Trends In Pro Reporting In Clinical Trials Leading To Gu Cancer Drug Approvals From 2007 To 2018

641 Background: Having standardized and high quality reporting of patient reported outcomes (PRO), especially in clinical trials that establish standards of care in oncology is important for patient centered care. This study assessed the status of reporting and quality of analysis of PROs in FDA approved drugs for genitourinary malignancies. Methods: We conducted a systematic review of the FDA archives to identify urological cancer drugs approved between 2007-2018. We retrieved the clinical trials that led to these drug approvals from ClinicalTrials.gov and PubMed. We systematically screened for PROs and reviewed their analytic tools and interpretation methods reported in their published manuscripts and study protocols. A clinical trial was considered to include PROs if they were reported in either the primary or a subsequent manuscript. Results: We identified 22 clinical trials leading to FDA approval of urological cancer drugs between 2007-2018. Only 63% of trials had published PROs. PROs were reported in the primary clinical trial manuscripts for two drugs (9%), and in a secondary PRO manuscript for 12 drugs (54%). The median time between the primary and secondary papers was 12 months (IQR:7.5-26 months). Among the 14 published PRO papers, the hypothesis was broad in 79%, and not reported in 21%. PROs were never included as a primary endpoint of a study. Instead, PROs were reported as secondary endpoints in 5 (36%) and as exploratory endpoints in 7 (50%) studies, while two papers (14%) did not mention PRO reporting in their endpoints. The most common PRO instruments were EQ-5D (64%) and FACT-P (50%). In 92% of PRO papers, statistical analyses were conducted to account for missing data. Control for type I error was needed but not done in 57% of the trials. Conclusions: Delays in publication of PROs occur regularly in trials leading to drug approval in GU malignancies. Our study highlights the need to enhance standardization of the analysis and interpretation of PROs to maximize the value of this data for drug development and approval.