Re: Patient Enrollment Modeling
in response to
by
posted on
Dec 09, 2018 09:39AM
Iconoclast,
Your example scenarios for event rates and %RRR look good to me. However, keep in mind that your scenarios are only two of many. Other scenarios are possible, some good some not so good, to explain a stated average event rate for the trial.
While EXAMINE is a good model, it is only one trial and there are too many variables that differ between the patient populations to assume with certainty that placebo populations in EXAMINE and BETonMACE will display similar event rates. EXAMINE and ELIXA were fairly similar patient populations except for the qualifying recent ACS event (w/i 90 days for EXAMINE; 180 days for ELIXA). Despite the similarities, the events per 100 patient years gives about 7.9 and 6.4 for EXAMINE and ELIXA, respectively. BETonMACE has a median time for ACS event to randomization of ~34 days, which is even shorter than in EXAMINE. Furthermore, BETonMACE has low-HDL requirement that was not present in EXAMINE or ELIXA.
Standard of care and treatment guidelines change over time and it is reasonable to expect that management of the risk factors for type 2 diabetes recent ACS patients has changed over time between past completed EXAMINE/ELIXA trials and ongoing BETonMACE. Some drugs for treating residual MACE risk in T2D may not have been available or not commonly used in patients during EXAMINE/ELIXA but may be more commonly used in BETonMACE patients, including the SGLT2 inhibitors, GLP1-R agonists, PCSK9 antibodies and Vascepa/other omega 3 drugs.
The event rate dropping over time is not necessarily due to apabetalone. Recent ACS patients are at highest risk of next MACE event within the first several months of follow up. BETonMACE has been fully enrolled since March 2018 and the median dosing period of BETonMACE is expected to end up ~2 years. Therefore, patients are now past the most high risk period of experiencing a subsequent MACE and a drop in the observed events per 100 patient years is expected.
Lastly, uncertainties about status and target patient years confound projections of timing.
BearDownAZ