This is not authoritative but the result of few minutes Google effort so take with some salt. I have extracted text below from the following link:

 http://onbiostatistics.blogspot.com/2016/12/

 “In clinical trial protocols, we usually specify one or more primary efficacy endpoints, then a list of secondary efficacy endpoints, and then more tertiary endpoints or exploratory endpoints. It is pretty standard that the primary efficacy endpoints are those the hypothesis testing or inferential statistics and sample size estimation are based on. If we have more than one primary efficacy endpoints, we will need to adjust for multiple tests or multiplicity. It is also clear that the tertiary or exploratory endpoints are for hypothesis generating or more bluntly for fishing expedition.  

In FDA’s guidance for industry “Clinical Studies Section of Labeling for Human Prescription Drug and Biological Products — Content and Format”, there is a statement about the primary and secondary endpoints:

§   Primary and Secondary Endpoints: The terms primary endpoint and secondary endpoint are used so variably that they are rarely helpful. The appropriate inquiry is whether there is a well-documented, statistically and clinically meaningful effect on a prospectively defined endpoint, not whether the endpoint was identified as primary or secondary.”

Here is the kill shot:

 “FDA does not care whether or not a study endpoint is called primary or secondary. However, if the information from these endpoints are used for supporting evidence and for product label, the endpoints need to be predefined and tests for these endpoints need to be controlled for the overall alpha or overall type I error.”

My interpretation of this is that BETonMACE could be used to support approval for apabetalone on the basis of one or more of the secondary outcomes if it (or they) can be demonstrated to result in a significant improvement in that (those) outcome(s).  That’s the good news. The bad news is that the more outcomes (and BoM has a lot of them) that are tested, the harder it becomes to reach significance.  Even worse news is that BoM wasn’t necessary powered to achieve a significant result in all of the secondary outcomes. 

For example, at the beginning of the trial, there were only 262 patients with eGFR values between 30 and 59 – this is the group being tested for CKD.  They had an average age of 71 (the average age of patients in the full BoM trial was 62).  Hopefully, CKD patients were randomized to placebo and apabetalone independent of randomization in full trial, with the result that exactly half went into each group, but that is not clear. At any rate, it is a small, old group of patients that may have experienced a high dropout due a variety of health factors.  On top of that, the test for significance is going to be tougher than just meeting P=0.05 in a single outcome test.

The more I think about the multitude of health challenges faced by BoM participants, the more I think that ‘all cause death’ might be most likely outcome met with significance.  That would be marvelous because it is the best possible result (an overall reduction in mortality in a patient group at high risk of death from a wide variety of causes) and because it is consistent with the observations that apabetalone affects many dysregulated inflammatory pathways.

Jupe