The DIA Statistics and Data Science Community are pleased to announce that registrations are now being accepted for our next webinar. The Utilization of Historical Trial/Registry Data in Drug Development will be held on17 Nov 2023, 11am - 12:30pm EST and will feature presentations from Dr Melanie Quintana, Direction and Senior Statistical Scientist at Berry Consultants and Dr Tao Lui, Associate Professor at Brown University.
The webinar is free to attend and registration can be completed using this web address:
https://diaglobal.zoom.us/meeting/register/tJUkf--prjkoGNWkAFnDeCODPdctL_5Bg7Vs
We hope to see you there!
Further details on the abstracts can be found below:
Title: Use of PRO-ACT Database in designing and analyzing clinical trials for amyotrophic lateral sclerosis (ALS)
Speaker: Melanie Quintana, PhD; Director and Senior Statistical Scientist at Berry Consultants
There is a growing need to learn from our past in clinical trial design and analysis. In light of this, numerous efforts are being made to promote the creation of shared disease-specific databases with patient-level historical control and observational data. With these efforts in mind, we discuss how we can synthesize and make better use of this historical information to design more informed and powerful clinical trials. Throughout this presentation, we highlight the use of the shared Pooled Resource Open-Access ALS Clinical Trials Database (PRO-ACT) in designing and analyzing clinical trials for amyotrophic lateral sclerosis (ALS). The PRO-ACT database provides patient-level longitudinal data from placebo and treatment arms from over 29 Phase II/III clinical trials and is an exemplary effort to share data and learn from past studies. Access to rich clinical trial patient-level data within the PRO-ACT database provides many advantages in designing and analyzing trials in ALS, including informing the creation of realistic clinical trial simulations to optimize key design elements and supplementing data from randomized trials with external information.
Title: Emulating target clinical trials using real-world databases for treating renal cell carcinoma
Speaker: Tao Liu, PhD; Associate Professor, Brown University
Abstract:
Emulating clinical trials provides an alternative approach to evaluating therapeutic values of a clinical treatment when it is practically difficult or costly to evaluate the treatment effectiveness using standard RCT. Using the National Cancer Database, we emulated separately an index trial of patients with cT1-3cN0cM0 renal cell carcinoma (RCC), designed to resemble EORTC 30881 (“index trial emulation”), and a hypothetical trial of patients at increased risk for lymph node metastases with cT1-4cN0-1cM0 RCC (“high-risk trial emulation”). A propensity score for lymph node dissection (LND) was estimated using preoperative features (Model 1) or preoperative and pathologic features (Model 2). The impacts of LND on overall survival (OS) were estimated using Cox regression on the two emulated trials. In this presentation, I will present an overview of the study design and analyses. The benefits and risks of emulating trials also will be discussed.