@vasillos, @Stezza, OK, thank you, the power of the HC message board.

So, it allows us to take a fresh look at the Richardson et al study used by Mesoblast to derive the mortality rate for comparison with the EAP.

Richardson looked at all of the C-19 admissions to 12 NYC hospitals during the period March 1 to April 4, so about 5 weeks. Note that the Mesoblast EAP started on April 6 just 2 days later, so it's a good indicator that treatment/ventilator protocols were essentially the same.

Richardson started with 5700 patients who were admitted and he then took the subset of patients who either died or were discharged back home. From 5700 we're down to 2,634. He further broke out the ones who were admitted to the ICU and placed on a ventilator and either died or were discharged home. We're now down to 320 patients who either died or were discharged home during the period March 1 through April 4. Of the 320 ICU ventilator patients, 282 died and 38 were discharged home. That's where the 88% mortality rate comes from (282/320).

Another way to think of it is that for every ICU ventilated patient who was successfully treated and discharged home there were 7.42 ICU ventilated patients who died. Being on a ventilator in an ICU with Covid-19 in March 2020 was not good for one's health.

So, another way to look at the Mesoblast data in line with Richardson would be that 12 patients were on a ventilator and 9 either died or were discharged home. The mortality rate using Richardson parameters drops from 88% (282/320) to 22% (2/9). For every patient successfully treated and discharged home there are now just 0.28 patients who die, a tremendous drop from 7.42.

For fun I ran a simple 2x2 chi square calculation

Chi-Square Calculator

Success! The contingency table below provides the following information: the observed cell totals, (the expected cell totals) and [the chi-square statistic for each cell].

The chi-square statistic,p-value and statement of significance appear beneath the table. Blue means you're dealing with dependent variables; red, independent.

You'll notice we've also calculated a chi-square statistic with the popular Yates correction. There's probably a consensus now that the correction is over-cautious in its desire to avoid a type 1 error, but the statistic is there if you want to use it.

Want to know how to report the result of your chi-square test (APA style)? (Opens in a new tab so you don't lose your result.)

How to Report a Chi-Square Result

	Died	Discharged	Marginal Row Totals
Not Treated	282 (276.23) [0.12]	38 (43.77) [0.76]	320
Remestemcel-L	2 (7.77) [4.28]	7 (1.23) [27.04]	9
Marginal Column Totals	284	45	329(Grand Total)

The chi-square statistic is 32.2007. Thep-value is < 0.00001. Significant atp< .05.

The chi-square statistic with Yates correction is 26.8609. Thep-value is < 0.00001. Significant atp< .05.

Needless to say a p-value LT 0.00001 is highly significant. The "Died" column is a rough marker for the primary end-point of 30-day all-cause mortality in the 300-patient phase 3 trial. Of course, here the rem-L group only had 18 days, not 30 days. And the DMC will be looking at other parameters besides death vs discharged. But if we continue to see this great of a difference between rem-L and placebo, I believe the DMC will indeed have to call the trial at the 90-patient interim check-point. Thanks to both of you for the feedback.