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2051 Background: Randomized clinical trials use stringent eligibility criteria to select patients which can raise concerns about generalizability of study results. Recent interest in external controls and new trial designs has increasingly focused on the possible use of real-world data sources. We examined potential differences of survival outcomes in clinical trial and real-world datasets in newly diagnosed glioblastoma. Methods: Patient-level data from 4 independent datasets were analyzed. Non-trial data were derived from an institutional dataset of 453 patients with newly diagnosed glioblastoma treated outside of a clinical trial with standard radiation therapy with concurrent and adjuvant temozolomide at a large academic center. Trial patients included patients on the control arm of several multi-institutional trials (NCT00689221, n = 273; NCT00813943, n = 89; NCT00943826; n = 459) and patients treated on trial at our institution (n = 210). Non-trial patients were compared with each of the 4 clinical trial datasets in pairwise comparisons with Cox regression with adjustments for age, sex, extent of resection, KPS and MGMT status. Results: Patient-level data from 1,484 patients were analyzed. Non-trial patients were older compared to patients in the multi-institutional trials (mean 58.6 vs. 56.1 years (NCT00943826), 53.9 years (NCT00813943), 55.7 years (NCT00689221); p < = 0.001). The non-trial cohort had fewer women (43.5% vs. 35.9%, p = 0.02), greater proportion of lower KPS patients (47% KPS 0.05). Conclusions: Glioblastoma patients treated on multi-institutional clinical trials that were included in our analysis did not have statistically significant differences in survival compared to patients treated outside of a clinical trial at a large academic center after adjustment for relevant variables. Our findings support the possible use of real-world data in the development of external control arms for future trials in newly diagnosed glioblastoma. [Table: see text]

We created a database of reconstructed patient-level data from published clinical trials that includes multiple time-to-event outcomes such as overall survival and progression-free survival. Outcomes were extracted from Kaplan–Meier (KM) curves reported in 153 oncology Phase III clinical trial publications identified through a PubMed search of clinical trials in breast, lung, prostate and colorectal cancer, published between 2014 and 2016. For each trial that met our search criteria, we curated study-level information and digitized all reported KM curves with the software Digitizelt. We then used the digitized KM survival curves to estimate (possibly censored) patient-level time-to-event outcomes. Collections of time-to-event datasets from completed trials can be used to support the choice of appropriate trial designs for future clinical studies. Patient-level data allow investigators to tailor clinical trial designs to diseases and classes of treatments. Patient-level data also allow investigators to estimate the operating characteristics (e.g. power and type I error rate) of candidate statistical designs and methods. Database URL: https://10.6084/m9.figshare.14642247.v1