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A high Glasgow prognostic score (GPS) or modified Glasgow prognostic score (mGPS) predicts poor prognosis in gynecologic cancers: a systematic review and meta-analysis

  • Gynecologic Oncology
  • Published:
Archives of Gynecology and Obstetrics Aims and scope Submit manuscript

Abstract

Purpose

The Glasgow Prognostic Score or modified Glasgow Prognostic Score (GPS/mGPS), a novel inflammatory indicator, which acts as a prognostic predictor in various cancers. However, these results are still controversial. In this meta-analysis, we aimed to investigate the prognostic role of GPS/mGPS in patients with gynecologic cancers.

Methods

We explored eligible studies by searching the databases PubMed, the Cochrane Library, EMBASE, and Web of Science. The hazard ratio (HR) and odds ratios (OR) with 95% confidence intervals (CIs) were extracted to investigate the correlation between GPS/mGPS and overall survival (OS) and progression-free survival (PFS). Additionally, we performed subgroup analyses to detect the potential heterogeneity in our study.

Results

11 studies involving 2830 patients were enrolled in this meta-analysis. The results revealed that a high GPS was significantly related to a shorter OS (pooled HR = 1.94; 95% CI = 1.54−2.43; P < 0.001) and PFS (pooled HR = 1.92; 95% CI = 1.56–2.35; P < 0.001) in patients with gynecologic cancers. Moreover, mGPS also predicted poor OS (pooled HR = 1.67; 95% CI = 1.41−1.96; P < 0.001) and PFS (pooled HR = 1.73; 95% CI = 1.47–2.04; P < 0.001) in gynecologic cancers patients.

Conclusion

A higher GPS/mGPS is correlated with poor survival outcomes in patients with gynecologic cancers. Pretreatment GPS/mGPS is a valid prognostic predictor in gynecologic cancers.

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References

  1. Siegel RL, Miller KD, Jemal A (2018) Cancer statistics. CA Cancer J Clin 68(1):7–30. https://doi.org/10.3322/caac.21442

    Article  PubMed  Google Scholar 

  2. Torre LA, Bray F, Siegel RL, Ferlay J, Lortet-Tieulent J, Jemal A (2012) Global cancer statistics. CA Cancer J Clin 65(2):87–108. https://doi.org/10.3322/caac.21262

    Article  Google Scholar 

  3. Chen W, Zheng R, Baade PD, Zhang S, Zeng H, Bray F, Jemal A, Yu XQ, He J (2015) Cancer statistics in China. CA Cancer J Clin 66(2):115–132. https://doi.org/10.3322/caac.21338

    Article  CAS  Google Scholar 

  4. McMillan DC (2009) Systemic inflammation, nutritional status and survival in patients with cancer. Curr Opin Clin Nutr Metab Care 12(3):223–226. https://doi.org/10.1097/MCO.0b013e32832a7902

    Article  PubMed  Google Scholar 

  5. Zitvogel L, Pietrocola F, Kroemer G (2017) Nutrition, inflammation and cancer. Nat Immunol 18(8):843–850. https://doi.org/10.1038/ni.3754

    Article  CAS  PubMed  Google Scholar 

  6. Benizri EI, Bereder JM, Rahili A, Bernard JL, Benchimol D (2013) Ascites and malnutrition are predictive factors for incomplete cytoreductive surgery for peritoneal carcinomatosis from gastric cancer. Am J Surg 205(6):668–673. https://doi.org/10.1016/j.amjsurg.2012.06.009

    Article  PubMed  Google Scholar 

  7. Yim GW, Eoh KJ, Kim SW, Nam EJ, Kim YT (2016) Malnutrition identified by the nutritional risk index and poor prognosis in advanced epithelial ovarian carcinoma. Nutr Cancer 68(5):772–779. https://doi.org/10.1080/01635581.2016.1159702

    Article  CAS  PubMed  Google Scholar 

  8. Zhang W, Ye B, Liang W, Ren Y (2017) Preoperative prognostic nutritional index is a powerful predictor of prognosis in patients with stage III ovarian cancer. Sci Rep 7(1):9548. https://doi.org/10.1038/s41598-017-10328-8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Nie D, Gong H, Mao X, Li Z (2019) Systemic immune-inflammation index predicts prognosis in patients with epithelial ovarian cancer: a retrospective study. Gynecol Oncol 152(2):259–264. https://doi.org/10.1016/j.ygyno.2018.11.034

