Clinical annotations for prostate cancer research: Defining data elements, creating a reproducible analytical pipeline, and assessing data quality.

BACKGROUND: Routine clinical data from clinical charts are indispensable for retrospective and prospective observational studies and clinical trials. Their reproducibility is often not assessed. We developed a prostate cancer-specific database for clinical annotations and evaluated data reproducibility. METHODS: For men with prostate cancer who had clinical-grade paired tumor-normal sequencing at a comprehensive cancer center, we performed team-based retrospective data collection from the electronic medical record using a defined source hierarchy. We developed an open-source R package for data processing. With blinded repeat annotation by a reference medical oncologist, we assessed data completeness, reproducibility of team-based annotations, and impact of measurement error on bias in survival analyses. RESULTS: Data elements on demographics, diagnosis and staging, disease state at the time of procuring a genomically characterized sample, and clinical outcomes were piloted and then abstracted for 2261 patients (with 2631 samples). Completeness of data elements was generally high. Comparing to the repeat annotation by a medical oncologist blinded to the database (100 patients/samples), reproducibility of annotations was high; T stage, metastasis date, and presence and date of castration resistance had lower reproducibility. Impact of measurement error on estimates for strong prognostic factors was modest. CONCLUSIONS: With a prostate cancer-specific data dictionary and quality control measures, manual clinical annotations by a multidisciplinary team can be scalable and reproducible. The data dictionary and the R package for reproducible data processing are freely available to increase data quality and efficiency in clinical prostate cancer research.

Differences in Prostate Cancer Genomes by Self-reported Race: Contributions of Genetic Ancestry, Modifiable Cancer Risk Factors, and Clinical Factors.

PURPOSE: Black men die from prostate cancer twice as often as White men, a disparity likely due to inherited genetics, modifiable cancer risk factors, and healthcare access. It is incompletely understood how and why tumor genomes differ by self-reported race and genetic ancestry. EXPERIMENTAL DESIGN: Among 2,069 men with prostate cancer (1,841 self-reported White, 63 Asian, 165 Black) with access to clinical-grade sequencing at the same cancer center, prevalence of tumor and germline alterations was assessed in cancer driver genes reported to have different alteration prevalence by race. RESULTS: Clinical characteristics such as prostate-specific antigen and age at diagnosis as well as cancer stage at sample procurement differed by self-reported race. However, most genomic differences persisted when adjusting for clinical characteristics. Tumors from Black men harbored fewer PTEN mutations and more AR alterations than those from White men. Tumors from Asian men had more FOXA1 mutations and more ZFHX3 alterations than White men. Despite fewer TP53 mutations, tumors from Black men had more aneuploidy, particularly chromosome arm 8q gains, an adverse prognostic factor. Genetic ancestry was associated with similar tumor alterations as self-reported race, but also with modifiable cancer risk factors. Community-level average income was associated with chr8q gains after adjusting for race and ancestry. CONCLUSIONS: Tumor genomics differed by race even after accounting for clinical characteristics. Equalizing access to care may not fully eliminate such differences. Therapies for alterations more common in racial minorities are needed. Tumor genomic differences should not be assumed to be entirely due to germline genetics.