al (2015) Postoperative complications are predictive of poor prognosis in hepatocellular carcinoma. J Surg Res 199(2):470–477

    Article  PubMed  Google Scholar 

  25. Coussens LM, Werb Z (2002) Inflammation and cancer. Nature 420:860–867

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Mantovani A, Allavena P, Sica A et al (2008) Cancer-related inflammation. Nature 454:436–444

    Article  CAS  PubMed  Google Scholar 

  27. Roxburgh CS, McMillan DC (2010) Role of systemic inflammatory response in predicting survival in patients with primary operative cancer. Future Oncol 6:149–163

    Article  CAS  PubMed  Google Scholar 

  28. Katz SC, Shia J, Liau KH et al (2009) Operative blood loss independently predicts recurrence and survival after resection of hepatocellular carcinoma. Ann Surg 249:617–623

    Article  PubMed  Google Scholar 

  29. Harada N, Shirabe K, Maeda T et al (2015) Blood transfusion is associated with recurrence of hepatocellular carcinoma after hepatectomy in Child–Pugh class A patients. World J Surg 39:1044–1051. doi:10.1007/s00268-014-2891-6

    Article  PubMed  Google Scholar 

  30. Gascon P, Zoumbos NC, Young NS (1984) Immunological abnormalities in patients receiving multiple blood transfusions. Ann Intern Med 100:173–177

    Article  CAS  PubMed  Google Scholar 

  31. Kaplan J, Sarnaik S, Gitlin J et al (1984) Diminished helper/suppressor lymphocyte ratios and natural killer activity in recipients of repeated blood transfusions. Blood 64:308–310

    CAS  PubMed  Google Scholar 

  32. Itoh S, Fukuzawa K, Shitomi Y, Okamoto M et al (2012) Impact of the VIO system in hepatic resection for patients with hepatocellular carcinoma. Surg Today 42:1176–1182

    Article  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Norifumi Harimoto.

Ethics declarations

Conflict of interest

There was no conflict of interest and financial support.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Harimoto, N., Yoshizumi, T., Sakata, K. et al. Prognostic Significance of Preoperative Controlling Nutritional Status (CONUT) Score in Patients Undergoing Hepatic Resection for Hepatocellular Carcinoma. World J Surg 41, 2805–2812 (2017). https://doi.org/10.1007/s00268-017-4097-1

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00268-017-4097-1

Navigation