Commentary: confidentiality of interim trial data-the emerging crisis.

Randomized controlled clinical trials (RCTs) represent the pinnacle of evidence used by clinicians and regulators to determine the effectiveness of therapeutic interventions. The importance of RCTs is so universally accepted that clinical practice guidelines for many fields of medicine assign the highest rating for quality of evidence (Class 1A) to recommendations supported by data derived from multiple RCTs. Similarly, regulators have generally required evidence derived from RCTs for approval of pharmacological interventions. These policies ensure that the therapies approved by regulatory agencies and endorsed by professional societies actually deliver the benefits promised to patients. Now, after decades of application, this paradigm is threatened by a looming crisis related to the ability to conduct cardiovascular safety trials of diabetes drugs using the highest standards of scientific integrity. As described by Fleming in this edition of Clinical Trials, maintaining the confidentiality of data for interim results from ongoing clinical trials is essential to maintaining the feasibility and reliability of these crucial studies. The current threat to clinical trial integrity arises from a regulatory crisis that emerged during the past decade. The US Food and Drug Administration (FDA) and global regulatory authorities traditionally approved diabetes drugs based primarily upon the ability of these agents to lower blood sugar in the absence of any apparent toxicity. Diabetes drugs were typically evaluated based upon short-term trials (6–12 months) showing a reduction in glycohemoglobin levels, a measure of average blood glucose values over the previous 3 months. In actual practice, most sponsors, to mitigate the risk of demonstrating toxicity, conducted relatively small trials (total sample size about 3000 patients) in populations with a predicted low likelihood of adverse clinical outcomes. However, like most surrogate outcomes, the use of average blood glucose values to approve diabetes drugs carried considerable theoretical risks. A therapeutic intervention could lower blood glucose, but worsen other important outcome measures, which would go undetected in the small, short-term trials conducted with glycemic endpoints. That’s exactly what happened. In 2005, the diabetes drug muraglitazar was presented to an FDA Advisory Panel, and a recommendation for approval received nearly unanimous support. A few weeks later, we published a meta-analysis of the clinical data presented to the FDA Panel, which showed an approximate doubling of the risk of major adverse cardiovascular events (MACE) in patients treated with muraglitazar compared with placebo or other glucoselowering therapies. Then, 2 years later, we published a meta-analysis of cardiovascular outcome data for an approved and widely prescribed drug, rosiglitazone, showing evidence for increased MACE. This latter publication resulted in considerable controversy with alarming newspaper headlines, Congressional inquiries, and public outcry. A consensus emerged that approval of diabetes drugs primarily on the basis of glucose lowering (without additional cardiovascular outcome data) was no longer tenable. Accordingly, the FDA assembled an advisory panel in 2008 to consider what changes in regulatory policy, if any, were needed. Two participants in that advisory committee meeting, Dr Fleming as a panel member and me as an invited speaker, proposed a new paradigm for diabetes drug approval. The approach we advocated was carefully designed to balance the need to approve new drugs for diabetes in a timely fashion with the compelling societal interest in making certain such drugs did not increase adverse cardiovascular outcomes. We weighed the risks and benefits of several approaches, including requiring a large-scale RCT prior to approval, but ultimately proposed a strategy that would require sponsors to rule out an upper 95% confidence interval (CI) for the hazard ratio (HR) for MACE of 1.8 prior to approval and an