International Urology and Nephrology

, Volume 46, Issue 7, pp 1317–1323 | Cite as

Scoring system for prediction of lymph node metastasis in radical cystectomy cohort

  • Miroslav M. StojadinovićEmail author
  • Rade Prelević
  • Arso Vukićević
Urology - Original Paper



The objective of the study was to assess whether pretreatment clinical parameters combined with computed tomography can improve the prediction of lymph node metastasis in patients with bladder cancer treated with radical cystectomy.

Patients and methods

In a single-center retrospective study, demographic and clinicopathological information (initial transurethral resection [grade, stage, multiplicity of tumors, lymphovascular invasion], hydronephrosis, abdominal and pelvic computed tomography) and the presence of lymph node disease on final pathology of 183 patients with bladder cancer undergoing radical cystectomy and pelvic lymph node dissection were reviewed. Logistic regression and bootstrap methods were used to create an integer score for estimating the risk of positive lymph nodes. Various measures for predictive ability and clinical utility were determined.


On pathological examination, 59.6 % of patients had positive lymph nodes. In a multivariable analysis, status lymph nodes on computed tomography and hydronephrosis were the most strongly associated predictors. The resultant total possible score ranged from 0 to 10, with a cut-off value of >4 points. The area under the receiver operating characteristic curve was 0.806. Relative integrated discrimination improvement was 14.3 %. In the decision curve analysis, the model provided net benefit throughout the entire range of threshold probabilities. However, the final model was roughly equivalent to using the clinical exam.


The pre-cystectomy scoring system improved the prediction of lymph node status in patients with bladder cancer. Our model represented a user-friendly staging aid, but a large multi-center study should be performed before widespread implementation.


Bladder cancer Lymph nodes metastasis Prognostic model Scoring system 



Area under the receiver operating characteristic curve


Bladder cancer


Confidential interval


Computed tomography


Extended pelvic LND


Integrated discrimination improvement


The integrated 1-specificity


The integrated sensitivity


Lymph node


Lymph node dissection


Lymphovascular invasion


Magnetic resonance imaging




Neoadjuvant chemotherapy


Negative predictive value


Net reclassification improvement


Odds ratios


Lymph node metastases


The receiver operating characteristic curve


Positive predictive value


Transurethral resection


Transurethral resection of bladder tumor



The authors were financially supported through a research grant N0175014 of the Ministry of Science and Technological Development of Serbia. The authors thank the Ministry for this support.

