Duration of sick leave after active surveillance, surgery or radiotherapy for localised prostate cancer: a nationwide cohort study

Ten-year work burden after prostate cancer treatment

INTRODUCTION

We aim to characterize the magnitude of the work burden (weeks off from work) associated with prostate cancer (PCa) treatment over a 10-year period after PCa diagnosis and identify those at greatest risk.

MATERIALS AND METHODS

We identified men diagnosed with PCa treated with radical prostatectomy, radiation therapy, or active surveillance/watchful waiting within CaPSURE. Patients self-reported work burden and SF36 general health scores via surveys before and 1,3,5, and 10 years after treatment. Using multivariate repeated measures generalized estimating equation modeling we examined the association between primary treatment with risk of any work weeks lost due to care.

RESULTS

In total, 6693 men were included. The majority were White (81%, 5% Black, and 14% Other) with CAPRA low- (60%) or intermediate-risk (32%) disease and underwent surgery (62%) compared to 29% radiation and 9% active surveillance. Compared to other treatments, surgical patients were more likely to report greater than 7 days off work in the first year, with relatively less time off over time. Black men (RR 0.64, 95% CI 0.54-0.77) and those undergoing radiation (vs. surgery, RR 0.46, 95% CI 0.41-0.51) were less likely to report time off from work over time. Mean baseline GH score (73 [SD 18]) was similar between race and treatment groups, and stable over time.

CONCLUSIONS

The work burden of cancer care continued up to 10 years after treatment and varied across racial groups and primary treatment groups, highlighting the multifactorial nature of this issue and the call to leverage greater resources for those at greatest risk.

Human exposome assessment platform

The Human Exposome Assessment Platform (HEAP) is a research resource for the integrated and efficient management and analysis of human exposome data. The project will provide the complete workflow for obtaining exposome actionable knowledge from population-based cohorts. HEAP is a state-of-the-science service composed of computational resources from partner institutions, accessed through a software framework that provides the world's fastest Hadoop platform for data warehousing and applied artificial intelligence (AI). The software, will provide a decision support system for researchers and policymakers. All the data managed and processed by HEAP, together with the analysis pipelines, will be available for future research. In addition, the platform enables adding new data and analysis pipelines. HEAP's final product can be deployed in multiple instances to create a network of shareable and reusable knowledge on the impact of exposures on public health.