Predicting Prostate Cancer Recurrence After Radical Prostatectomy | Zendy

Jeffers Abra | Zendy; Sochat Vanessa | Zendy; Kattan Michael W. | Zendy; Yu Changhong | Zendy; Melcon Erin | Zendy; Yamoah Kosi | Zendy; Rebbeck Timothy R. | Zendy; Whittemore Alice S. | Zendy

AI Assistant Blog Pricing

Home ZAIA Blog

Premium

Predicting Prostate Cancer Recurrence After Radical Prostatectomy

Author(s) -

Jeffers Abra,

Sochat Vanessa,

Kattan Michael W.,

Yu Changhong,

Melcon Erin,

Yamoah Kosi,

Rebbeck Timothy R.,

Whittemore Alice S.

Publication year - 2017

Publication title -

the prostate

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 1.295

H-Index - 123

eISSN - 1097-0045

pISSN - 0270-4137

DOI - 10.1002/pros.23268

Subject(s) - medicine , prostatectomy , prostate cancer , biochemical recurrence , receiver operating characteristic , confidence interval , body mass index , cohort , prostate , breakpoint cluster region , prostate specific antigen , cancer , urology , oncology , receptor

Prostate cancer prognosis is variable, and management decisions involve balancing patients' risks of recurrence and recurrence-free death. Moreover, the roles of body mass index (BMI) and race in risk of recurrence are controversial [1,2]. To address these issues, we developed and cross-validated RAPS (Risks After Prostate Surgery), a personal prediction model for biochemical recurrence (BCR) within 10 years of radical prostatectomy (RP) that includes BMI and race as possible predictors, and recurrence-free death as a competing risk.

This content is not available in your region!

Continue researching here.

Having issues? You can contact us here

Accelerating Research