Skip to main content

Advertisement

SpringerLink
Log in

Low preoperative prognostic nutritional index predicts poor survival in patients with newly diagnosed high-grade gliomas

  • Clinical Study
  • Published:
Journal of Neuro-Oncology Aims and scope Submit manuscript

Abstract

Preoperative prognostic nutritional index (PNI) has been widely demonstrated to predict survival of patients with malignant tumors. Its utility in predicting outcomes in patients with high-grade gliomas (HGG) remains undefined. A retrospective study of 188 HGG patients was conducted. An optimal PNI cut-off value was applied to stratify patients into high PNI (≥52.55, n = 78) and low PNI (<52.55, n = 110) groups. Univariate and multivariate analysis was performed to identify prognostic factors associated with overall survival (OS) and progression free survival (PFS). The resulting prognostic models were externally validated using a demographic-matched cohort of 130 HGG patients. In the training set, PNI value was negatively correlated with age (p = 0.027) and tumor grade (p = 0.048). Both PFS (8.27 vs. 20.77 months, p < 0.001) and OS (13.57 vs. 33.23 months, p < 0.001) were significantly worse in the low PNI group. Strikingly, patients in high PNI group had a 52% decrease in the risk of tumor progression and 55% decrease of death relative to low PNI. Multivariate analysis further demonstrated PNI as an independent predictor for PFS (HR = 0.62, 95% CI 0.43–0.87) and OS (HR = 0.56, 95% CI 0.38–0.80). The PNI retained independent prognostic value in the validation set for both PFS (p = 0.013) and OS (p = 0.003). On subgroup analysis by tumor grade and treatment modalities, both PFS and OS were better for the patients with high PNI. The PNI is a potentially valuable preoperative marker for the survival of patients following HGG resection.

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

Access this article

Log in via an institution

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

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2

Similar content being viewed by others

References

  1. Ostrom QT, Gittleman H, Fulop J, Liu M, Blanda R, Kromer C, Wolinsky Y, Kruchko C, Barnholtz-Sloan JS (2015) CBTRUS statistical report: primary brain and central nervous system tumors diagnosed in the United States in 2008–2012. Neuro Oncol 17(Suppl 4):iv1–iv62. doi:10.1093/neuonc/nov189

    Article  PubMed  PubMed Central  Google Scholar 

  2. Wen PY, Kesari S (2008) Malignant gliomas in adults. N Engl J Med 359(5):492–507. doi:10.1056/NEJMra0708126

    Article  CAS  PubMed  Google Scholar 

  3. Gilbert MR, Dignam JJ, Armstrong TS, Wefel JS, Blumenthal DT, Vogelbaum MA, Colman H, Chakravarti A, Pugh S, Won M, Jeraj R, Brown PD, Jaeckle KA, Schiff D, Stieber VW, Brachman DG, Werner-Wasik M, Tremont-Lukats IW, Sulman EP, Aldape KD, Curran WJ, Mehta MP (2014) A randomized trial of bevacizumab for newly diagnosed glioblastoma. N Engl J Med 370(8):699–708. doi:10.1056/NEJMoa1308573

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Wick W, Meisner C, Hentschel B, Platten M, Schilling A, Wiestler B, Sabel MC, Koeppen S, Ketter R, Weiler M, Tabatabai G, von Deimling A, Gramatzki D, Westphal M, Schackert G, Loeffler M, Simon M, Reifenberger G, Weller M (2013) Prognostic or predictive value of MGMT promoter methylation in gliomas depends on IDH1 mutation. Neurology 81(17):1515–1522. doi:10.1212/WNL.0b013e3182a95680

    Article  CAS  PubMed  Google Scholar 

  5. Louis DN, Perry A, Reifenberger G, von Deimling A, Figarella-Branger D, Cavenee WK, Ohgaki H, Wiestler OD, Kleihues P, Ellison DW (2016) The 2016 World Health Organization classification of tumors of the central nervous system: a summary. Acta Neuropathol 131(6):803–820

    Article  Google Scholar 

  6. Wei XL, Wang FH, Zhang DS, Qiu MZ, Ren C, Jin Y, Zhou YX, Wang DS, He MM, Bai L, Wang F, Luo HY, Li YH, Xu RH (2015) A novel inflammation-based prognostic score in esophageal squamous cell carcinoma: the C-reactive protein/albumin ratio. BMC Cancer 15:350. doi:10.1186/s12885-015-1379-6

    Article  PubMed  PubMed Central  Google Scholar 

  7. Tohme S, Sukato D, Chalhoub D, McDonald KA, Zajko A, Amesur N, Orons P, Marsh JW, Geller DA, Tsung A (2015) Neutrophil-lymphocyte ratio is a simple and novel biomarker for prediction of survival after radioembolization for metastatic colorectal cancer. Ann Surg Oncol 22(5):1701–1707. doi:10.1245/s10434-014-4050-6