    Article  PubMed  Google Scholar 

  10. Forrest LM, McMillan DC, McArdle CS, Angerson WJ, Dunlop DJ (2004) Comparison of an inflammation-based prognostic score (GPS) with performance status (ECOG) in patients receiving platinum-based chemotherapy for inoperable non-small-cell lung cancer. Br J Cancer 90(9):1704–1706. https://doi.org/10.1038/sj.bjc.6601789

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Proctor MJ, Morrison DS, Talwar D, Balmer SM, O'Reilly DS, Foulis AK, Horgan PG, McMillan DC (2011) An inflammation-based prognostic score (mGPS) predicts cancer survival independent of tumour site: a Glasgow Inflammation Outcome Study. Br J Cancer 104(4):726–734. https://doi.org/10.1038/sj.bjc.6606087

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. Lindenmann J, Fink-Neuboeck N, Taucher V, Pichler M, Posch F, Brcic L, Smolle E, Koter S, Smolle J, Smolle-Juettner FM (2020) Prediction of postoperative clinical outcomes in resected stage I non-small cell lung cancer focusing on the preoperative glasgow prognostic score. Cancers (Basel). https://doi.org/10.3390/cancers12010152

    Article  Google Scholar 

  13. Hsueh SW, Liu KH, Hung CY, Kuo YC, Tsai CY, Hsu JT, Hung YS, Tsang NM, Chou WC (2019) Significance of the glasgow prognostic score in predicting the postoperative outcome of patients with stage III gastric cancer. J Clin Med. https://doi.org/10.3390/jcm8091448

    Article  PubMed  PubMed Central  Google Scholar 

  14. Liu Y, He X, Pan J, Chen S, Wang L (2017) Prognostic role of Glasgow prognostic score in patients with colorectal cancer: evidence from population studies. Sci Rep 7(1):6144. https://doi.org/10.1038/s41598-017-06577-2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Polterauer S, Grimm C, Seebacher V, Rahhal J, Tempfer C, Reinthaller A, Hefler L (2010) The inflammation-based Glasgow Prognostic Score predicts survival in patients with cervical cancer. Int J Gynecol Cancer 20(6):1052–1057. https://doi.org/10.1111/IGC.0b013e3181e64bb1

    Article  PubMed  Google Scholar 

  16. Nishida T, Nakamura K, Haraga J, Ogawa C, Kusumoto T, Seki N, Masuyama H, Katayama N, Kanazawa S, Hiramatsu Y (2015) The Glasgow prognostic score determined during concurrent chemoradiotherapy is an independent predictor of survival for cervical cancer. Int J Gynecol Cancer 25(7):1306–1314. https://doi.org/10.1097/IGC.0000000000000485

    Article  PubMed  Google Scholar 

  17. He X, Li JP, Liu XH, Zhang JP, Zeng QY, Chen H, Chen SL (2018) Prognostic value of C-reactive protein/albumin ratio in predicting overall survival of Chinese cervical cancer patients overall survival: comparison among various inflammation based factors. J Cancer 9(10):1877–1884. https://doi.org/10.7150/jca.23320

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  18. Seebacher V, Sturdza A, Bergmeister B, Polterauer S, Grimm C, Reinthaller A, Hilal Z, Aust S (2019) Factors associated with post-relapse survival in patients with recurrent cervical cancer: the value of the inflammation-based Glasgow prognostic score. Arch Gynecol Obstet 299(4):1055–1062. https://doi.org/10.1007/s00404-018-4993-0

    Article  CAS  PubMed  Google Scholar 

  19. Saijo M, Nakamura K, Masuyama H, Ida N, Haruma T, Kusumoto T, Seki N, Hiramatsu Y (2017) Glasgow prognostic score is a prognosis predictor for patients with endometrial cancer. Eur J Obstet Gynecol Reprod Biol 210:355–359. https://doi.org/10.1016/j.ejogrb.2017.01.024

    Article  PubMed  Google Scholar 

  20. Nakamura K, Nakayama K, Minamoto T et al (2018) High preoperative Glasgow prognostic score is a negative prognostic factor for patients with endometrial carcinoma. Mol Clin Oncol 8(3):429–433. https://doi.org/10.3892/mco.2018.1551

