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Uric acid levels in blood are associated with clinical outcome in soft-tissue sarcoma patients

  • Joanna Szkandera , Armin Gerger , Bernadette Liegl-Atzwanger , Michael Stotz , Hellmut Samonigg , Ferdinand Ploner , Tatjana Stojakovic , Thomas Gary , Andreas Leithner and Martin Pichler EMAIL logo
Published/Copyright: October 15, 2014

Abstract

Background: Recent evidence indicates toward a role of uric acid (UA) as a potential antioxidant. Elevated UA levels were shown to be associated with better survival in various malignancies. The aim of the present study was to evaluate the prognostic relevance of pre-operative UA levels on cancer-specific survival (CSS) in soft-tissue sarcoma (STS) patients who underwent curative surgical resection.

Methods: Three hundred and fifty-seven patients with STS were included in the study. Pre-operative serum UA level was measured using an enzymatic colorimetric assay. The effect of UA levels on CSS was analyzed using Kaplan-Meier curves. To further evaluate the prognostic impact of UA levels, univariate and multivariate Cox proportional models were calculated.

Results: Among the 357 STS patients, cancer-related deaths occurred in 20 (24.7%) of 81 patients with a serum UA level <279.6 µmol/L and in 36 (13%) of 276 patients with a UA level ≥279.6 µmol/L. In univariate analysis, elevated UA levels were significantly associated with increased CSS in STS patients [hazard ratio (HR) 0.44, 95% confidence interval (CI) 0.26–0.77, p=0.004]. Furthermore, elevated UA levels remain a significant factor for better CCS in multivariate analysis (HR 0.42, 95% CI 0.23–0.75, p=0.003).

Conclusions: Our study is the first one to demonstrate that higher UA levels are associated with positive clinical outcome in STS patients. UA levels are a simple and cost-effective test for the assessment of the prognosis of STS patients.


Corresponding author: Martin Pichler, MD, Division of Clinical Oncology, Department of Medicine, Medical University of Graz, Auenbruggerplatz 15, 8036 Graz, Austria, Phone: +43-316-385-81320, Fax: +43-316-385-13355, E-mail:

References

1. Cormier JN, Pollock RE. Soft tissue sarcomas. CA Cancer J Clin 2004;54:94–109.10.3322/canjclin.54.2.94Search in Google Scholar

2. Siegel R, Naishadham D, Jemal A. Cancer statistics, 2012. CA Cancer J Clin 2012;62:10–29.10.3322/caac.20138Search in Google Scholar

3. Scaife CL, Pisters PW. Combined-modality treatment of localized soft tissue sarcomas of the extremities. Surg Oncol Clin N Am 2003;12:355–68.10.1016/S1055-3207(03)00003-6Search in Google Scholar

4. Szkandera J, Gerger A, Liegl-Atzwanger B, Absenger G, Stotz M, Friesenbichler J, et al. The lymphocyte/monocyte ratio predicts poor clinical outcome and improves the predictive accuracy in patients with soft tissue sarcomas. Br J Cancer 2014;110:435–40.10.1002/ijc.28677Search in Google Scholar PubMed

5. Szkandera J, Gerger A, Liegl-Atzwanger B, Absenger G, Stotz M, Samonigg H, et al. Validation of the prognostic relevance of plasma C-reactive protein levels in soft-tissue sarcoma patients. Br J Cancer 2013;109:2316–22.10.1038/bjc.2013.595Search in Google Scholar PubMed PubMed Central

6. Kattan MW, Leung DH, Brennan MF. Postoperative nomogram for 12-year sarcoma-specific death. J Clin Oncol 2002;20:791–6.10.1200/JCO.2002.20.3.791Search in Google Scholar PubMed

7. Yamauchi T, Negoro E, Lee S, Takai M, Matsuda Y, Takagi K, et al. A high serum uric acid level is associated with poor prognosis in patients with acute myeloid leukemia. Anticancer Res 2013;33:3947–51.Search in Google Scholar

