Reliability of real-world data for diagnosis of metastatic prostate cancer.
Authors: Phuong Christina , Lin Amy M. , Friesner Izzy , Ni Lisa , Aggarwal Rahul Raj , Borno Hala , Koshkin Vadim S , Desai Arpita , Friedlander Terence W. , Fong Lawrence , Bose Rohit , Chou Jonathan , Rodvelt Tammy J. , Mohamad Osama , Wong Anthony C. , Feng Felix Y , Small Eric Jay , Hong Julian C. 
Published: September 2022

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Background: Real-world data (RWD) is playing an increasingly important role in cancer research. Surrogate endpoints such as metastasis-free survival play an important role in prostate cancer research, leading to interest in its computational extraction, typically with use of International Classification of Disease (ICD) metastatic codes. While prior studies have suggested that ICD codes are valid for identification of patients (pts) with metastatic prostate cancer (MPC), delays in coding may impact their accuracy. The objective of this informatics-based study is to quantify the time delay between diagnosis of MPC and entry of ICD MPC-related code and its interaction with changing institutional healthcare processes. Methods: A single institutional EHR data warehouse was queried to identify a random sample of 100 pts with MPC diagnosis based on ICD codes (ICD10 C79 or ICD9 198.5) from 2013-2021 who were also seen in the genitourinary medical oncology program (GUMOP). Of note, in 6/2018, the GUMOP adopted EHR-specific MPC visit diagnosis identifiers (Dx ID) to improve MPC coding during clinic independent of ICD codes typically used by RWD researchers. Thus, the study cohort was designed to include pts whose first follow up after being diagnosed with MPC was before (n = 50) or after (n = 50) Dx ID implementation. Date of first MPC ICD code entry at any point in the EHR was compared against true date of MPC, based on physician review of definitive imaging or pathology. Data analysis was performed with Wilcox Signed rank test, bivariate analyses, and multivariable linear regression. Covariates included modality of diagnosis confirmation and timing with Dx ID implementation. Results: One hundred pts with MPC ICD coded in the EHR were included, with 29 pts diagnosed by PSMA PET and 71 by conventional imaging. Median time from true MPC diagnosis to first subsequent clinic follow up was < 1 month (IQR 0-2), while median time from true MPC diagnosis to entry of ICD MPC-related code was longer at 4mo (IQR 0-15). 5 pts had C79 applied for N1 disease and 10 pts for work-up of biochemical recurrence. On multivariable analysis of potential factors affecting time interval to MPC ICD entry, Dx ID implementation (b = -6.5 mo [95% CI -1.8 to -11.2], p = 0.007) and non-PSMA based diagnosis (b = -5.7 mo [95% CI -0.5 to -10.8], p = 0.03) were independently associated with shorter time to ICD coding. In subset analysis of the cohort after Dx ID implementation, use of both ICD and Dx ID to identify pts with MPC reduced the median time from true MPC diagnosis to EHR coding (1mo, IQR 0-6.3) compared to ICD alone (2mo, IQR 0-8) (p = 0.003). Conclusions: Timing of MPC ICD entry is highly variable and may carry biases derived from healthcare processes, including data entry and diagnostic testing. This may be improved with EHR workflow interventions. It is essential to have domain knowledge of clinical coding practices to improve information retrieval and recognize potential limitations and biases.