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  21. Zhu J, Wang H, Liu CC, Lu Y, Tang H (2016) The Glasgow Prognostic Score (GPS) is a novel prognostic indicator in advanced epithelial ovarian cancer: a multicenter retrospective study. J Cancer Res Clin Oncol 142(11):2339–2345. https://doi.org/10.1007/s00432-016-2228-y

    Article  CAS  PubMed  Google Scholar 

  22. Omichi C, Nakamura K, Haraga J, Masuyama H, Hiramatsu Y (2016) Glasgow prognostic score is an independent marker for poor prognosis with all cases of epithelial ovarian cancer. Cancer Med 5(6):1074–1080. https://doi.org/10.1002/cam4.681

    Article  PubMed  PubMed Central  Google Scholar 

  23. Sharma R, Hook J, Kumar M, Gabra H (2008) Evaluation of an inflammation-based prognostic score in patients with advanced ovarian cancer. Eur J Cancer 44(2):251–256. https://doi.org/10.1016/j.ejca.2007.11.011

    Article  PubMed  Google Scholar 

  24. Roncolato FT, Berton-Rigaud D, O'Connell R et al (2018) Validation of the modified Glasgow prognostic score (mGPS) in recurrent ovarian cancer (ROC)—Analysis of patients enrolled in the GCIG Symptom Benefit Study (SBS). Gynecol Oncol 148(1):36–41. https://doi.org/10.1016/j.ygyno.2017.10.019

    Article  PubMed  Google Scholar 

  25. Xiao Y, Ren YK, Cheng HJ, Wang L, Luo SX (2015) Modified Glasgow prognostic score is an independent prognostic factor in patients with cervical cancer undergoing chemoradiotherapy. Int J Clin Exp Pathol 8(5):5273–5281

    CAS  PubMed  PubMed Central  Google Scholar 

  26. Liu Y, Chen S, Zheng C, Ding M, Zhang L, Wang L, Xie M, Zhou J (2017) The prognostic value of the preoperative c-reactive protein/albumin ratio in ovarian cancer. BMC Cancer 17(1):285. https://doi.org/10.1186/s12885-017-3220-x

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  27. Liang M, Holzapfel M, Chang H, Lester J, Li A, Cass I, Rimel BJ, Karlan B, Leuchter R, Walsh C (2016) Glasgow prognostic score associated with lower rates of R0 cytoreduction in women with stage iii serous ovarian cancer. Gynecol Oncol 143(1):219–219. https://doi.org/10.1016/j.ygyno.2016.08.304

    Article  Google Scholar 

  28. Moher D, Liberati A, Tetzlaff J, Altman DG (2009) Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. BMJ 339:b2535. https://doi.org/10.1136/bmj.b2535

    Article  PubMed  PubMed Central  Google Scholar 

  29. Stroup DF, Berlin JA, Morton SC, Olkin I, Williamson GD, Rennie D, Moher D, Becker BJ, Sipe TA, Thacker SB (2000) Metaanalysis of observational studies in epidemiology a proposal for reporting. Metaanalysis Of Observational Studies in Epidemiology (MOOSE) group. JAMA 283(15):2008–2012. https://doi.org/10.1001/jama.283.15.2008

    Article  CAS  PubMed  Google Scholar 

  30. Stang A (2010) Critical evaluation of the Newcastle-Ottawa scale for the assessment of the quality of nonrandomized studies in meta-analyses. Eur J Epidemiol 25(9):603–605. https://doi.org/10.1007/s10654-010-9491-z

    Article  PubMed  Google Scholar 

  31. Diakos CI, Charles KA, McMillan DC, Clarke SJ (2014) Cancer-related inflammation and treatment effectiveness. Lancet Oncol 15(11):e493–503. https://doi.org/10.1016/S1470-2045(14)70263-3

    Article  PubMed  Google Scholar 

  32. Marnell L, Mold C, Du Clos TW (2005) C-reactive protein: ligands, receptors and role in inflammation. Clin Immunol 117(2):104–111. https://doi.org/10.1016/j.clim.2005.08.004

    Article  CAS  PubMed  Google Scholar 

  33. Toriola AT, Grankvist K, Agborsangaya CB, Lukanova A, Lehtinen M, Surcel HM (2011) Changes in pre-diagnostic serum C-reactive protein concentrations and ovarian cancer risk: a longitudinal study. Ann Oncol 22(8):1916–1921. https://doi.org/10.1093/annonc/mdq694

