International Journal of Clinical Oncology

, Volume 24, Issue 10, pp 1301–1310 | Cite as

Clinical significance of prognostic nutritional index (PNI) in malignant melanoma

  • Cem MiriliEmail author
  • Ali Yılmaz
  • Serkan Demirkan
  • Mehmet Bilici
  • Salim Basol Tekin
Original Article



Nutrition and inflammation play a crucial role in the development of cancer. The prognostic value of the prognostic nutritional index (PNI) has been confirmed in some types of human cancers. However, few studies are available indicating its prognostic power in patients with malignant melanoma (MM). Thus, we aimed to identify baseline peripheral blood biomarkers to predict the outcome of MM patients

Material and methods

Data of 101 patients with MM were evaluated retrospectively. Associations between clinical and histopathological parameters with overall survival (OS) and progression-free survival (PFS) were analyzed using Kaplan–Meier curves and compared by the log-rank test. The optimal cutoff values were determined by a receiver operating characteristic (ROC) curve analysis. Neutrophil–lymphocyte ratio (NLR), systemic immune-inflammation index (SII) and PNI were grouped based on a cutoff points 2.18, 547.1, and 40.1, respectively. Univariate and multivariate analyses were used to assess their prognostic values for overall survival (OS).


Lower NLR ( < 2.18), SII ( < 547.1) and higher PNI ( ≥ 40.1) were linked with a longer PFS and OS in patients with MM, as reflected in the Kaplan–Meier analyses. In univariate analysis, TNM stage, Breslow thickness, Clark stage, ulceration, Ki67 status, LDH, NLR, SII, and PNI were significantly associated with OS. Multivariate analysis identified TNM stage, ulceration, LDH and PNI as an independent predictor of OS in patients with MM.


PNI can be regarded as a novel independent prognostic factor for predicting OS in MM.


Malignant melanoma Prognostic nutritional index Neutrophil–lymphocyte ratio Systemic immune-inflammation index 



This research received no specific grant from any funding agency in the public, commercial, or not-for-profit sectors.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.


