How to design future studies of systemic exercise intolerance disease (chronic fatigue syndrome)?

Someone named Ramsey writes on behalf of a self-managed support community of 100+ systemic exercise intolerance disease (SEID) patients. He read my recent article on the topic and had a question regarding the following excerpt:

For conditions like S.E.I.D., then, the better approach may be to gather data from people suffering “in the wild,” combining the careful methodology of a study like PACE with the lived experience of thousands of people. Though most may be less eloquent than Rehmeyer, each may have his or her own potential path to recovery.

Ramsey asks:

From your perspective, are there particular design features to such an approach that one should prioritize, in order to maximize its usefulness to others?

Here’s the challenge.

The current standard model of evaluating medical research is the randomized clinical trial with 100 or so patients. This sort of trial is both too large and too small (see also here): too large in there is so much variation in the population of patients, and different treatments will work (or not work, or even be counterproductive) for different people; too small in that the variation in such studies makes it hard to find reliable, reproducible results.

I think we need to move in two directions at once. From one direction, N=1 experiments: careful scientific evaluations of treatment options adapted to individual people. From the other direction, full population studies, tracking what really is happening outside the lab. The challenge there, as Ramsey notes, is that a lot of uncontrolled information is and will be available.

I’m sorry to say that I don’t have any good advice right now on how future studies should proceed. Speaking generally, I think it’s important to measure exactly what’s being done by the doctor and patient at all times, I think you should think carefully about outcome measures, and I think it’s a good idea to try multiple treatments on individual patients (that is, to perform within-person comparisons, also called crossover trials in this context). And, when considering observational studies (that is, comparisons based on existing treatments), gather whatever pre-treatment information that is predictive of individuals’ choice of treatment regimen to follow. For SEID in particular, it seems that the diversity of the condition is a key part of the story and so it would be good to find treatments that work with well-defined subgroups.

I hope others can participate in this discussion.

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