Joint spatial survival modeling for the age at diagnosis and the vital outcome of prostate cancer.
Prostate cancer (PrCA) is the most common malignancy in men and a leading cause of cancer mortality among males in the United States. Large geographical variation and racial disparities exist in both the incidence of PrCA and the survival rate after diagnosis. In this population-based study, a joint spatial survival model is constructed to investigate factors that affect the age at diagnosis of PrCA and the subsequent survival. The joint model for these two time-to-event outcomes is specified through parametric models for age at diagnosis and survival time conditional on diagnosis age. To account for possible correlation in these outcomes among men from the same geographical region, frailty terms are included in the survival model. Both spatially correlated and uncorrelated frailties are incorporated in each model considered. The deviance information criterion is used to select a best-fitting model within the Bayesian framework. The results from our final best-fitting model indicate that race, marital status at diagnosis, and cancer stage are significantly associated with both of the two time-to-event outcomes. No pattern emerged in the geographical distribution of age at PrCA diagnosis. In contrast, a spatially clustered pattern was observed in the geographic distribution of survival experience post diagnosis.
Zhou
Huafeng
H
Department of Epidemiology and Biostatistics, The Arnold School of Public Health, University of South Carolina, 800 Sumter Street, Columbia, SC 29208, USA.
Lawson
Andrew B
AB
Hebert
James R
JR
Slate
Elizabeth H
EH
Hill
Elizabeth G
EG
D000328:Adult; D000367:Age Factors; D000368:Aged; D000369:Aged, 80 and over; D003710:Demography; D006801:Humans; D008297:Male; D008875:Middle Aged; D010043:Outcome and Process Assessment, Health Care / Q000706:statistics & numerical data*; D011471:Prostatic Neoplasms / Q000145:classification / Q000175:diagnosis* / Q000401:mortality*; D013022:South Carolina / Q000453:epidemiology; D016019:Survival Analysis