Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Review Article
  • Published:

Predictive models and prostate cancer

Nature Clinical Practice Urology volume 5, pages 82–92 (2008)Cite this article

Abstract

Prostate cancer stage migration has changed the diagnostic approach toward men at risk of the disease. For example, sextant needle biopsy of the prostate has been abandoned in favor of biopsies using 10 or more cores. This has in turn affected the stage and grade of newly diagnosed prostate cancers, with a shift toward earlier stage and lower grade. In this manuscript we review novel diagnostic, staging, and preoperative prognostic nomograms that have been developed to accommodate the stage migration. Several novel nomograms have been developed for the purpose of prediction of initial and repeat-biopsy outcomes using 10 or more biopsy cores. Additionally, a novel saturation biopsy nomogram has also been devised. For the purpose of staging, the Partin tables have recently been updated. A series of contemporary nomograms have also been developed to predict extracapsular extension, seminal vesicle invasion, and lymph node invasion. The preoperative nomogram for prediction of biochemical recurrence, introduced by Kattan and colleagues, has been updated and predicts up to 10 years after radical prostatectomy.

Key Points

  • Prediction of prostate cancer at initial and repeat biopsy is best achieved with nomograms based on 10 or more biopsy cores

  • Due to differences in serum PSA level, clinical stage, and biopsy Gleason sum distribution between North American and European men, continent-specific tools should be considered

  • Extracapsular extension, seminal vesicle invasion, and lymph node invasion can be predicted in the most contemporary and highly accurate fashion with the novel European staging nomograms that predominantly rely on diagnoses made with 10 or more core biopsies

  • Currently, biochemical recurrence rates after alternative treatment modalities can be compared with brachytherapy, external beam radiotherapy, and radical prostatectomy nomograms

This is a preview of subscription content, access via your institution

Access options

Buy this article

  • Purchase on Springer Link
  • Instant access to full article PDF
Buy now

Prices may be subject to local taxes which are calculated during checkout

Figure 1: Nomogram predicting prostate cancer on extended initial biopsy (≥10 cores) of the prostate.
Figure 2: Nomograms predicting biopsy outcome in men undergoing 10 or more cores at repeat biopsy.
Figure 3: Nomogram predicting side-specific probability of extracapsular extension (ECE).
Figure 4: Nomogram predicting seminal vesicle invasion.
Figure 5: Nomogram predicting the probability of lymph node invasion in patients undergoing extended pelvic lymphadenectomy.

Similar content being viewed by others

References

  1. Jemal A et al. (2007) Cancer statistics, 2007. CA Cancer J Clin 57: 43–66

    Article  Google Scholar 

  2. Steuber T et al. (2006) Validation of a nomogram for prediction of side specific extracapsular extension at radical prostatectomy. J Urol 175: 939–944

    Article  Google Scholar 

  3. Irish WD et al. (2003) Nomogram for predicting the likelihood of delayed graft function in adult cadaveric renal transplant recipients. J Am Soc Nephrol 14: 2967–2974

    Article  Google Scholar 

  4. Eastham JA et al. (1999) Development of a nomogram that predicts the probability of a positive prostate biopsy in men with an abnormal digital rectal examination and a prostate-specific antigen between 0 and 4 ng/ml. Urology 54: 709–713

    Article  CAS  Google Scholar 

  5. Karakiewicz PI et al. (2005) Development and validation of a nomogram predicting the outcome of prostate biopsy based on patient age, digital rectal examination and serum prostate specific antigen. J Urol 173: 1930–1934

    Article  Google Scholar 

  6. Yanke BV et al. (2006) African-American race is a predictor of prostate cancer detection: incorporation into a pre-biopsy nomogram. BJU Int 98: 783–787

    Article  Google Scholar 

  7. Chun FK et al. (2007) Development and external validation of an extended 10-core biopsy nomogram. Eur Urol 52: 436–445

    Article  Google Scholar 

  8. O'Dowd GJ et al. (2000) Analysis of repeated biopsy results within 1 year after a noncancer diagnosis. Urology 55: 553–559

    Article  CAS  Google Scholar 

  9. Lopez-Corona E et al. (2003) A nomogram for predicting a positive repeat prostate biopsy in patients with a previous negative biopsy session. J Urol 170: 1184–1188

