News Release

Individualized model could help guide treatment of non-metastatic prostate cancer

Peer-Reviewed Publication

PLOS

Individualised model could help guide treatment of non-metastatic prostate cancer

image: A new risk model, easily accessible on a web interface, can predict the survival of non-metastatic prostate cancer patients, as well as the effect of different treatment approaches on survival. view more 

Credit: marijana1, Pixabay

A new risk model, easily accessible on a web interface, can predict the survival of non-metastatic prostate cancer patients, as well as the effect of different treatment approaches on survival. The modeling approach, developed by David Thurtle of the University of Cambridge, UK, and colleagues, is described this week in PLOS Medicine.

Among men with non-metastatic prostate cancer, a number of treatment options may be appropriate, ranging from "watchful waiting" to surgery and aggressive therapies. Prognosticating prostate cancer-specific mortality, all-cause mortality, and the impact of treatment are of crucial importance to inform decision making and avoid over-treatment of indolent disease and under-treatment of aggressive disease. In the new study, researchers developed the PREDICT Prostate model, using data from the UK National Cancer Registration and Analysis Service on 10,089 men diagnosed with non-metastatic prostate cancer between 2000 and 2010 in Eastern England as well as 2,546 men diagnosed in Singapore. The model--estimating 10- and 15-year survival outcomes--was constructed and validated using the men's age, level of PSA (prostate specific antigen), tumour histological grade, biopsy core involvement, disease stage and primary treatment.

The new PREDICT Prostate risk model predicted survival outcomes with concordance indices up to 0.84 (95% CI: 0.82-0.86). There were no significant differences between predicted and observed prostate-cancer-specific or overall deaths in the UK dataset. However, the study was limited by a relatively small external validation cohort and the inability to account for delayed changes to treatment beyond 12 months.

"The model does not require any additional tests beyond standard of care, and is freely available for use," the authors say, adding that it "has the potential to enable well-informed and standardized decision-making and reduce both over- and under-treatment."

###

Research Article

Funding:

This work was supported by The Urology Foundation Research Scholarship (DRT), http://www.theurologyfoundation.org, and by The Evelyn Trust (REF 16/16) Cambridge (DRT, PDP, and VJG), http://evelyntrust.com. Infrastructure support was received from Cancer Research UK Cambridge Centre. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. The researchers are independent of the sponsors.

Competing Interests:

The authors have declared that no competing interests exist.

Citation:

Thurtle DR, Greenberg DC, Lee LS, Huang HH, Pharoah PD, Gnanapragasam VJ (2019) Individual prognosis at diagnosis in nonmetastatic prostate cancer: Development and external validation of the PREDICT Prostate multivariable model. PLoS Med 16(3): e1002758. https://doi.org/10.1371/journal.pmed.1002758

Image Credit: marijana1, Pixabay

Author Affiliations:

Academic Urology Group, Department of Surgery, University of Cambridge, Cambridge, United Kingdom
Department of Urology, Cambridge University Hospitals NHS Foundation Trust, Cambridge, United Kingdom
National Cancer Registration and Analysis Service (Eastern Region), Fulbourn, Cambridge, United Kingdom
Department of Urology, Singapore General Hospital, Singapore
Centre for Cancer Genetic Epidemiology, Department of Oncology, University of Cambridge, Cambridge, United Kingdom
Cambridge Urology Translational Research and Clinical Trials, Cambridge, United Kingdom

In your coverage please use this URL to provide access to the freely available paper: http://journals.plos.org/plosmedicine/article?id=10.1371/journal.pmed.1002758


Disclaimer: AAAS and EurekAlert! are not responsible for the accuracy of news releases posted to EurekAlert! by contributing institutions or for the use of any information through the EurekAlert system.