Jane Yakowitz writes:
Vioxx, the non-steroidal anti-inflammatory drug once prescribed for arthritis, was on the market for over five years before it waswithdrawn from the market in 2004. Though a group of small-scale studies had found a correlation between Vioxx and increased risk of heart attack, the FDA did not have convincing evidence until it completed its own analysis of 1.4 million Kaiser Permanente HMO members. By the time Vioxx was pulled, it had caused between 88,000 and 139,000 unnecessary heart attacks, and 27,000-55,000 avoidable deaths.
The Vioxx debacle is a haunting illustration of the importance of large-scale data research. Dr. Richard Platt, one of the FDA’s drug risk researchers, described a series of “what if” scenarios in 2007 FDA testimony. (Barbara Evans describes the studyhere.) If researchers had had access to 7 million longitudinal patient record, a statistically significant relationship between Vioxx and heart attack would have been revealed in under three years. If researchers had had access to 100 million longitudinal patient records, the relationship would have been discovered in just three months. Of course, if public health researchers did post-market studies that looked for everything all the time, many of the results that look significant would be the product of random noise. But even if it took six months or one year to become confident in the results from a nation-wide health research database, tens of thousands of deaths may have been averted.