  1. 1.
    Friberg S, Nystrom A (2015) Cancer metastases: early dissemination and late recurrences. Cancer Growth Metastasis 8:43–49CrossRefGoogle Scholar
  2. 2.
    Davey RJ, van der Westhuizen A, Bowden NA (2016) Metastatic melanoma treatment: combining old and new therapies. Crit Rev Oncol Hematol 98:242–253CrossRefGoogle Scholar
  3. 3.
    Siegel RL, Miller KD, Jemal A (2017) Cancer statistics, 2017. CA Cancer J Clin 67(1):7–30CrossRefGoogle Scholar
  4. 4.
    Pavri SN, Clune J, Ariyan S et al (2016) Malignant melanoma: beyond the basics. Plast Reconstr Surg 138(2):330–340CrossRefGoogle Scholar
  5. 5.
    Rozeman EA, Dekker TJ, Haanen JB et al (2018) Advanced melanoma: current treatment options, biomarkers, and future perspectives. Am J Clin Dermatol 19(3):303–317CrossRefGoogle Scholar
  6. 6.
    Miller KD, Siegel RL, Lin CC et al (2016) Cancer treatment and survivorship statistics, 2016. CA Cancer J Clin 66(4):271–289CrossRefGoogle Scholar
  7. 7.
    Ali Z, Yousaf N, Larkin J (2013) Melanoma epidemiology, biology and prognosis. EJC Suppl 11(2):81–91CrossRefGoogle Scholar
  8. 8.
    Liu J, Charles PL, Zhou PB (2015) Inflammation fuels tumor progress and metastasis. Curr Pharm Des 21(21):3032–3040CrossRefGoogle Scholar
  9. 9.
    El-Hag A, Clark RA (1987) Immunosuppression by activated human neutrophils. Dependence on the myeloperoxidase system. J Immunol 139(7):2406–2413Google Scholar
  10. 10.
    Jabłońska E, Kiluk M, Markiewicz W et al (2001) TNF-alpha, IL-6 and their soluble receptor serum levels and secretion by neutrophils in cancer patients. Arch Immunol Ther Exp 49(1):63–69Google Scholar
  11. 11.
    Schaider H, Oka M, Bogenrieder T et al (2003) Differential response of primary and metastatic melanomas to neutrophils attracted by IL-8. Int J Cancer 103(3):335–343CrossRefGoogle Scholar
  12. 12.
    Faria SS, Fernandes PC Jr, Silva MJB et al (2016) The neutrophil-to-lymphocyte ratio: a narrative review. Ecancermedicalscience 10:702Google Scholar
  13. 13.
    Templeton AJ, Ace O, McNamara MG et al (2014) Prognostic role of platelet to lymphocyte ratio in solid tumors: a systematic review and meta-analysis. Cancer Epidemiol Biomarkers Prev 23(7):1204–1212CrossRefGoogle Scholar
  14. 14.
    Nishijima TF, Muss HB, Shachar SS et al (2015) Prognostic value of lymphocyte-to-monocyte ratio in patients with solid tumors: a systematic review and meta-analysis. Cancer Treat Rev 41(10):971–978CrossRefGoogle Scholar
  15. 15.
    Kanatsios S, Melanoma Project M, Suen LW et al (2018) Neutrophil to lymphocyte ratio is an independent predictor of outcome for patients undergoing definitive resection for stage IV melanoma. J Surg Oncol 118(6):915–921CrossRefGoogle Scholar
  16. 16.
    Yang R, Chang Q, Meng X et al (2018) Prognostic value of Systemic immune-inflammation index in cancer: a meta-analysis. J Cancer 9(18):3295–3302CrossRefGoogle Scholar
  17. 17.
    Feng Z, Wen H, Ju X et al (2018) The preoperative prognostic nutritional index is a predictive and prognostic factor of high-grade serous ovarian cancer. BMC Cancer 18(1):883CrossRefGoogle Scholar
  18. 18.
    Onodera T, Goseki N, Kosaki G (1984) Prognostic nutritional index in gastrointestinal surgery of malnourished cancer patients. Nihon Geka Gakkai Zasshi 85(9):1001–1005Google Scholar
  19. 19.
    Ikeya T, Shibutani M, Maeda K et al (2015) Maintenance of the nutritional prognostic index predicts survival in patients with unresectable metastatic colorectal cancer. J Cancer Res Clin Oncol 141(2):307–313CrossRefGoogle Scholar
  20. 20.
    Migita K, Takayama T, Saeki K et al (2013) The prognostic nutritional index predicts long-term outcomes of gastric cancer patients independent of tumor stage. Ann Surg Oncol 20(8):2647–2654CrossRefGoogle Scholar
  21. 21.
    Yao ZH, Tian GY, Wan YY et al (2013) Prognostic nutritional index predicts outcomes of malignant pleural mesothelioma. J Cancer Res Clin Oncol 139(12):2117–2123CrossRefGoogle Scholar
  22. 22.
    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):1439–1445CrossRefGoogle Scholar
  23. 23.
    Wang DS, Luo HY, Qiu MZ et al (2012) Comparison of the prognostic values of various inflammation based factors in patients with pancreatic cancer. Med Oncol 29(5):3092–3100CrossRefGoogle Scholar
  24. 24.
    Abbas O, Miller DD, Bhawan J (2014) Cutaneous malignant melanoma: update on diagnostic and prognostic biomarkers. Am J Dermatopathol 36(5):363–379CrossRefGoogle Scholar
  25. 25.
    Atkinson V (2017) Recent advances in malignant melanoma. Intern Med J 47(10):1114–1121CrossRefGoogle Scholar
  26. 26.
    Gorantla VC, Kirkwood JM (2014) State of melanoma: an historic overview of a field in transition. Hematol Oncol Clin N Am 28(3):415–435CrossRefGoogle Scholar
