Too many unknowns at this point to read into the tea leaves, in my opinion. "The longer, the better" logic is based on the ideas that: 1) Resverlogix and the Clinical Steering Committee accurately predicted the 3-point MACE event rate in the control (placebo) group; and 2) Apabetalone is eliciting a much more robust relative risk reduction than originally projected (30%) in trial designs. Therefore, if #2 is more robust than planned, then the 3-point MACE events contributed by the apabetalone treated patients would be slower.

Although the above logic makes sense, the actuality of this scenario is weaked by the statement by Resverlogix that "Projected primary MACE rate still 8.0 per 100 patient years on top of aggressive standard of care." When asked about this, Clayton replied "yes the actual events we are observing in the blinded analysis from BETonMACE is close to 8 per 100 patient years as we had planned. As you know this trial remains blinded and therefore, we do not have any access to who is on placebo or who is on drug, so these numbers are derived from all patients." So if one accepts that the observed event rate in BETonMACE is as planned, then one would not expect the trial to take any longer than planned. So the "the longer, the better" logic would go out the window from this perspective.

The SSRA isn't so much concerned with the # of 3-point MACE events from the apabetalone arm, or the rate to accumulate 250 3-point MACE events. The SSRA is conducted by an independent statistical team, analagous to the independence of the DSMB. If I recall, the SSRA was pre-defined in the trial protocol and allows for an increase in sample size of up to 50% compared to the originally planned sample size and for an increase of up to 50% of the original number of target 3-point MACE events. Most likely, if the interim data is clearly favorable or unfavorable, then the SSRA will result in a continuation of the original sample size. Data that are promising, but not as strong as favorable, may result in a sample size increase.

Probably more info than you want, but here's a good ref on sample size calculation:

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5037946/