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Predicting Time From Metastasis to Overall Survival in Castration-Resistant Prostate Cancer: Results From SEARCH.


ABSTRACT: To identify the predictors of time from initial diagnosis of metastatic castration-resistance prostate cancer (mCRPC) to all-cause death within the Shared Equal Access Regional Cancer Hospital cohort.We performed a retrospective analysis of 205 mCRPC men. Overall survival was estimated and plotted using the Kaplan-Meier method. The uni- and multivariable overall survival predictors were evaluated with the Cox proportional hazards model. A nomogram was generated to predict overall survival at 1, 2, 3, and 5 years after mCRPC. Concordance index and calibration plot were obtained.A total of 170 men (83%) died over a median follow-up of 41 months. In univariable analysis, older age, more remote year of mCRPC, nonblack race, greater number of bone metastasis, higher prostate-specific antigen (PSA) levels, shorter PSA doubling time, and faster PSA velocity at mCRPC diagnosis were significantly associated with shorter overall survival (all P < .05). In multivariable analysis, older age, more remote year of mCRPC, greater number of bone metastasis, higher PSA levels, and shorter PSA doubling time at mCRPC diagnosis remained significantly associated with shorter overall survival (all P < .05). On the basis of these variables, a nomogram was generated yielding a concordance index of 0.67 and good calibration.The use of clinical parameter such as age, disease burden, and PSA levels and kinetics can be used to estimate overall survival in mCRPC patients.

SUBMITTER: Moreira DM 

PROVIDER: S-EPMC5536956 | biostudies-literature | 2017 Feb

REPOSITORIES: biostudies-literature

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<h4>Objective</h4>To identify the predictors of time from initial diagnosis of metastatic castration-resistance prostate cancer (mCRPC) to all-cause death within the Shared Equal Access Regional Cancer Hospital cohort.<h4>Patients and methods</h4>We performed a retrospective analysis of 205 mCRPC men. Overall survival was estimated and plotted using the Kaplan-Meier method. The uni- and multivariable overall survival predictors were evaluated with the Cox proportional hazards model. A nomogram w  ...[more]

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