    Article  Google Scholar 

  10. Yanke BV et al. (2005) Validation of a nomogram for predicting positive repeat biopsy for prostate cancer. J Urol 173: 421–424

    Article  Google Scholar 

  11. Chun FK et al. (2007) Development and external validation of an extended repeat biopsy nomogram. J Urol 177: 510–515

    Article  Google Scholar 

  12. Patel AR et al. (2004) Parasagittal biopsies add minimal information in repeat saturation prostate biopsy. Urology 63: 87–89

    Article  Google Scholar 

  13. Rabets JC et al. (2004) Prostate cancer detection with office based saturation biopsy in a repeat biopsy population. J Urol 172: 94–97

    Article  Google Scholar 

  14. Stewart CS et al. (2001) Prostate cancer diagnosis using a saturation needle biopsy technique after previous negative sextant biopsies. J Urol 166: 86–91

    Article  CAS  Google Scholar 

  15. Borboroglu PG et al. (2000) Extensive repeat transrectal ultrasound guided prostate biopsy in patients with previous benign sextant biopsies. J Urol 163: 158–162

    Article  CAS  Google Scholar 

  16. Walz J et al. (2006) High incidence of prostate cancer detected by saturation biopsy after previous negative biopsy series. Eur Urol 50: 498–505

    Article  Google Scholar 

  17. Fleshner N et al. (2002) Role of “saturation biopsy” in the detection of prostate cancer among difficult diagnostic cases. Urology 60: 93–97

    Article  Google Scholar 

  18. Partin AW et al. (1997) Combination of prostate-specific antigen, clinical stage, and Gleason score to predict pathological stage of localized prostate cancer. A multi-institutional update. JAMA 277: 1445–1451

    Article  CAS  Google Scholar 

  19. Partin AW et al. (2001) Contemporary update of prostate cancer staging nomograms (Partin tables) for the new millennium. Urology 58: 843–848

    Article  CAS  Google Scholar 

  20. Makarov DV et al. (2007) Updated nomogram to predict pathologic stage of prostate cancer given prostate-specific antigen level, clinical stage, and biopsy Gleason score (Partin tables) based on cases from 2000 to 2005. Urology 69: 1095–1101

    Article  Google Scholar 

  21. Graefen M et al. (2001) A validated strategy for side specific prediction of organ confined prostate cancer: a tool to select for nerve sparing radical prostatectomy. J Urol 165: 857–863

    Article  CAS  Google Scholar 

  22. Ohori M et al. (2004) Predicting the presence and side of extracapsular extension: a nomogram for staging prostate cancer. J Urol 171: 1844–1849

    Article  Google Scholar 

  23. Koh H et al. (2003) A nomogram to predict seminal vesicle invasion by the extent and location of cancer in systematic biopsy results. J Urol 170: 1203–1208

    Article  Google Scholar 

  24. Gallina A et al. (2007) Development and split-sample validation of a nomogram predicting the probability of seminal vesicle invasion at radical prostatectomy. Eur Urol 52: 98–105

    Article  Google Scholar 

  25. Hutterer GC et al. (2007) The evolution of staging of lymph node metastases in clinically localized prostate cancer. EAU-EBU Update Series 5: 153–162

    Article  Google Scholar 

  26. Cagiannos I et al. (2003) A preoperative nomogram identifying decreased risk of positive pelvic lymph nodes in patients with prostate cancer. J Urol 170: 1798–1803

    Article  Google Scholar 

  27. Briganti A et al. (2007) Critical assessment of ideal nodal yield at pelvic lymphadenectomy to accurately diagnose prostate cancer nodal metastasis in patients undergoing radical retropubic prostatectomy. Urology 69: 147–151

    Article  Google Scholar 

  28. Briganti A et al. (2006) Validation of a nomogram predicting the probability of lymph node invasion based on the extent of pelvic lymphadenectomy in patients with clinically localized prostate cancer. BJU Int 98: 788–793

    Article  Google Scholar 

  29. DiMarco DS et al. (2005) The extent of lymphadenectomy for pTXNO prostate cancer does not affect prostate cancer outcome in the prostate specific antigen era. J Urol 173: 1121–1125

    Article  Google Scholar 

  30. Briganti A et al. (2006) Validation of a nomogram predicting the probability of lymph node invasion among patients undergoing radical prostatectomy and an extended pelvic lymphadenectomy. Eur Urol 49: 1019–1026

