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.

  • Original Article
  • Published:

Clinical Research

Evaluating prostate cancer mortality and competing risks of death in patients with localized prostate cancer using a comprehensive nomogram

Abstract

BACKGROUND:

The aim of this study was to determine the optimal treatment for a patient with newly diagnosed prostate cancer weighing the individual's risk of disease progression against his risk of non-cancer death.

METHODS:

We developed a predictive model incorporating clinicopathological tumor variables, patient age, comorbidity status, and primary treatment modality. We identified 6091 patients with clinically-localized prostate cancer managed with radical prostatectomy (n=4117) or radiation therapy (n=1974) from the Cancer of the Prostate Strategic Urologic Research Endeavor database. Fine and Gray competing-risks proportional hazards regression models were used to calculate the risks of prostate cancer-specific mortality (PCSM) and non-prostate cancer death and to generate a nomogram.

RESULTS:

The median follow-up after treatment was 53 months (interquartile range 30, 80 months). In total, 983 men died during follow-up, including 167 who died of prostate cancer and 816 who died of non-prostate cancer causes. On multivariate analysis, higher Cancer of the Prostate Risk Assessment score and primary treatment with radiation were associated with an increased risk of PCSM, whereas older age, African-American race, and treatment with radiation predicted non-prostate cancer death. The number of comorbidities and receipt of androgen deprivation therapy correlated with an increased risk of non-prostate cancer death, but not PCSM. The resulting nomogram allows quantification and comparison of the 10-year risk of PCSM and non-prostate cancer death.

CONCLUSIONS:

Integrating clinicopathological variables with comorbid conditions in a competing-risks model affords quantification and comparison of relative probabilities of PCSM and non-prostate cancer death following treatment. Our model thereby facilitates an individualized approach for counseling patients regarding prostate cancer management.

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

Access options

Buy this article

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

Figure 1
Figure 2

Similar content being viewed by others

References

  1. Siegel R, Ward E, Brawley O, Jemal A . Cancer statistics, 2011: the impact of eliminating socioeconomic and racial disparities on premature cancer deaths. CA Cancer J Clin 2011; 61: 212–236.

    Article  Google Scholar 

  2. Lu-Yao GL, Albertsen PC, Moore DF, Shih W, Lin Y, DiPaola RS et al. Outcomes of localized prostate cancer following conservative management. JAMA 2009; 302: 1202–1209.

    Article  CAS  Google Scholar 

  3. Sanda MG, Dunn RL, Michalski J, Sandler HM, Northouse L, Hembroff L et al. Quality of life and satisfaction with outcome among prostate-cancer survivors. N Engl J Med 2008; 358: 1250–1261.

    CAS  PubMed  Google Scholar 

  4. Mohler JL . The 2010 NCCN clinical practice guidelines in oncology on prostate cancer. J Natl Compr Canc Netw 2010; 8: 145.

    Article  Google Scholar 

  5. Thompson I, Thrasher JB, Aus G, Burnett AL, Canby-Hagino ED, Cookson MS et al. Guideline for the management of clinically localized prostate cancer: 2007 update. J Urol 2007; 177: 2106–2131.

    Article  Google Scholar 

  6. Heidenreich A, Bellmunt J, Bolla M, Joniau S, Mason M, Matveev V et al. EAU guidelines on prostate cancer. Part 1: screening, diagnosis, and treatment of clinically localised disease. Eur Urol 2011; 59: 61–71.

    Article  Google Scholar 

  7. Bill-Axelson A, Holmberg L, Ruutu M, Garmo H, Stark JR, Busch C et al. Radical prostatectomy versus watchful waiting in early prostate cancer. N Engl J Med 2011; 364: 1708–1717.

    Article  CAS  Google Scholar 

  8. Harlan LC, Potosky A, Gilliland FD, Hoffman R, Albertsen PC, Hamilton AS et al. Factors associated with initial therapy for clinically localized prostate cancer: prostate cancer outcomes study. J Natl Cancer Inst 2001; 93: 1864–1871.

