Delayed Prostate Cancer treatment might increase the risk of recurrence
Time to receive treatment or treatment delays is an important quality metric in patient-centered care that has been shown to impact outcome among various cancer. However, the clinical implications of delays in prostate cancer treatment remain unclear, with some studies suggesting no association between treatment delays and prostate cancer outcomes.
The Authors conducted a retrospective study with 1,807 patients who underwent radical prostatectomy (RP) as primary treatment for clinically localized PCa at 2 large tertiary referral centers from 1987 to 2015. The median follow-up time was 46 months (range 18-86 months). Initial delay up to 6 months did not adversely affect outcomes, but a delay in treatment beyond 6 months was associated with a nearly 2-fold increased risk of biochemical recurrence.
Most patients (61.5%) underwent RP at 3 months or less after diagnosis, whereas 31.1% underwent RP more than 3 months and up to 6 months after diagnosis, and 7.4% underwent RP more than 6 months after diagnosis.
The overall 5-year rates of freedom from biochemical failure were 78% and 82% for time to treatment of 0-3 month and greater than 3 but not more than 6 months after diagnosis, respectively, compared with 69% for time to treatment greater than 6 months.
The investigators defined biochemical recurrence as a clinician documented single PSA value of 0.2 ng/mL or higher or 2 consecutive PSA values of 0.2 ng/mL after RP.
The initial delays up to 6 months in prostate cancer primary treatment may be sustainable without adversely affecting the outcome. However, significant delays beyond 6 months can unfavorably impact biochemical disease control. Impact:Time to treatment can aide clinicians in the decision making of PCa treatment recommendation and educate patients against unintentional treatment delays.
Awasthi S, Gerke T, Park JY, et al. Optimizing time-to-treatment to achieve durable biochemical disease control after surgery in prostate cancer - A multi-institutional cohort study. Cancer Epidemiol Biomarkers Prev. 2018; published online ahead of print.