Noncurated Data Lead to Misinterpretation of Treatment Outcomes in Patients With Prostate Cancer After Salvage or Palliative Radiotherapy.

Abstract

Clinical data warehouses (cDWHs) and cancer registry databases have enabled researchers to conduct clinical analytics with structured electronic health record data. However, these secondary electronic health record sources are often limited in scope because they do not capture the clinical information needed to understand complex clinical questions. Thus, we evaluated the effect of additional curation of data. Clinical data sets of 149 patients with prostate cancer with biochemical recurrence after radical prostatectomy treated with salvage or palliative radiotherapy between 2008 and 2017 from our institutional cDWH and Gießener Tumor Documentation System (GTDS) were linked (data warehouse [DWH] population) for analyzing treatment outcomes. The linked data sets were manually curated (manual postprocessing [MPP], eg, incorporate data from established urologists). The primary outcomes were the impact on data quality of treatment outcomes and the time spent on data curation. We obtained significantly more information on disease progression and patient survival (nonsignificant) when using curated data; the biochemical progression-free survival rate at 5 years for the DWH and DWH plus MPP populations was 63% v 30% (P ≤ .001) and the overall survival rate was 84% v 81% (P = .479), respectively. The median deviation of completeness and the median concordance of clinical data values were 21.47% (range, 55.38%-100%) and 95.00% (range, 63.40%-100%), respectively. We spent 121 hours, 42 minutes on data curation, with most time required for laboratory values, accounting, for a total of 45 hours, 20 minutes (37.26%). Our analysis indicates that time-to-event outcomes for patients with prostate cancer cannot be extracted using secondary data sources (cDWH plus GTDS) only. Outcomes data differed between the electronic data (DWH) and the second manual extraction (DWH plus MPP) because of a lack of follow-up data. When using such unique database resources, only baseline characteristics can reliably be extracted.