    Article  PubMed  Google Scholar 

  8. Onodera T, Goseki N, Kosaki G (1984) Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients. Nihon Geka Gakkai Zasshi 85 (9):1001–1005

    CAS  PubMed  Google Scholar 

  9. Hong S, Zhou T, Fang W, Xue C, Hu Z, Qin T, Tang Y, Chen Y, Ma Y, Yang Y, Hou X, Huang Y, Zhao H, Zhao Y, Zhang L (2015) The prognostic nutritional index (PNI) predicts overall survival of small-cell lung cancer patients. Tumour Biol 36(5):3389–3397. doi:10.1007/s13277-014-2973-y

    Article  CAS  PubMed  Google Scholar 

  10. Pinato DJ, North BV, Sharma R (2012) A novel, externally validated inflammation-based prognostic algorithm in hepatocellular carcinoma: the prognostic nutritional index (PNI). Br J Cancer 106(8):1439–1445. doi:10.1038/bjc.2012.92

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Yang Z, Zhang B, Hou L, Xie Y, Cao X (2014) Pre-operative prognostic nutritional index predicts the outcomes for triple-negative breast cancer. Tumour Biol 35(12):12165–12171. doi:10.1007/s13277-014-2524-6

    Article  CAS  PubMed  Google Scholar 

  12. Louis DN, Ohgaki H, Wiestler OD, Cavenee WK, Burger PC, Jouvet A, Scheithauer BW, Kleihues P (2007) The 2007 WHO classification of tumours of the central nervous system. Acta Neuropathol 114(2):97–109. doi:10.1007/s00401-007-0243-4

    Article  PubMed  PubMed Central  Google Scholar 

  13. Weller M, Pfister SM, Wick W, Hegi ME, Reifenberger G, Stupp R (2013) Molecular neuro-oncology in clinical practice: a new horizon. Lancet Oncol 14(9):e370–e379. doi:10.1016/s1470-2045(13)70168-2

    Article  CAS  PubMed  Google Scholar 

  14. Mantovani A, Allavena P, Sica A, Balkwill F (2008) Cancer-related inflammation. Nature 454(7203):436–444. doi:10.1038/nature07205

    Article  CAS  PubMed  Google Scholar 

  15. Sánchez-Lara K, Turcott JG, Juárez E, Guevara P, Núñez-Valencia C, Oñate-Ocaña LF, Flores D, Arrieta O (2012) Association of nutrition parameters including bioelectrical impedance and systemic inflammatory response with quality of life and prognosis in patients with advanced non-small-cell lung cancer: a prospective study. Nutr Cancer 64(4):526–534

    Article  Google Scholar 

  16. Dudley ME, Wunderlich JR, Robbins PF, Yang JC, Hwu P, Schwartzentruber DJ, Topalian SL, Sherry R, Restifo NP, Hubicki AM (2002) Cancer regression and autoimmunity in patients after clonal repopulation with antitumor lymphocytes. Science 298(5594):850–854

    Article  CAS  Google Scholar 

  17. Han S, Zhang C, Li Q, Dong J, Liu Y, Huang Y, Jiang T, Wu A (2014) Tumour-infiltrating CD4(+) and CD8(+) lymphocytes as predictors of clinical outcome in glioma. Br J Cancer 110(10):2560–2568. doi:10.1038/bjc.2014.162

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Bairey O, Shacham-Abulafia A, Shpilberg O, Gurion R (2015) Serum albumin level at diagnosis of diffuse large B-cell lymphoma: an important simple prognostic factor. Hematol Oncol. doi:10.1002/hon.2233

    Article  PubMed  Google Scholar 

  19. Hülshoff A, Schricker T, Elgendy H, Hatzakorzian R, Lattermann R (2013) Albumin synthesis in surgical patients. Nutrition 29(5):703–707

    Article  Google Scholar 

  20. Weissenberger J, Loeffler S, Kappeler A, Kopf M, Lukes A, Afanasieva TA, Aguzzi A, Weis J (2004) IL-6 is required for glioma development in a mouse model. Oncogene 23(19):3308–3316

    Article  CAS  Google Scholar 

  21. Estève PO, Chicoine É, Robledo O, Aoudjit F, Descoteaux A, Potworowski EF, St-Pierre Y (2002) Protein kinase C-ζ regulates transcription of the matrix metalloproteinase-9 gene induced by IL-1 and TNF-α in glioma cells via NF-κB. J Biol Chem 277(38):35150–35155

    Article  Google Scholar 

  22. Gupta D, Lis CG (2010) Pretreatment serum albumin as a predictor of cancer survival: a systematic review of the epidemiological literature. Nutr J 9(1):1