    Article  CAS  PubMed  Google Scholar 

  34. Peres LC, Mallen AR, Townsend MK et al (2019) High levels of C-Reactive protein are associated with an increased risk of ovarian cancer: results from the ovarian cancer cohort consortium. Cancer Res 79(20):5442–5451. https://doi.org/10.1158/0008-5472.CAN-19-1554

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  35. Roxburgh CS, McMillan DC (2010) Role of systemic inflammatory response in predicting survival in patients with primary operable cancer. Future Oncol 6(1):149–163. https://doi.org/10.2217/fon.09.136

    Article  CAS  PubMed  Google Scholar 

  36. Hefler LA, Concin N, Hofstetter G et al (2008) Serum C-reactive protein as independent prognostic variable in patients with ovarian cancer. Clin Cancer Res 14(3):710–714. https://doi.org/10.1158/1078-0432.CCR-07-1044

    Article  CAS  PubMed  Google Scholar 

  37. Dolan RD, McSorley ST, Horgan PG, Laird B, McMillan DC (2017) The role of the systemic inflammatory response in predicting outcomes in patients with advanced inoperable cancer: systematic review and meta-analysis. Crit Rev Oncol Hematol 116:134–146. https://doi.org/10.1016/j.critrevonc.2017.06.002

    Article  PubMed  Google Scholar 

  38. Kathiresan AS, Brookfield KF, Schuman SI, Lucci JA (2011) Malnutrition as a predictor of poor postoperative outcomes in gynecologic cancer patients. Arch Gynecol Obstet 284(2):445–451. https://doi.org/10.1007/s00404-010-1659-y

    Article  CAS  PubMed  Google Scholar 

  39. McMillan DC, Watson WS, O'Gorman P, Preston T, Scott HR, McArdle CS (2001) Albumin concentrations are primarily determined by the body cell mass and the systemic inflammatory response in cancer patients with weight loss. Nutr Cancer 39(2):210–213. https://doi.org/10.1207/S15327914nc392_8

    Article  CAS  PubMed  Google Scholar 

  40. McMillan DC (2013) The systemic inflammation-based Glasgow prognostic score: a decade of experience in patients with cancer. Cancer Treat Rev 39(5):534–540. https://doi.org/10.1016/j.ctrv.2012.08.003

    Article  PubMed  Google Scholar 

  41. Hu X, Wang Y, Yang WX, Dou WC, Shao YX, Li X (2019) Modified Glasgow prognostic score as a prognostic factor for renal cell carcinomas: a systematic review and meta-analysis. Cancer Manag Res 11:6163–6173. https://doi.org/10.2147/CMAR.S208839

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  42. Egger M, Zellweger-Zähner T, Schneider M, Junker C, Lengeler C, Antes G (1997) Language bias in randomised controlled trials published in English and German. Lancet 350(9074):326–329. https://doi.org/10.1016/S0140-6736(97)02419-7

    Article  CAS  PubMed  Google Scholar 

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Funding

This work was supported by the Doctoral Research Initiation Fund of Affiliated Hospital of Southwest Medical University and the Science and Technology Projects of Luzhou (2019-JYJ-56).

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Authors and Affiliations

  1. Department of Gynecology, Affiliated Hospital of Southwest Medical University, No.8 Section 2, Kangcheng Road, Luzhou, Sichuan, 646000, People’s Republic of China

    Dan Nie, Chunyan Wang, Qian Guo & Xiguang Mao

  2. First Department of Respiratory Medicine, Affiliated Hospital of Southwest Medical University, Luzhou, 646000, People’s Republic of China

    Lingping Zhang

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  1. Dan Nie
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Contributions

DN and XM project development. DN and LZ data collection. DN, LZ, CW, and QG statistical analysis. DN and LZ manuscript writing. All authors have given approval to the final version of the manuscript. DN had primary responsibility for final content.

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Correspondence to Dan Nie.

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Nie, D., Zhang, L., Wang, C. et al. A high Glasgow prognostic score (GPS) or modified Glasgow prognostic score (mGPS) predicts poor prognosis in gynecologic cancers: a systematic review and meta-analysis. Arch Gynecol Obstet 301, 1543–1551 (2020). https://doi.org/10.1007/s00404-020-05581-8

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