A secure distributed logistic regression protocol for the detection of rare adverse drug events.
There is limited capacity to assess the comparative risks of medications after they enter the market. For rare adverse events, the pooling of data from multiple sources is necessary to have the power and sufficient population heterogeneity to detect differences in safety and effectiveness in genetic, ethnic and clinically defined subpopulations. However, combining datasets from different data custodians or jurisdictions to perform an analysis on the pooled data creates significant [...]
Author(s): El Emam, Khaled, Samet, Saeed, Arbuckle, Luk, Tamblyn, Robyn, Earle, Craig, Kantarcioglu, Murat
DOI: 10.1136/amiajnl-2011-000735