Menu Back toSession 6: Advanced Statistical Methods to Borrow External Information

DIA/FDA Biostatistics Industry and Regulator Forum

Join us virtually from the comfort of your home/office March 29-31 or watch later at a time that works for you. This event provides access to the materials for a full two months!

Session 6: Advanced Statistical Methods to Borrow External Information

Session Chair(s)

Jerald  Schindler, DrPH

Jerald Schindler, DrPH

  • Vice President, Enterprise Biostatistics
  • Medtronic, United States
Xiang  Ling, PhD

Xiang Ling, PhD

  • Statistician
  • FDA, United States
External Information is incorporated into the statistical analysis of clinical trials in various settings. For example, trials for rare diseases may leverage external data to improve the study power with smaller sample size and oncology trials may use external controls for ethical consideration. Borrowing external information has been mostly used in early phases drug development and has increased usage in phase III trials protocols in recent years. This session will focus on considerations for using external patient-level data in late phase randomized clinical trials to improve statistical power. An overview of advanced statistical methods will be presented and application in clinical trials designs will be discussed through clinical case studies and simulation studies.
Learning Objective : At the conclusion of this session, participants should be able to:
  • Describe the general ideas of various methods to borrow information from external data
  • Explain the assumptions these approaches make
  • Discuss the considerations of the potential applications in regulatory clinical trials


Ben  Saville, PhD

Streamlining Randomized Clinical Trials for Device Therapies in Heart Failure: Bayesian Borrowing of External Data

Ben Saville, PhD

  • Berry Consultants, United States
Robert  Abugov, PhD, MPH, MS


Robert Abugov, PhD, MPH, MS

  • Mathematical Statistician
  • FDA, United States
Roberto  Crackel, PhD, MS


Roberto Crackel, PhD, MS

  • Mathmatical Statistician
  • FDA, United States
Yoonhee  Kim, PhD


Yoonhee Kim, PhD

  • Lead Mathematical Statistician
  • FDA, United States