Background:‘Synthetic’ control arms (SCAs), created using electronic health records (EHRs), have immense potential to augment clinical trial findings and provide a rich context of real-world evidence (RWE) while reducing patient (pt) and sponsor burden (Gottlieb 2019). PICI0002 (PRINCE) is a ph1b/2 study evaluating APX005M with gemcitabine (gem) and nab-paclitaxel (NP) ± nivolumab for the treatment of metastatic pancreatic adenocarcinoma (mPDAC; NCT03214250). PRINCE pts were enrolled from select US academic cancer centers and a global, ph3 study was utilized for an historical reference control (Von Hoff 2013). To address the perceived limitations of this design, we explored the feasibility and utility of developing a contemporary SCA using real-world data (RWD). Methods: The SCA was derived using retrospective pt data from the two highest enrolling participating centers on PRINCE. Pts meeting key PRINCE eligibility criteria, who received gem/NP in the two years preceding the trial start date, were identified using an electronic phenotyping algorithm applied to cancer registry and EHR data, followed by manual review. Baseline characteristics, treatment exposure, efficacy and survival data were extracted electronically and via manual chart abstraction. Data were stored in a REDCap database built and housed by the Parker Institute for Cancer Immunotherapy. SCA pt characteristics were compared with PRINCE and overall survival (OS; time from initiation of gem/NP to death) was compared to historical reference controls (Table). Results: N=68 pts treated with gem/NP meeting PRINCE eligibility criteria were identified. All pts were deceased at the time of analysis. SCA pts had comparable baseline characteristics to PRINCE pts; key differences included inferior performance status and a higher proportion of pts presenting with a de novo mPDAC diagnosis. Median time on gem/NP was 4.8 months (mos; range 0-39). Median OS was 11.5 mos (95% CI 9.0-13.6) and 1-year OS was 43% (95% CI 31-55), in line with historical controls (Table). Conclusions: This study confirms the feasibility and utility of generating a control arm via a semi-automated approach. Current limitations entail manual oversight requirements as well as the known constraints of RWD, including associated biases and lack of available RECIST data. These limitations stand to evolve alongside EHR technologies. SCAs using RWD may help inform the value of prospective data by providing a contemporary reference of RWE. In some circumstances, SCAs may also serve as an alternative to traditional control arms, particularly for well-characterized standard therapies.

*Manually estimated from Kaplan-Meier curve; NR = Not reported.