Investigators evaluate work burden post-prostate cancer treatment

In this video, Samuel L. Washington III, MD, MAS, discusses the background for the recent Cancer Medicine study “Ten-year work burden after prostate cancer treatment.” Washington is an assistant professor of urology and holds the Goldberg-Benioff Endowed Professorship in Cancer Biology at the University of California, San Francisco.

Transcription:

What were some of the notable findings? Were any of them surprising to you and your coauthors?

Some of the things that we expected were that surgical patients would take more time off during the first year. But we really expected that there would be minimal time moving forward for any treatments. And we saw that there were still a significant proportion of patients who were taking more than a week off each year over time for cancer care. We found that Black men and those undergoing radiation were less likely to report time off from work over time compared with other groups. And that was really surprising. That was something that we couldn't exactly explain with the data and the questions that we had asked, but really raises questions about the ability to take time off from work long term. And this really informed continued work in our department to better understand the burden of care, social needs, and other barriers that may be preventing patients from following up even after treatment.

How do you think these findings will affect how you counsel patients with prostate cancer?

I think this study gives us actual numbers, so we can have a sense of how much time people will take off over time. So I could say that for people who are undergoing surgery, still somewhere between 11% to 14% of patients will report taking at least a week's worth of time off after surgery has already happened. And that just gives them an idea of what that continued package of cancer surveillance looks like. And we would be able to do the same thing for radiation and the same thing for active surveillance now that we have these specific numbers, where before we may not have been able to characterize it in that quantitative way.

This transcript was edited for clarity.