    Article  Google Scholar 

  31. Briganti A et al. (2007) A nomogram for staging of exclusive nonobturator lymph node metastases in men with localized prostate cancer. Eur Urol 51: 112–119

    Article  Google Scholar 

  32. Chun FK et al. (2006) Significant upgrading affects a third of men diagnosed with prostate cancer: predictive nomogram and internal validation. BJU Int 98: 329–334

    Article  Google Scholar 

  33. Chun FK et al. (2006) Development and internal validation of a nomogram predicting the probability of prostate cancer Gleason sum upgrading between biopsy and radical prostatectomy pathology. Eur Urol 49: 820–826

    Article  Google Scholar 

  34. Epstein JI et al. (1998) Nonpalpable stage T1c prostate cancer: prediction of insignificant disease using free/total prostate specific antigen levels and needle biopsy findings. J Urol 160: 2407–2411

    Article  CAS  Google Scholar 

  35. Kattan MW et al. (2003) Counseling men with prostate cancer: a nomogram for predicting the presence of small, moderately differentiated, confined tumors. J Urol 170: 1792–1797

    Article  Google Scholar 

  36. Steyerberg EW et al. (2007) Prediction of indolent prostate cancer: validation and updating of a prognostic nomogram. J Urol 177: 107–112

    Article  CAS  Google Scholar 

  37. Klotz L (2005) Active surveillance for prostate cancer: for whom? J Clin Oncol 23: 8165–8169

    Article  Google Scholar 

  38. Kattan MW et al. (1998) A preoperative nomogram for disease recurrence following radical prostatectomy for prostate cancer. J Natl Cancer Inst 90: 766–771

    Article  CAS  Google Scholar 

  39. Kattan MW et al. (2000) Pretreatment nomogram for predicting the outcome of three-dimensional conformal radiotherapy in prostate cancer. J Clin Oncol 18: 3352–3359

    Article  CAS  Google Scholar 

  40. Kattan MW et al. (2001) Pretreatment nomogram for predicting freedom from recurrence after permanent prostate brachytherapy in prostate cancer. Urology 58: 393–399

    Article  CAS  Google Scholar 

  41. [No authors listed] (1997) Consensus statement: guidelines for PSA following radiation therapy. American Society for Radiology and Oncology Consensus Panel. Int J Radiat Oncol Biol Phys 37: 1035–1041

  42. Graefen M et al. (2002) International validation of a preoperative nomogram for prostate cancer recurrence after radical prostatectomy. J Clin Oncol 20: 3206–3212

    Article  Google Scholar 

  43. Specht MC et al. (2005) Predicting nonsentinel node status after positive sentinel lymph biopsy for breast cancer: clinicians versus nomogram. Ann Surg Oncol 12: 654–659

    Article  Google Scholar 

  44. Stephenson AJ et al. (2006) Preoperative nomogram predicting the 10-year probability of prostate cancer recurrence after radical prostatectomy. J Natl Cancer Inst 98: 715–717

    Article  Google Scholar 

Download references

Acknowledgements

PI Karakiewicz is partially supported by the University of Montreal Heath Center Urology Associates, Fonds de la Recherche en Santé du Québec, the University of Montreal Department of Surgery, and the University of Montreal Health Center (CHUM) Foundation.

Author information

Authors and Affiliations

  1. PI Karakiewicz is a Urologic Oncologist, Associate Professor and Director of the Cancer Prognostics and Health Outcomes Unit, and GC Hutterer is completing a research fellowship at the University of Montreal Health Center, Montreal, QC, Canada.,

    Pierre I Karakiewicz & Georg C Hutterer

Authors
  1. Pierre I Karakiewicz
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Georg C Hutterer
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Pierre I Karakiewicz.

Ethics declarations

Competing interests

The authors declare no competing financial interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Karakiewicz, P., Hutterer, G. Predictive models and prostate cancer. Nat Rev Urol 5, 82–92 (2008). https://doi.org/10.1038/ncpuro0972

Download citation

  • Received:

  • Accepted:

  • Issue Date:

  • DOI: https://doi.org/10.1038/ncpuro0972

This article is cited by

Search

Advanced search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing