Hi Lawrence
Your paper is great. It asks whether doctors should treat patients with a novel disease that is manifesting as a previously established clinical syndrome the same way they have always treated the syndrome. For example, COVID is a novel disease that can cause ARDS (a long-recognized clinical syndrome). When the pandemic began, was it reasonable for doctors to extrapolate ventilation strategies that had been established through RCTs involving patients with non COVID-related ARDS to patients with COVID-related ARDS?
Historically, part of the reason that we might assume that treatment efficacy is generalizable across many types of patients is that we’ve been taught that qualitative interactions between patients and treatments tend to be rare. If a treatment shows efficacy in an RCT, we consider it unlikely that there could be a sizeable subset of patients who might be harmed by the treatment (other than perhaps through rare immunologic or genetically-based idiosyncratic reactions). We’ve been much more willing to accept the possibility of quantitative interactions (i.e., the idea that the treatment might simply benefit some groups of patients more than others). If one patient winds up with an ejection fraction of 20% after PCI for STEMI, while another winds up with a fairly normal ejection fraction, we don’t usually consider that the PCI might have harmed the first patient. Rather, we’re more likely to conclude that the PCI just didn’t help the first patient as much (possibly because the territory affected by his occlusion was larger or his door-to-balloon time was too long).
But syndromes are not discrete clinical events like myocardial infarctions. Multiple diverse disease processes can all produce the same syndrome (e.g., ARDS can be caused by pancreatitis or trauma or bowel bowel perforation or bacterial sepsis…). Should we more seriously entertain the possibility of qualitative interactions when we’re considering the efficacy of treatments directed at syndromes?
You describe concern, near the start of the pandemic, that previously-established ARDS ventilation strategies were not working as well as expected. Clinicians’ impressions were that fatality rates among patients with COVID-related ARDS seemed higher than fatality rates among historical patients with other aetiologies for their ARDS (?) In this situation, it was reasonable to ask whether the established ventilation protocols were not just not helping as much as expected, but whether they were actually making outcomes worse than they might have been if an alternate strategy had been used. Complicating any assessment of cause and effect would have been the fact that many factors aside from ventilation strategy can potentially impact the prognosis of critically ill patients.
You propose that doctors need a way to identify, in real-time, whether an established treatment approach might not be having the expected effect in the context of a novel disease. Since ARDS has a high mortality rate and patient deaths are not unexpected, signals of lack of efficacy (or even harm) for an old approach in a new disease context might be missed unless group-level data can be obtained rapidly.
It sounds like one solution you’re proposing is to proactively collect granular data on the clinical trajectories of patients treated with established approaches to clinical syndromes. If we could develop libraries of such data, then later, when treating patients presenting with a novel disease (e.g., COVID-related ARDS), we could check to see whether the new patients’ trajectories are similar to the trajectories we saw in previous patient cohorts. If the trajectories of the new patients appeared less favourable, then maybe this could serve as a signal for doctors to step back and re-evaluate their approach. And maybe this type of lack of efficacy/safety signal could create the clinical equipoise needed to justify rapid recruitment to a large RCT examining different treatment approaches.
Ultimately, you seem to be asking whether the potential for qualitative interactions between patients and treatments might be more important to consider when doctors are treating clinical syndromes like ARDS, rather than diseases with a uniform etiology (like CAD). Please correct me if the above summary is mangled.