    Article  CAS  Google Scholar 

  9. Houterman S, Janssen-Heijnen ML, Verheij CD, Kil PJ, van den Berg HA, Coebergh JW . Greater influence of age than co-morbidity on primary treatment and complications of prostate cancer patients: an in-depth population-based study. Prostate Cancer Prostatic Dis 2006; 9: 179–184.

    Article  CAS  Google Scholar 

  10. Alibhai SM, Leach M, Tomlinson GA, Krahn MD, Fleshner NE, Naglie G . Is there an optimal comorbidity index for prostate cancer? Cancer 2008; 112: 1043–1050.

    Article  Google Scholar 

  11. Lughezzani G, Briganti A, Karakiewicz PI, Kattan MW, Montorsi F, Shariat SF et al. Predictive and prognostic models in radical prostatectomy candidates: a critical analysis of the literature. Eur Urol 2010; 58: 687–700.

    Article  Google Scholar 

  12. Walz J, Gallina A, Saad F, Montorsi F, Perrotte P, Shariat SF et al. A nomogram predicting 10-year life expectancy in candidates for radical prostatectomy or radiotherapy for prostate cancer. J Clin Oncol 2007; 25: 3576–3581.

    Article  Google Scholar 

  13. Tewari A, Johnson CC, Divine G, Crawford ED, Gamito EJ, Demers R et al. Long-term survival probability in men with clinically localized prostate cancer: a case-control, propensity modeling study stratified by race, age, treatment and comorbidities. J Urol 2004; 171: 1513–1519.

    Article  Google Scholar 

  14. Lubeck DP, Litwin MS, Henning JM, Stier DM, Mazonson P, Fisk R et al. The CaPSURE database: a methodology for clinical practice and research in prostate cancer. CaPSURE Research Panel. Cancer of the Prostate Strategic Urologic Research Endeavor. Urology 1996; 48: 773–777.

    Article  CAS  Google Scholar 

  15. Cooperberg MR, Broering JM, Carroll PR . Risk assessment for prostate cancer metastasis and mortality at the time of diagnosis. J Natl Cancer Inst 2009; 101: 878–887.

    Article  Google Scholar 

  16. Marr PL, Elkin EP, Arredondo SA, Broering JM, DuChane J, Carroll PR . Comorbidity and primary treatment for localized prostate cancer: data from CaPSURE. J Urol 2006; 175: 1326–1331.

    Article  Google Scholar 

  17. Crawford ED, Grubb III R, Black A, Andriole Jr GL, Chen MH, Izmirlian G et al. Comorbidity and mortality results from a randomized prostate cancer screening trial. J Clin Oncol 2011; 29: 355–361.

    Article  Google Scholar 

  18. US National Center for Health Statistics. National Vital Statistics Report (NVSR) Deaths: Final Data for 2006. Vol. 67, No. 14, 24 April 2009.

  19. Fine JP, Gray RJ . A proportional hazards model for the subdistrituion of a competing risk. J Am Stat Assoc 1999; 94: 496–509.

    Article  Google Scholar 

  20. Zhao KH, Hernandez DJ, Han M, Humphreys EB, Mangold LA, Partin AW . External validation of University of California, San Francisco, Cancer of the Prostate Risk Assessment score. Urology 2008; 72: 396–400.

    Article  Google Scholar 

  21. Shariat SF, Karakiewicz PI, Roehrborn CG, Kattan MW . An updated catalog of prostate cancer predictive tools. Cancer 2008; 113: 3075–3099.

    Article  Google Scholar 

  22. Cowen ME, Halasyamani LK, Kattan MW . Predicting life expectancy in men with clinically localized prostate cancer. J Urol 2006; 175: 99–103.

    Article  Google Scholar 

  23. Albertsen PC, Moore DF, Shih W, Lin Y, Li H, Lu-Yao GL . Impact of comorbidity on survival among men with localized prostate cancer. J Clin Oncol 2011; 29: 1335–1341.

