Today I am receiving several requests to explain we should wait for Trial data before a new routine treatment become standard practice.
First of all, unless a disease has a 100% mortality, association between administration of treatment and survival does not prove causality.

So if we administer a new treatment without evidence, survival does not mean that the treatment caused the outcome. Patients (luckily) survive often. On the other hand, in case of death, the contribution of the treatment to mortality cannot be excluded.

Trials inform about the efficacy and, safety. For example, the #Recoverytrial brought to us very important information about steroids in COVID19. To the ones saying they were using steroids before anyway, did you really know when to start them and when to avoid them?

It is true that every patient is different and that many treatments in our daily practice have not been studied in large trials yet; this however should not be an excuse to try every possible treatment focusing only on the hope of a positive outcome. Harm is possible.

Precision medicine is not about ignoring trials, it is about coping with the uncertainty present in our profession, welcoming results from good research which ultimately adds some degree of precision to our uncertainty.

The fact we are facing a pandemic, it's no excuse to say that we have no time to do research. We have demonstrated that efforts like #RECOVERY or #REMAPCAP can work: adaptive trials that allow us to learn while doing.

Last but not least: if a small percentage of the money spent on unproven treatments was used to create research platforms, I suspect we would be faster and better at doing research and bringing the results to bedside practice.