This is a bit of a fascinating application of clinical informatics – using retrospective patient cohorts and propensity matching techniques to reduce the need for placebo groups in future trials.
This is work done by Pfizer on their own internal database, to address the ethical and financial concerns regarding recruiting large populations for new clinical trials. For example, if you’re testing a new diabetes medication – do you really need a new control group, or can you sort of re-use the control group you had from the previous trial? The answer of course, has traditionally been no – but their answer is yes-and-no. Using their database of over 24,000 trials, they were able to identify 4,075 placebo-controlled groups, with varying degrees of data integrity, crossover, and parallel status. They then suggest these groups could be used, when appropriate, as comparators in future studies in the same domain.
This is certainly an interesting application of clinical informatics – creating temporal databases of clinical trial patients with the potential to augment the evaluation of new medications. What’s nice is that these authors appropriately recognize the limitations of such a database, noting it may only supplement, not replace placebo arms in future trials.
“Creation and implementation of a historical controls database from randomized clinical trials”
www.ncbi.nlm.nih.gov/pubmed/23449762