    Article  Google Scholar 

  24. Abdollah F, Sun M, Schmitges J, Tian Z, Jeldres C, Briganti A et al. Cancer-specific and other-cause mortality after radical prostatectomy versus observation in patients with prostate cancer: competing-risks analysis of a large North American population-based cohort. Eur Urol 2011; 60: 920–930.

    Article  Google Scholar 

  25. Stephenson AJ, Kattan MW, Eastham JA, Bianco Jr FJ, Yossepowitch O, Vickers AJ et al. Prostate cancer-specific mortality after radical prostatectomy for patients treated in the prostate-specific antigen era. J Clin Oncol 2009; 27: 4300–4305.

    Article  Google Scholar 

  26. Melfi C, Holleman E, Arthur D, Katz B . Selecting a patient characteristics index for the prediction of medical outcomes using administrative claims data. J Clin Epidemiol 1995; 48: 917–926.

    Article  CAS  Google Scholar 

  27. Rochon PA, Katz JN, Morrow LA, McGlinchey-Berroth R, Ahlquist MM, Sarkarati M et al. Comorbid illness is associated with survival and length of hospital stay in patients with chronic disability. A prospective comparison of three comorbidity indices. Med Care 1996; 34: 1093–1101.

    Article  CAS  Google Scholar 

  28. Daskivich TJ, Chamie K, Kwan L, Labo J, Dash A, Greenfield S et al. Comorbidity and competing risks for mortality in men with prostate cancer. Cancer 2011 (E-pub ahead of print).

  29. Cooperberg MR, Vickers AJ, Broering JM, Carroll PR . Comparative risk-adjusted mortality outcomes after primary surgery, radiotherapy, or androgen-deprivation therapy for localized prostate cancer. Cancer 2010; 116: 5226–5234.

    Article  Google Scholar 

  30. Abdollah F, Sun M, Thuret R, Jeldres C, Tian Z, Briganti A et al. A competing-risks analysis of survival after alternative treatment modalities for prostate cancer patients: 1988–2006. Eur Urol 2011; 59: 88–95.

    Article  Google Scholar 

  31. Nanda A, Chen MH, Braccioforte MH, Moran BJ, D’Amico AV . Hormonal therapy use for prostate cancer and mortality in men with coronary artery disease-induced congestive heart failure or myocardial infarction. JAMA 2009; 302: 866–873.

    Article  CAS  Google Scholar 

  32. Punnen S, Cooperberg MR, Sadetsky N, Carroll PR . Androgen deprivation therapy and cardiovascular risk. J Clin Oncol 2011; 29: 3510–3516.

    Article  CAS  Google Scholar 

  33. Cooperberg MR, Broering JM, Carroll PR . Time trends and local variation in primary treatment of localized prostate cancer. J Clin Oncol 2010; 28: 1117–1123.

    Article  Google Scholar 

Download references

Acknowledgements

CaPSURE is supported in part by an independent educational grant from Abbott. Abbott did not have a role in the design, conduct, analysis, or interpretation of the study or its results. This publication was also supported in part through the P30 CA006927 Comprehensive Cancer Center Program at Fox Chase Cancer Center (AK, RGU), and a Department of Defense Physician Research Training Award (AK).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to S A Boorjian.

Ethics declarations

Competing interests

CaPSURE is supported in part by an independent educational grant from Abbott. Abbott did not have a role in the design, conduct, analysis, or interpretation of the study or its results. Dr Cooperberg has served as a consultant for Dendreon, Amgen, Centocor Ortho-biotech, and has received an honorarium from Takeda.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Kutikov, A., Cooperberg, M., Paciorek, A. et al. Evaluating prostate cancer mortality and competing risks of death in patients with localized prostate cancer using a comprehensive nomogram. Prostate Cancer Prostatic Dis 15, 374–379 (2012). https://doi.org/10.1038/pcan.2012.21

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/pcan.2012.21

Keywords

This article is cited by

Search

Quick links