The Prevention and Treatment of Missing Data in Clinical Trials

The Prevention and Treatment of Missing Data in Clinical Trials Blog
November 1st – 2nd 2011, Iselin, New Jersey
by Andrew Grannell

This was a short course, organised be Daniel Scharfstein and held in New Jersey, aimed at statisticians in pharmaceutical industry to inform and discuss the new National Academy of Science on Statistics’ report on how to prevent and treat missing data in clinical trials. Several members of the panel attended the short course to discuss the new recommendations. Also in attendance were two representatives from the Food and Drug Administration, Robert O’Neill (Senior Statistical Advisor to the CDER, FDA) and Thomas Permutt (Director at the Division of Biometrics II, CDER, FDA).

On the first morning, the course started off with Robert O’Neill giving some background information on how the panel was formed and what its task was. The panel from the National Academy of Science on Statistics were tasked with developing some recommendations for the FDA on how to approach the prevention and treatment of missing data in clinical trials. They were asked to prepare “a report with recommendations that would be useful for FDA’s development of guidance for clinical trials on appropriate study designs and follow-up methods to reduce missing data and appropriate statistical methods to address missing data for analysis of results.”

The next speaker was the chairman of the panel, Roderick Little (Associate Director for Research and Methodology, and Chief Scientist, U.S. Census Bureau). He presented a very good and clear overview on the design, conduct and analysis issues that currently exist. Following the break, Thomas Permutt gave great insight into his opinion on where the FDA’s position is on the prevention and treatment of missing data. He felt they were moving in the right direction towards reviewing new methods on handling missing data analysis. Daniel Scharfstein then presented an overview of some of the practical case studies they were going to present, which helped put this course into perspective on a very practical level.

After lunch, both Jay Seigal (Chief Biotechnology Officer and the Head of Pharmaceutical Global Regulatory Affairs, Johnson & Johnson) and James Neaton (Professor of Biostatistics, School of Public Health, University of Minnesota) gave very interesting talks on the prevention of missing data. Jay spoke about the design aspects that could help reduce missing data and James spoke about methods in how to efficiently approach the data management and site personnel side of collecting data for clinical trials.

For Day 2, Daniel had organised a much more intense day of presentations, involving the heavy theory behind these very impressive methods of handling missing data analysis. In that respect, the second day was very appropriately kicked off with a presentation by Rod Little on defining missingness, missing data patterns, inverse probability weighting (IPW), likelihood methods, multiple imputation and sensitivity analysis.

Daniel Scharfstein gave a very interesting and comprehensive presentation on the methodology of sensitivity analysis and gave great weighting to its importance. His presentation outlined that sensitivity adds a certain degree of verification to results obtained. The first case study of the course was given by Joe Hogan (Professor and Director of Graduate Studies, Department of Biostatistics, Brown University). He outlined a very detailed and comprehensive approach to the analysis of missing data in this case. It helped put the material covered during the first day into perspective when approaching a real clinical trial. The second case study was presented by Daniel Scharfstein. Again, with this case study a very detailed and comprehensive approach was outlined and explained very well.

The last presentation of the short course was given by Rod Little. He outlined any other considerations such as clarification of specific characteristics encountered in clinical trials and collecting data. There were also a string of very interesting Q&A sessions after each presentation. There were very open and engaging discussions held between the panel and the attendees on various topics encountered in the pharmaceutical industry today. To sum up, it was a very successful course and gave great insight into the future of prevention and treatment of missing data in the pharmaceutical industry.