TechGuru, I find this conversation extremely in

TechGuru,

I find this conversation extremely interesting. Hope you don't mind me picking your mind. You stated,

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In our case, if some patients are switched over to another arm, or Lero’s arm, two conditions will be violated: the number of observations will not be fixed and the probability of success will not be the same for each outcome as patients that need to be retired will not count in the “failure” outcome, biasing the results against Leronlimab arm.

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It's counterintuitive to think we'd move patients over to Leronlimab and that would bias results against Leronlimab. I think this is a high probability given the severity of these patients and doctors being unwilling to risk their patients' lives with near certain death knocking on their doors. Plus, they need the beds/ventilators for the next severe patient.

Then, you stated,

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If this is this case, patients will be effectively "re-assigned" in sequential order (depending on patients well being) FDA could stop the trial when a predefined endpoint is reached. This is called curtailed sampling.

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Are you saying patients on Leronlimab will be taken off Leronlimab (because they're doing better) and returned to placebo? How do the doctors even know what arm the patient is in if it's double blinded? Would love a little clarity here. If I was a family member, I'd have a fit.

Then, you stated,

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Under curtailed sampling, the range of the sample size can be smaller. For example, they observe that some patients in the placebo arm have to be switched to other treatment, and this happens with much less patients in the Lero arm as they are doing well (surviving). They can stop the trial short and determine that Leronlimab achieved statistical significance.

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In the long run, does this undermine our data when science looks back at the statistics? Wouldn't a smaller sample size lead to lower statistical relevance/study power? Or, does the world just throw out statistics when the control group's patients improve greatly vs placebo?

Thank you for providing great insights.