PURPOSE: We designed and fully evaluated the performance of a nomogram to identify patients with prostate cancer who may be suitable for active surveillance. MATERIALS AND METHODS: We developed a nomogram to predict the probability of minimal prostate cancer (total tumor volume less than 0.5 cc, organ confined disease and no Gleason pattern 4 or 5) using preoperative data on 2,525 Australian patients who underwent radical prostatectomy. Accuracy and error rates at multiple probability cutoffs were compared with those of contemporary Epstein criteria and the Prostate Cancer Research International: Active Surveillance trial inclusion criteria when applied to these patients. High risk disease was defined as 1 or more adverse characteristics (including positive surgical margins, seminal vesicle invasion, extracapsular extension, 50% or greater Gleason pattern 4/5 and/or tumor volume 4.0 cc or greater) at radical prostatectomy. RESULTS: Minimal cancer was confirmed in 152 men (6.0%) at prostatectomy. The bootstrap corrected predictive accuracy of our nomogram was 93.3% vs 89.1% and 91.0% for Prostate Cancer Research International: Active Surveillance and Epstein criteria, respectively. For men with a nomogram derived minimal cancer probability of 0% to 4.9%, 5.0% to 19.9%, 20.0% to 34.9%, 35.0% to 49.9% and 50.0% to 71.0% the rate of high risk disease was 70.8%, 37.8%, 22.4%, 9.0% and 3.8%, respectively. In contrast, the rate of high risk disease for men who met Prostate Cancer Research International: Active Surveillance and Epstein criteria were 17.1% and 13.9%, respectively. CONCLUSIONS: A detailed breakdown of the expected rates of false-positive results and high risk disease associated with the nomogram derived probability of minimal cancer would provide more complete information to clinicians and patients on which to base therapeutic clinical decisions for presumed early stage prostate cancer.
PURPOSE: We designed and fully evaluated the performance of a nomogram to identify patients with prostate cancer who may be suitable for active surveillance. MATERIALS AND METHODS: We developed a nomogram to predict the probability of minimal prostate cancer (total tumor volume less than 0.5 cc, organ confined disease and no Gleason pattern 4 or 5) using preoperative data on 2,525 Australian patients who underwent radical prostatectomy. Accuracy and error rates at multiple probability cutoffs were compared with those of contemporary Epstein criteria and the Prostate Cancer Research International: Active Surveillance trial inclusion criteria when applied to these patients. High risk disease was defined as 1 or more adverse characteristics (including positive surgical margins, seminal vesicle invasion, extracapsular extension, 50% or greater Gleason pattern 4/5 and/or tumor volume 4.0 cc or greater) at radical prostatectomy. RESULTS: Minimal cancer was confirmed in 152 men (6.0%) at prostatectomy. The bootstrap corrected predictive accuracy of our nomogram was 93.3% vs 89.1% and 91.0% for Prostate Cancer Research International: Active Surveillance and Epstein criteria, respectively. For men with a nomogram derived minimal cancer probability of 0% to 4.9%, 5.0% to 19.9%, 20.0% to 34.9%, 35.0% to 49.9% and 50.0% to 71.0% the rate of high risk disease was 70.8%, 37.8%, 22.4%, 9.0% and 3.8%, respectively. In contrast, the rate of high risk disease for men who met Prostate Cancer Research International: Active Surveillance and Epstein criteria were 17.1% and 13.9%, respectively. CONCLUSIONS: A detailed breakdown of the expected rates of false-positive results and high risk disease associated with the nomogram derived probability of minimal cancer would provide more complete information to clinicians and patients on which to base therapeutic clinical decisions for presumed early stage prostate cancer.
Authors: L M Wong; D E Neal; A Finelli; S Davis; C Bonner; J Kapoor; J Trachtenberg; B Thomas; C M Hovens; A J Costello; N M Corcoran Journal: Prostate Cancer Prostatic Dis Date: 2015-02-10 Impact factor: 5.554
Authors: Gianluca Severi; Liesel M FitzGerald; David C Muller; John Pedersen; Anthony Longano; Melissa C Southey; John L Hopper; Dallas R English; Graham G Giles; John Mills Journal: Cancer Med Date: 2014-06-07 Impact factor: 4.452
Authors: L-M Wong; D E Neal; R B Johnston; N Shah; N Sharma; A Y Warren; C M Hovens; S Larry Goldenberg; M E Gleave; A J Costello; N M Corcoran Journal: Br J Cancer Date: 2012-10-04 Impact factor: 7.640