Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer

Siao Yi Wang, Janet E. Cowan, K. Clinton Cary, June M. Chan, Peter R. Carroll, Matthew R. Cooperberg

Research output: Contribution to journalArticle

24 Citations (Scopus)

Abstract

Objective To assess the ability of current nomograms to predict disease progression at repeat biopsy or at delayed radical prostatectomy (RP) in a prospectively accrued cohort of patients managed by active surveillance (AS).

Materials and Methods A total of 273 patients meeting low-risk criteria who were managed by AS and who underwent multiple biopsies and/or delayed RP were included in the study. The Kattan (base, medium and full), Steyerberg, Nakanishi and Chun nomograms were used to calculate the likelihood of indolent disease ('nomogram probability') as well as to predict 'biopsy progression' by grade or volume, 'surgical progression' by grade or stage, or 'any progression' on repeat biopsy or surgery. We evaluated the associations between each nomogram probability and each progression outcome using logistic regression with (area under the receiver-operating characteristic curve (AUC) values and decision curve analysis.

Results The nomogram probabilities of indolent disease were lower in patients with biopsy progression (P <0.01) and any progression on repeat biopsy or surgical pathology (P <0.05). In regression analyses, nomograms showed a modest ability to predict biopsy progression, adjusted for total number of biopsies (AUC range 0.52-0.67) and any progression (AUC range 0.52-0.70). Decision curve analyses showed that all the nomograms, except for the Kattan base model, have similar value in predicting biopsy progression and any progression. Nomogram probabilities were not associated with surgical progression in a subgroup of 58 men who underwent delayed RP.

Conclusions Existing nomograms have only modest accuracy in predicting the outcomes of patients undergoing AS. Improvements to existing nomograms should be made before they are implemented in clinical practice and used to select patients for AS.

Original languageEnglish (US)
Pages (from-to)E18-E24
JournalBJU International
Volume114
Issue number6
DOIs
StatePublished - Dec 1 2014
Externally publishedYes

Fingerprint

Nomograms
Prostatic Neoplasms
Biopsy
Prostatectomy
Area Under Curve
Decision Support Techniques
Surgical Pathology
ROC Curve
Disease Progression
Logistic Models
Regression Analysis

Keywords

  • active surveillance
  • nomograms
  • prediction
  • progression
  • prostate cancer

ASJC Scopus subject areas

  • Urology
  • Medicine(all)

Cite this

Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer. / Wang, Siao Yi; Cowan, Janet E.; Cary, K. Clinton; Chan, June M.; Carroll, Peter R.; Cooperberg, Matthew R.

In: BJU International, Vol. 114, No. 6, 01.12.2014, p. E18-E24.

Research output: Contribution to journalArticle

Wang, Siao Yi ; Cowan, Janet E. ; Cary, K. Clinton ; Chan, June M. ; Carroll, Peter R. ; Cooperberg, Matthew R. / Limited ability of existing nomograms to predict outcomes in men undergoing active surveillance for prostate cancer. In: BJU International. 2014 ; Vol. 114, No. 6. pp. E18-E24.
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abstract = "Objective To assess the ability of current nomograms to predict disease progression at repeat biopsy or at delayed radical prostatectomy (RP) in a prospectively accrued cohort of patients managed by active surveillance (AS).Materials and Methods A total of 273 patients meeting low-risk criteria who were managed by AS and who underwent multiple biopsies and/or delayed RP were included in the study. The Kattan (base, medium and full), Steyerberg, Nakanishi and Chun nomograms were used to calculate the likelihood of indolent disease ('nomogram probability') as well as to predict 'biopsy progression' by grade or volume, 'surgical progression' by grade or stage, or 'any progression' on repeat biopsy or surgery. We evaluated the associations between each nomogram probability and each progression outcome using logistic regression with (area under the receiver-operating characteristic curve (AUC) values and decision curve analysis.Results The nomogram probabilities of indolent disease were lower in patients with biopsy progression (P <0.01) and any progression on repeat biopsy or surgical pathology (P <0.05). In regression analyses, nomograms showed a modest ability to predict biopsy progression, adjusted for total number of biopsies (AUC range 0.52-0.67) and any progression (AUC range 0.52-0.70). Decision curve analyses showed that all the nomograms, except for the Kattan base model, have similar value in predicting biopsy progression and any progression. Nomogram probabilities were not associated with surgical progression in a subgroup of 58 men who underwent delayed RP.Conclusions Existing nomograms have only modest accuracy in predicting the outcomes of patients undergoing AS. Improvements to existing nomograms should be made before they are implemented in clinical practice and used to select patients for AS.",
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N2 - Objective To assess the ability of current nomograms to predict disease progression at repeat biopsy or at delayed radical prostatectomy (RP) in a prospectively accrued cohort of patients managed by active surveillance (AS).Materials and Methods A total of 273 patients meeting low-risk criteria who were managed by AS and who underwent multiple biopsies and/or delayed RP were included in the study. The Kattan (base, medium and full), Steyerberg, Nakanishi and Chun nomograms were used to calculate the likelihood of indolent disease ('nomogram probability') as well as to predict 'biopsy progression' by grade or volume, 'surgical progression' by grade or stage, or 'any progression' on repeat biopsy or surgery. We evaluated the associations between each nomogram probability and each progression outcome using logistic regression with (area under the receiver-operating characteristic curve (AUC) values and decision curve analysis.Results The nomogram probabilities of indolent disease were lower in patients with biopsy progression (P <0.01) and any progression on repeat biopsy or surgical pathology (P <0.05). In regression analyses, nomograms showed a modest ability to predict biopsy progression, adjusted for total number of biopsies (AUC range 0.52-0.67) and any progression (AUC range 0.52-0.70). Decision curve analyses showed that all the nomograms, except for the Kattan base model, have similar value in predicting biopsy progression and any progression. Nomogram probabilities were not associated with surgical progression in a subgroup of 58 men who underwent delayed RP.Conclusions Existing nomograms have only modest accuracy in predicting the outcomes of patients undergoing AS. Improvements to existing nomograms should be made before they are implemented in clinical practice and used to select patients for AS.

AB - Objective To assess the ability of current nomograms to predict disease progression at repeat biopsy or at delayed radical prostatectomy (RP) in a prospectively accrued cohort of patients managed by active surveillance (AS).Materials and Methods A total of 273 patients meeting low-risk criteria who were managed by AS and who underwent multiple biopsies and/or delayed RP were included in the study. The Kattan (base, medium and full), Steyerberg, Nakanishi and Chun nomograms were used to calculate the likelihood of indolent disease ('nomogram probability') as well as to predict 'biopsy progression' by grade or volume, 'surgical progression' by grade or stage, or 'any progression' on repeat biopsy or surgery. We evaluated the associations between each nomogram probability and each progression outcome using logistic regression with (area under the receiver-operating characteristic curve (AUC) values and decision curve analysis.Results The nomogram probabilities of indolent disease were lower in patients with biopsy progression (P <0.01) and any progression on repeat biopsy or surgical pathology (P <0.05). In regression analyses, nomograms showed a modest ability to predict biopsy progression, adjusted for total number of biopsies (AUC range 0.52-0.67) and any progression (AUC range 0.52-0.70). Decision curve analyses showed that all the nomograms, except for the Kattan base model, have similar value in predicting biopsy progression and any progression. Nomogram probabilities were not associated with surgical progression in a subgroup of 58 men who underwent delayed RP.Conclusions Existing nomograms have only modest accuracy in predicting the outcomes of patients undergoing AS. Improvements to existing nomograms should be made before they are implemented in clinical practice and used to select patients for AS.

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KW - prediction

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