Conflict of interest



  1. 1.
    Karl A, Carroll PR, Gschwend JE et al (2009) The impact of lymphadenectomy and lymph node metastasis on the outcomes of radical cystectomy for bladder cancer. Eur Urol 55:826–835PubMedCrossRefGoogle Scholar
  2. 2.
    Vikram R, Sandler CM, Ng CS (2009) Imaging and staging of transitional cell carcinoma: part 1, lower urinary tract. Am J Roentgenol 192:1481–1487CrossRefGoogle Scholar
  3. 3.
    Youssef RF, Raj GV (2011) Lymphadenectomy in management of invasive bladder cancer. Int J Surg Oncol, 758189. Published online: Jun 16. doi: 10.1155/2011/758189
  4. 4.
    Kim JK, Park SY, Ahn HJ, Kim CS, Cho KS (2004) Bladder cancer: analysis of multi-detector row helical CT enhancement pattern and accuracy in tumor detection and perivesical staging. Radiology 231:725–731PubMedCrossRefGoogle Scholar
  5. 5.
    Xie HY, Zhu Y, Yao XD et al (2012) Development of a nomogram to predict non-organ-confined bladder urothelial cancer before radical cystectomy. Int Urol Nephrol 44:1711–1719PubMedCrossRefGoogle Scholar
  6. 6.
    Green DA, Rink M, Hansen J, et al (2012) Accurate preoperative prediction of non-organ-confined bladder urothelial carcinoma at cystectomy. BJU Int. Published online: Jul 13. doi: 10.1111/j.1464-410X.2012.11370.x
  7. 7.
    Karakiewicz PI, Shariat SF, Palapattu GS et al (2006) Precystectomy nomogram for prediction of advanced bladder cancer stage. Eur Urol 50:1254–1262PubMedCrossRefGoogle Scholar
  8. 8.
    Ahmadi H, Mitra AP, Abdelsayed GA, et al (2012) Principal component analysis based pre-cystectomy model to predict pathological stage in patients with clinical organ-confined bladder cancer. BJU Int. Published online: Oct 4. doi: 10.1111/j.1464-410X.2012.11502.x
  9. 9.
    Margel D, Harel A, Yossepowitch O, Baniel J (2009) A novel algorithm to improve pathologic stage prediction of clinically organ-confined muscle-invasive bladder cancer. Cancer 115:1459–1464PubMedCrossRefGoogle Scholar
  10. 10.
    Mitra AP, Skinner EC, Miranda G, Daneshmand S (2013) A precystectomy decision model to predict pathological upstaging and oncological outcomes in clinical stage T2 bladder cancer. BJU Int 111:240–248PubMedCrossRefGoogle Scholar
  11. 11.
    Rink M, Hansen J, Cha EK et al (2013) Outcomes and prognostic factors in patients with a single lymph node metastasis at time of radical cystectomy. BJU Int 111:74–84PubMedCrossRefGoogle Scholar
  12. 12.
    McLaughlin S, Shephard J, Wallen E, Maygarden S, Carson CC, Pruthi RS (2007) Comparison of the clinical and pathologic staging in patients undergoing radical cystectomy for bladder cancer. Int Braz J Urol 33:25–31PubMedCrossRefGoogle Scholar
  13. 13.
    Haleblian GE, Skinner EC, Dickinson MG, Lieskovsky G, Boyd SD, Skinner DG (1998) Hydronephrosis as a prognostic indicator in bladder cancer patients. J Urol 160:2011–2014PubMedCrossRefGoogle Scholar
  14. 14.
    Sobin LH, Gospodariwicz M, Wittekind C (1973) TNM classification of malignant tumors. UICC international union against cancer, 7 edn. Wiley, London, 2009Google Scholar
  15. 15.
    Mostofi FK, Sobin LH, Torloni H (1973) Histological typing of urinary bladder tumours. World Health Organization, GenevaGoogle Scholar
  16. 16.
    Quek ML, Stein JP, Nichols PW et al (2005) Prognostic significance of lymphovascular invasion of bladder cancer treated with radical cystectomy. J Urol 174:103–106PubMedCrossRefGoogle Scholar
  17. 17.
    Eisenhauer EA, Therasse P, Bogaerts J et al (2009) New response evaluation criteria in solid tumours: revised RECIST guideline (version 1.1). Eur J Cancer 45:228–247PubMedCrossRefGoogle Scholar
  18. 18.
    Altman D, Royston P (2000) What do we mean by validating a prognostic model? Stat Med 19:453–473PubMedCrossRefGoogle Scholar
  19. 19.
    Pickering JW, Endre ZH (2012) New metrics for assessing diagnostic potential of candidate biomarkers. Clin J Am Soc Nephrol 7:1355–1364PubMedCrossRefGoogle Scholar
  20. 20.
    Vickers AJ, Elkin EB (2006) Decision curve analysis: a novel method for evaluating prediction models. Med Decis Making 26:565–574PubMedCentralPubMedCrossRefGoogle Scholar
  21. 21.
    Turker P, Bostrom PJ, Wroclawski ML et al (2012) Upstaging of urothelial cancer at the time of radical cystectomy: factors associated with upstaging and its effect on outcome. BJU Int 110:804–811PubMedCrossRefGoogle Scholar
  22. 22.
    Matsumoto K, Shariat SF, Casella R, Wheeler TM, Slawin KM, Lerner SP (2003) Preoperative plasma soluble E-cadherin predicts metastases to lymph nodes and prognosis in patients undergoing radical cystectomy. J Urol 170:2248–2252PubMedCrossRefGoogle Scholar
  23. 23.
    Suzuki K, Morita T, Tokue A (2005) Vascular endothelial growth factor-C (VEGF-C) expression predicts lymph node metastasis of transitional cell carcinoma of the bladder. Int J Urol 12:152–158PubMedCrossRefGoogle Scholar
  24. 24.
    Smith SC, Baras AS, Dancik G et al (2011) A 20-gene model for molecular nodal staging of bladder cancer: development and prospective assessment. Lancet Oncol 12:137–143PubMedCentralPubMedCrossRefGoogle Scholar
  25. 25.
    Abdel-Latif M, Abol-Enein H, El-Baz M, Ghoneim MA (2004) Nodal involvement in bladder cancer cases treated with radical cystectomy: incidence and prognosis. J Urol 172:85–89PubMedCrossRefGoogle Scholar
  26. 26.
    Stimson CJ, Cookson MS, Barocas DA et al (2010) Preoperative hydronephrosis predicts extravesical and node positive disease in patients undergoing cystectomy for bladder cancer. J Urol 183:1732–1737PubMedCrossRefGoogle Scholar
  27. 27.
    May M, Burger M, Brookman-May S et al (2011) Validation of pre-cystectomy nomograms for the prediction of locally advanced urothelial bladder cancer in a multicentre study: are we able to adequately predict locally advanced tumour stages before surgery? Der Urol Ausg A 50:706–713CrossRefGoogle Scholar
  28. 28.
    Niegisch G, Lorch A, Droller MJ, Lavery HJ, Stensland KD, Albers P (2013) Neoadjuvant chemotherapy in patients with muscle-invasive bladder cancer: which patients benefit? Eur Urol. Published online: Jun 12. doi: 10.1016/j.eururo.2013.06.002
  29. 29.
    Ploeg M, Kiemeney LA, Smits GA et al (2012) Discrepancy between clinical staging through bimanual palpation and pathological staging after cystectomy. Urol Oncol 30:247–251PubMedCrossRefGoogle Scholar
  30. 30.
    Abol-Enein H, El-Baz M, Abd El-Hameed MA, Abdel-Latif M, Ghoneim MA (2004) Lymph node involvement in patients with bladder cancer treated with radical cystectomy: a patho-anatomical study–a single center experience. J Urol 172:1818–1821PubMedCrossRefGoogle Scholar
  31. 31.
    Shariat SF, Ehdaie B, Rink M et al (2012) Clinical nodal staging scores for bladder cancer: a proposal for preoperative risk assessment. Eur Urol 61:237–242PubMedCrossRefGoogle Scholar
  32. 32.
    Shariat SF, Rink M, Ehdaie B et al (2013) Pathologic nodal staging score for bladder cancer: a decision tool for adjuvant therapy after radical cystectomy. Eur Urol 63:371–378PubMedCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media Dordrecht 2014

Authors and Affiliations

  • Miroslav M. Stojadinović
    • 1
    Email author
  • Rade Prelević
    • 2
  • Arso Vukićević
    • 3
  1. 1.Department of Urology, Clinic of Urology and NephrologyClinical Centre “Kragujevac”KragujevacSerbia
  2. 2.Clinic of UrologyMilitary Medical AcademyBelgradeSerbia
  3. 3.Faculty of EngineeringUniversity of KragujevacKragujevacSerbia

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