Quality of remdesivir trials

[f2harrell]

I note that the McCreary & Angus editorial you cite contains a major misunderstanding of ordinal outcome scales. Such scales simply do not assume equal severity spacing across levels of the scale.

@pmbrown

i enjoyed reading it and should reread it, but isnt it ironic that you quote senn because he has been critical of that measure: “Random sampling does not take place in clinical trials and overlap measures make most sense in a sampling context” (senn 2011)?

I’m not seeing how that context relates to ours.

@pmbrown

t’s difficult to translate the scale “into a clinically meaningful statement for patients, clinicians, and policy makers" then i regret the wasted cost on a trial that had little chance of producing a result that could be readily accepted/communicated and instead incites debate

@pmbrown

Our analysis shows that most trials testing new treatment options for SARS-CoV-2 include a surrogate measure which may or may not predict clinical benefit.” etc

These are very physician-centric views of the world IMHO, as if what matters to patients is not relevant. It also assumes that a worsening condition is not sufficiently predictive of a tendency to have clinical events. On the first point we know from the international survey of thousands of patients that they place great weight on shortness of breath.

The progression-free survival issue is a good one to bring up, but there are two differences: (1) we have a lot of data showing how reducing progression does not lead to improved survival, for many cancers/treatments; and (2) in a chronic disease requiring long-duration expensive treatment and long-term follow-up patients have different utility functions. In many cases patients have elected to sacrifice quality of life voluntarily and have put their emphasis on life extension.

To keep the good discussion going, here is way of stating it that is a slight exaggeration: You would rather spend the time and resources to do a 7,000 patient COVID-19 clinical trial on a mortality endpoint than do a 700 patient trial on a full-spectrum ordinal endpoint. You would wait for 7,000 patients to jettison ineffective treatments instead of stopping early for futility with fewer than 700 patients with a multi-level ordinal endpoint just because it takes a bit more time to interpret.

And what is so hard to interpret about an ordinal outcome? SImplifying to 5 outcomes levels (at home with no shortness of breath, at home with significant shortness of breath, hospitalized, invasive ventilation, death), the interpretation of the trial can be stated these ways simultaneously:

• The estimated probability that a randomly chosen patient given treatment B has a better clinical outcome than a randomly chosen patient on treatment A is 0.7
• The estimated probabilities for treatments A and B of the patient having significant shortness of breath or worse are x.xx and x.xx
• The probabilities of the patient needing hospitalization or worse are x.xx an x.xx
• The probabilities of needing invasive ventilation or dying are x.xx and x.xx
• The probabilities of death are x.xx and x.xx
• The Bayesian posterior probability that treatment B affects mortality differently than it affects shortness of breath, hospitalization, or need for a ventilator is x.xx