    Article  Google Scholar 

  23. Borg N, Guilfoyle MR, Greenberg DC, Watts C, Thomson S (2011) Serum albumin and survival in glioblastoma multiforme. J Neurooncol 105(1):77–81

    Article  CAS  Google Scholar 

  24. Chambless LB, Parker SL, Hassam-Malani L, McGirt MJ, Thompson RC (2012) Type 2 diabetes mellitus and obesity are independent risk factors for poor outcome in patients with high-grade glioma. J Neurooncol 106(2):383–389. doi:10.1007/s11060-011-0676-4

    Article  PubMed  Google Scholar 

  25. Sabha N, Knobbe CB, Maganti M, Al Omar S, Bernstein M, Cairns R, Cako B, von Deimling A, Capper D, Mak TW, Kiehl TR, Carvalho P, Garrett E, Perry A, Zadeh G, Guha A, Sidney C (2014) Analysis of IDH mutation, 1p/19q deletion, and PTEN loss delineates prognosis in clinical low-grade diffuse gliomas. Neuro Oncol 16(7):914–923. doi:10.1093/neuonc/not299

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  26. Eckel-Passow JE, Lachance DH, Molinaro AM, Walsh KM, Decker PA, Sicotte H, Pekmezci M, Rice T, Kosel ML, Smirnov IV, Sarkar G, Caron AA, Kollmeyer TM, Praska CE, Chada AR, Halder C, Hansen HM, McCoy LS, Bracci PM, Marshall R, Zheng S, Reis GF, Pico AR, O’Neill BP, Buckner JC, Giannini C, Huse JT, Perry A, Tihan T, Berger MS, Chang SM, Prados MD, Wiemels J, Wiencke JK, Wrensch MR, Jenkins RB (2015) Glioma groups based on 1p/19q, IDH, and TERT promoter mutations in tumors. N Engl J Med 372(26):2499–2508. doi:10.1056/NEJMoa1407279

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

This work was supported by the Science and Technology Planning Project of Guangdong Province, China [Grant Numbers 2013B090500095, 2014A020212576, 2015B010125003]; the National Natural Science Foundation of China [Grant Numbers 81201982, 81572500]; and the Doctoral Fund of Ministry of Education of China [Grant Number 20120171120110].

Author information

Authors and Affiliations

  1. Department of Neurosurgery/Neuro-oncology, Sun Yat-sen University Cancer Center, State Key Laboratory of Oncology in South China, Collaborative Innovation Center for Cancer Medicine, Guangzhou, China

    Zhen-Qiang He, Chao Ke, Fuad Al-Nahari, Hao Duan, Cheng-Cheng Guo, Yang Wang, Xiang-Heng Zhang, Yin-Sheng Chen, Jian Wang, Zhong-Ping Chen, Xiao-Bing Jiang & Yong-Gao Mou

  2. Key Laboratory of Translational Radiation Oncology, Hunan Province, Department of Radiation Oncology, Hunan Cancer Hospital, The Affiliated Cancer Hospital of Xiangya School of Medicine, Central South University, Changsha, China

    Zhi-Gang Liu

Authors
  1. Zhen-Qiang He
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Chao Ke
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Fuad Al-Nahari
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hao Duan
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cheng-Cheng Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Yang Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Xiang-Heng Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Yin-Sheng Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Zhi-Gang Liu
    View author publications

    You can also search for this author in PubMed Google Scholar

  10. Jian Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  11. Zhong-Ping Chen
    View author publications

    You can also search for this author in PubMed Google Scholar

  12. Xiao-Bing Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  13. Yong-Gao Mou
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Xiao-Bing Jiang or Yong-Gao Mou.

Ethics declarations

Conflict of interest

The authors report no conflicts of interest in this work.

Electronic supplementary material

Below is the link to the electronic supplementary material.

11060_2016_2361_MOESM1_ESM.tif

Supplementary Fig. S1 Kaplan-Meier survival curves of HGG patients by IDH1 mutation status. Mutated IDH1 was significantly associated with better PFS (A) and OS (B). (TIF 424 KB)

11060_2016_2361_MOESM2_ESM.tif

Supplementary Fig. S2 Kaplan-Meier survival curves of all HGG patients. Patients in PNI-high group had significantly longer PFS and OS than patients in PNI-low group (Both p&#x003C;0.001). (TIF 392 KB)

Supplementary material 3 (DOCX 34 KB)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

He, ZQ., Ke, C., Al-Nahari, F. et al. Low preoperative prognostic nutritional index predicts poor survival in patients with newly diagnosed high-grade gliomas. J Neurooncol 132, 239–247 (2017). https://doi.org/10.1007/s11060-016-2361-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11060-016-2361-0

Keywords

Search

Navigation