External validation of the PREDICT Prostate tool for prognostication in non-metastatic prostate cancer: A study in 69,206 men from Prostate Cancer data Base Sweden
BAUS ePoster online library. Thurtle D. Jun 24, 2019; 259546; P5-2
Mr. David Thurtle
Mr. David Thurtle
Login now to access Regular content available to all registered users.

You may also access this content "anytime, anywhere" with the Free MULTILEARNING App for iOS and Android
Abstract
Rate & Comment (0)
Introduction and objectives
PREDICT Prostate is a novel prognostic model for non-metastatic prostate cancer(PCa). Derived from UK data, it uses baseline clinico-pathological and co-morbidity data to generate individualised survival estimates and model potential treatment benefit. Here we externally validated the model in a large independent dataset, and reviewed performance by treatment groups.

Materials and methods
Data on age, PSA, clinical T stage, grade group, biopsy involvement, primary treatment and comorbidity were retrieved from the nation-wide population-based PCa dataBase Sweden(PCBase). Men with non-metastatic PCa and PSA<100 ng/ml diagnosed between 2000 and 2010 were included.
15-year PCa-specific mortality(PCSM) and all-cause mortality(ACM) estimates were calculated using the PREDICT Prostate algorithm within a competing-risk model. Discrimination was assessed using Harrell's concordance(c)-index. Calibration was evaluated using cumulative follow-up until 15 years.

RESULTS

69,206 men were included with 13 years median follow-up. Overall discrimination of PREDICT was good with c-indices of 0.85(95%CI:0.85-0.86) for PCSM and 0.79(95%CI:0.79-0.79) for ACM. Calibration was excellent with 25,925 deaths predicted and 25,849 deaths observed.
20,384 men underwent conservative management and 32,842men received radical treatment. Within these treatment groups c-indices for 15-year PCSM were 0.81 and 0.78 respectively. C-indices were further improved at 0.88 for PCSM and 0.75 for ACM among men on 'active surveillance'. Differences between observed and predicted deaths were less than 3.5% in each treatment group.

CONCLUSION

This large external validation demonstrates PREDICT Prostate is a robust and generalisable model. It improves upon existing models by providing individualised estimates, adjusting for competing-risks and modelling treatment benefit.
    This eLearning portal is powered by:
    This eLearning portal is powered by MULTIEPORTAL
Anonymous User Privacy Preferences

Strictly Necessary Cookies (Always Active)

MULTILEARNING platforms and tools hereinafter referred as “MLG SOFTWARE” are provided to you as pure educational platforms/services requiring cookies to operate. In the case of the MLG SOFTWARE, cookies are essential for the Platform to function properly for the provision of education. If these cookies are disabled, a large subset of the functionality provided by the Platform will either be unavailable or cease to work as expected. The MLG SOFTWARE do not capture non-essential activities such as menu items and listings you click on or pages viewed.


Performance Cookies

Performance cookies are used to analyse how visitors use a website in order to provide a better user experience.


Save Settings