8. Shin HS, Lee HR, Lee DC, Shim JY, Cho KH, Suh SY. Uric acid as a prognostic factor for survival time: a prospective cohort study of terminally ill cancer patients. J Pain Symptom Manage 2006;31:493–501.10.1016/j.jpainsymman.2005.11.014Search in Google Scholar PubMed

9. Dziaman T, Banaszkiewicz Z, Roszkowski K, Gackowski D, Wisniewska E, Rozalski R, et al. 8-Oxo-7,8-dihydroguanine and uric acid as efficient predictors of survival in colon cancer patients. Int J Cancer 2014;134:376–83.10.1002/ijc.28374Search in Google Scholar PubMed

10. Fletcher CD, Bridge JA, Hogendoorn P, Mertens F, editors. WHO classification of tumours of soft tissue and bone, 4th ed., vol. 5. Lyon: IARC Press, 2013.Search in Google Scholar

11. Coindre JM. Grading of soft tissue sarcomas: review and update. Arch Pathol Lab Med 2006;130:1448–53.10.5858/2006-130-1448-GOSTSRSearch in Google Scholar PubMed

12. Liegl-Atzwanger B, Hofmann G, Leithner A, Beham A. Undifferentiated high-grade pleomorphic sarcoma (UHPS): diagnostic criteria, differential diagnosis, and treatment. An attempt to erasure the misnomer MFH. Eur Surg 2009;41:143–9.10.1007/s10353-009-0474-9Search in Google Scholar

13. Absenger G, Szkandera J, Stotz M, Postlmayr U, Pichler M, Ress AL, et al. A derived neutrophil to lymphocyte ratio predicts clinical outcome in stage II and III colon cancer patients. Br J Cancer 2013;109:395–400.10.1038/bjc.2013.346Search in Google Scholar

14. Strasak AM, Lang S, Kneib T, Brant LJ, Klenk J, Hilbe W, et al. Use of penalized splines in extended Cox-type additive hazard regression to flexibly estimate the effect of time-varying serum uric acid on risk of cancer incidence: a prospective, population-based study in 78,850 men. Ann Epidemiol 2009;19:15–24.10.1016/j.annepidem.2008.08.009Search in Google Scholar

15. Chaudhary K, Malhotra K, Sowers J, Aroor A. Uric acid – key ingredient in the recipe for cardiorenal metabolic syndrome. Cardiorenal Med 2013;3:208–20.10.1159/000355405Search in Google Scholar

16. Shi Y, Evans JE, Rock KL. Molecular identification of a danger signal that alerts the immune system to dying cells. Nature 2003;425:516–21.10.1038/nature01991Search in Google Scholar

17. Ames BN, Cathcart R, Schwiers E, Hochstein P. Uric acid provides an antioxidant defense in humans against oxidant- and radical-caused aging and cancer: a hypothesis. Proc Natl Acad Sci USA 1981;78:6858–62.10.1073/pnas.78.11.6858Search in Google Scholar

18. Jackson AL, Loeb LA. The contribution of endogenous sources of DNA damage to the multiple mutations in cancer. Mutat Res 2001;477:7–21.10.1016/S0027-5107(01)00091-4Search in Google Scholar

19. Storz P. Reactive oxygen species in tumor progression. Front Biosci 2005;10:1881–96.10.2741/1667Search in Google Scholar PubMed

20. Troppan K, Deutsch A, Gerger A, Stojakovic T, Beham-Schmid C, Wenzl K, et al. The derived neutrophil to lymphocyte ratio is an independent prognostic factor in patients with diffuse large B-cell lymphoma. Br J Cancer 2014;110:369–74.10.1038/bjc.2013.763Search in Google Scholar PubMed PubMed Central

Received: 2014-5-6
Accepted: 2014-9-15
Published Online: 2014-10-15
Published in Print: 2015-2-1

©2015 by De Gruyter

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