Active surveillance (AS)/watchful waiting (WW) strategy for localized prostate cancer (PCa) is increasingly and broadly endorsed as a preferred option for initial treatment of men with very low- and low-risk PCa, but outcomes can be difficult to analyze in traditional, population-based registries. The recently released Surveillance, Epidemiology, and End Results (SEER) Prostate with WW dataset provides an opportunity to understand national patterns and trends in AS/WW, but the data source itself has not been well described.
To provide a comprehensive description of this dataset and investigate possible biases due to missing data.
The SEER is a population-based epidemiologic registry in the USA. Newly diagnosed PCa patient data were collected from 18 SEER registries between 2010 and 2015, with inclusion of a new treatment variable for AS/WW. We identified 316 724 patients in the entire cohort and 257 060 men with clinically localized PCa (T1-2N0M0).
Various primary treatments for PCa.
The degree of missing data for each variable was measured. In order to investigate possible bias due to missing data for cancer characterization, we compared two versions of the data: one that excluded cases with missing data and one dataset generated applying multiple imputations.
Only 46% of cases had complete data on basic cancer characteristics for risk stratification. The excluded dataset (N=118 821) differed significantly from the multiple imputation dataset (N=257 060) in the distribution of every reported variable (all p<0.001). The dataset does not distinguish WW from AS, which is a limitation.
While the SEER Prostate with WW dataset offers a new method to describe treatment trends for men with PCa, including the use of AS/WW, the amount of missing data should not be ignored.
While the Surveillance, Epidemiology, and End Results Prostate with Watchful Waiting dataset offers a new method to describe treatment trends for men with prostate cancer, including the use of active surveillance, it has a significant amount of missing data, which can be a source of potential bias if not addressed properly.
European urology. 2020 Jan 21 [Epub ahead of print]
Chang Wook Jeong, Samuel L Washington, Annika Herlemann, Scarlett L Gomez, Peter R Carroll, Matthew R Cooperberg
Helen Diller Family Comprehensive Cancer Center, Department of Urology, University of California, San Francisco, CA, USA; Department of Urology, Seoul National University Hospital, Seoul, Republic of Korea. Electronic address: ., Helen Diller Family Comprehensive Cancer Center, Department of Urology, University of California, San Francisco, CA, USA., Helen Diller Family Comprehensive Cancer Center, Department of Urology, University of California, San Francisco, CA, USA; Department of Urology, Ludwig-Maximilians-University of Munich, Munich, Germany., Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA., Helen Diller Family Comprehensive Cancer Center, Department of Urology, University of California, San Francisco, CA, USA; Department of Epidemiology & Biostatistics, University of California, San Francisco, CA, USA.