Lessons from TGN 1412 - Applied Clinical Trials

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Lessons from TGN 1412 How applying statistics to the design, conduct, and analysis of Phase I trials can improve clinical research.

Source: Applied Clinical Trials



Stephen Senn
On the morning of March 13, 2006, eight healthy volunteers forming the first cohort of a planned group escalation study of TeGenero's monoclonal antibody TGN 1412 at a Phase I clinical research facility adjacent to Northwick Park Hospital were given their treatment. Within a short period of time, the six men who had been allocated to TGN 1412 began showing signs of an adverse reaction. In fact, they were all showing the first signs of a severe cytokine storm. By that evening, all six had been admitted to intensive care.

None of the six died as a result of the treatment, but all suffered severe adverse reactions—and in some cases, these have had long-term consequences on their health.

TeGenero aftermath

This was possibly the most dramatic example of adverse events due to pharmaceuticals since the thalidomide tragedy of the early 1960s and the incident attracted considerable media attention for several days. It was also, of course, the cause of much scientific debate and regulatory discussion and the impact is clearly being felt in Europe in regulatory legislation and guidance for Phase I studies.

One of the bodies that reacted was the Royal Statistical Society (RSS), which set up a working party under my chairmanship to make recommendations from a statistical perspective as to what might be done to improve the design, conduct, and analysis of such trials. That this is a relevant concern of a statistical society might come as a surprise to readers of Applied Clinical Trials, but it will not surprise most statisticians.


Study Outcome in a Conventional Format
First, the RSS has a tradition of commenting on matters of public interest. Indeed, more than 15 years ago a working party of the RSS looked at the issue of the competence of European drug regulatory agencies in statistical matters1 and came to the conclusion that there was an urgent need for them to employ statisticians. One should not mistake subsequence for consequence, but it is widely believed that the report was influential in improving the regulatory position—although an important impetus was also given by the International Conference on Harmonization (ICH). Whatever the reason, it is certainly now the case that many European regulatory authorities (but not all) employ statisticians.

The second point is that statistics is, of course, highly relevant to the analysis of Phase I studies and, inevitably, their design—although in view of the cursory and often ambiguous statements on intended analysis of Phase I studies, one would hardly think so. Of course, when several individuals suffer severe cytokine storms within a few hours of administering a monoclonal antibody, you do not need a formal statistical analysis to tell you what happened. Indeed, a conventional statistical analysis would be extremely misleading, as it would ignore most of the information. For example, Table 1 summarizes the outcome of the study in conventional form.

Such a table is conventionally analyzed using Fisher's exact test, which yields a one-sided P-value of 0.036, which—clearly—does not remotely begin to do justice to the situation. The point is that such an analysis makes no use of the fact that the background rate of such events is extremely rare. This might perhaps be appropriate when analyzing the occurrence of the sort of common and nonserious "nocebo" effects, such as headache or upset stomach, that could also easily occur under placebo.

Case in points

So, we are all agreed that you do not need statistics to work out that TGN 1412 was poison in the doses administered. However, that is not the point. First, such clinical trials are not designed with the expectation that they will have the sort of disastrous and dramatic conclusion that the trial of TGN 1412 did. On the contrary, this sort of outcome, while it cannot be excluded, ought to be extremely rare.


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