  27. 27.
    Homsi J, Kashani-Sabet M, Messina JL et al (2005) Cutaneous melanoma: prognostic factors. Cancer Control 12(4):223–229CrossRefGoogle Scholar
  28. 28.
    Weinstein D, Leininger J, Hamby C et al (2014) Diagnostic and prognostic biomarkers in melanoma. J Clin Aesthet Dermatol 7(6):13–24Google Scholar
  29. 29.
    Mantovani A, Allavena P, Sica A et al (2008) Cancer-related inflammation. Nature 454(7203):436–444CrossRefGoogle Scholar
  30. 30.
    Gandini S, Ferrucci PF, Botteri E et al (2016) Prognostic significance of hematological profiles in melanoma patients. Int J Cancer 139(7):1618–1625CrossRefGoogle Scholar
  31. 31.
    Lino-Silva LS, Salcedo-Hernández RA, García-Pérez L et al (2017) Basal neutrophil-to-lymphocyte ratio is associated with overall survival in melanoma. Melanoma Res 27(2):140–144CrossRefGoogle Scholar
  32. 32.
    Wade RG, Robinson AV, Lo MC et al (2018) Baseline neutrophil–lymphocyte and platelet–lymphocyte ratios as biomarkers of survival in cutaneous melanoma: a multicenter cohort study. Ann Surg Oncol 25(11):3341–3349CrossRefGoogle Scholar
  33. 33.
    Ding Y, Zhang S, Qiao J (2018) Prognostic value of neutrophil-to-lymphocyte ratio in melanoma: evidence from a PRISMA-compliant meta-analysis. Medicine 97(30):11446 (Baltimore) CrossRefGoogle Scholar
  34. 34.
    Tomita M, Ayabe T, Maeda R et al (2018) Systemic immune-inflammation index predicts survival of patients after curative resection for non-small cell lung cancer. Vivo 32(3):663–667Google Scholar
  35. 35.
    Hong X, Cui B, Wang M et al (2015) Systemic immune-inflammation index, based on platelet counts and neutrophil–lymphocyte ratio, is useful for predicting prognosis in small cell lung cancer. Tohoku J Exp Med 236(4):297–304CrossRefGoogle Scholar
  36. 36.
    Geng Y, Shao Y, Zhu D et al (2016) Systemic immune-inflammation index predicts prognosis of patients with esophageal squamous cell carcinoma: a propensity score-matched analysis. Sci Rep 6:39482CrossRefGoogle Scholar
  37. 37.
    Huang L, Liu S, Lei Y et al (2016) Systemic immune-inflammation index, thymidine phosphorylase and survival of localized gastric cancer patients after curative resection. Oncotarget 7(28):44185–44193Google Scholar
  38. 38.
    Zhong JH, Huang DH, Chen ZY (2017) Prognostic role of systemic immune-inflammation index in solid tumors: a systematic review and meta-analysis. Oncotarget 8(43):75381–75388Google Scholar
  39. 39.
    Yu J, Wu X, Yu H et al (2017) Systemic immune-inflammation index and circulating T-cell immune index predict outcomes in high-risk acral melanoma patients treated with high-dose interferon. Transl Oncol 10(5):719–725CrossRefGoogle Scholar
  40. 40.
    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(1):92–97CrossRefGoogle Scholar
  41. 41.
    Yang Y, Gao P, Song Y et al (2016) The prognostic nutritional index is a predictive indicator of prognosis and postoperative complications in gastric cancer: a meta-analysis. Eur J Surg Oncol 42(8):1176–1182CrossRefGoogle Scholar
  42. 42.
    Don BR, Kaysen G (2004) Poor nutritional status and inflammation: serum albumin: relationship to inflammation and nutrition. Semin Dial 17(6):432–437CrossRefGoogle Scholar
  43. 43.
    Crumley AB, Stuart RC, McKernan M et al (2010) Is hypoalbuminemia an independent prognostic factor in patients with gastric cancer? World J Surg 34(10):2393–2398CrossRefGoogle Scholar
  44. 44.
    Nazha B, Moussaly E, Zaarour M et al (2015) Hypoalbuminemia in colorectal cancer prognosis: nutritional marker or inflammatory surrogate? World J Gastrointest Surg 7(12):370–377CrossRefGoogle Scholar
  45. 45.
    Wu ES, Oduyebo T, Cobb LP et al (2016) Lymphopenia and its association with survival in patients with locally advanced cervical cancer. Gynecol Oncol 140(1):76–82CrossRefGoogle Scholar
  46. 46.
    Ray-Coquard I, Cropet C, Van Glabbeke M et al (2009) Lymphopenia as a prognostic factor for overall survival in advanced carcinomas, sarcomas, and lymphomas. Cancer Res 69(13):5383–5391CrossRefGoogle Scholar
  47. 47.
    Sun K, Chen S, Xu J et al (2014) The prognostic significance of the prognostic nutritional index in cancer: a systematic review and meta-analysis. J Cancer Res Clin Oncol 140(9):1537–1549CrossRefGoogle Scholar

Copyright information

© Japan Society of Clinical Oncology 2019

Authors and Affiliations

  1. 1.Department of Medical OncologyAtaturk University Faculty of MedicineYakutiyeTurkey
  2. 2.Department of DermatologyKatip Çelebi University Ataturk Education and Research HospitalİzmirTurkey

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