Opinion Recommended long COVID outcome measures and their implications for clinical trial design, with a focus on post-exertional malaise, 2026, Soares

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Recommended long COVID outcome measures and their implications for clinical trial design, with a focus on post-exertional malaise Personal View​


Letícia Soares, Hannah Davis, Ezra Spier, Tiffany Walker, Todd Davenport, David Putrino, Michael Peluso, Julia Moore Vogel,

Received 4 August 2025, Revised 1 December 2025, Accepted 5 December 2025, Available online 19 December 2025, Version of Record 19 December 2025.

What do these dates mean?


https://doi.org/10.1016/j.ebiom.2025.106083
Under a Creative Commons license
Open access

Summary​

Long COVID has created a worldwide public health crisis and has no approved treatments or validated biomarkers.

We summarize the current challenges and considerations of outcome selection in Long COVID trials, along with recommendations for current trial design and future endpoint validation, with a focus on post-exertional malaise (PEM).

We make five overarching recommendations for Long COVID clinical trials:

1) thorough characterisation of baseline disease;

2) collection of longitudinal data;

3) design of a placebo arm to enable comparison of treatment effect relative to the disease natural history;

4) accounting for, and when feasible, measuring PEM;

5) balancing severity, duration, and relevant phenotypes across trial arms and within subgroups to be analysed.

We present a list of outcomes that may be considered for Long COVID clinical trials, with a focus on PEM.

Crucially, the field of Long COVID clinical trials urgently needs funding and research effort investment to develop and validate outcomes concomitantly with clinical trial research.
 
Letícia Soares on LinkedIn https://www.linkedin.com/posts/leti...ng-outcomes-activity-7407740325810814977-V6BA


Happy to share our new paper discussing outcomes for Long COVID clinical trials, with special considerations on post-exertional malaise (PEM). We were deliberate in focusing on PEM because it’s a highly disabling symptom that is common in Long COVID. Although PEM is a hallmark of ME/CFS and a prevalent phenotype in Long COVID, there’s still a lack of understanding on why accounting for PEM matters in study design.

https://lnkd.in/dtSnazhV

In this paper, our super collaborative team makes five key recommendations:
1. Thoroughly characterize patients’ phenotype and baseline symptoms
2. Collect longitudinal data (not just one-time snapshots)
3. Include a placebo arm to compare treatment effects
4. Measure PEM—it can drastically affect trial results
5. Balance trial groups by severity, duration, and phenotype - we want to see subgroup analyses

Taking into consideration that trialists are currently operating in an evidence sparse landscape, we also make recommendations on outcomes to consider for clinical trials, and the limitations and research needs associated with each outcome measure. A lot of work on outcome validation in the context of Long COVID still needs to be done, and for that we need research investment (especially in funding) in outcome development and validation for Long COVID.

As someone living with Long COVID, I want clinical trials that can move the field forward, even if the results are negative. This means robust trial design that can yield conclusive results and can inform the trials that come next.

Hannah Davis, Todd Davenport, David Putrino, Julia Moore Vogel, Ezra S., Tiffany Walker, Michael Peluso
 
Todd Davenport on LinkedIn https://www.linkedin.com/posts/todd...and-medical-activity-7407724109154938880-gLW1

We need better endpoints and more careful research design to succeed in Long COVID research.

Our new article offers 5 key recommendations to improve trial design and accelerate progress:
✅ Characterize the disease thoroughly. Long COVID is highly heterogeneous, leading to highly personalized experiences with it.
✅ Collect longitudinal data. Single time-point snapshots miss the big picture.
✅ Include a placebo arm. Natural disease progression can be variable, which introduces a lot of noise against which to detect a signal.
✅ Measure post-exertional malaise (PEM). This hallmark constellation of symptom and signs that can make or break the validity of a trial.
✅ Balance severity, duration, and phenotypes across arms. Meaningful subgroup analysis depends on comparing apples with apples.

Better validated patient-reported outcomes and biomarkers will help us move forward toward approved tests and cures. In the meantime, we should rigorously use the ones already developed for purpose. And upping investment in preclinical science, network funding, and global collaborations are critical to move the field forward.

Our bottom line: Better endpoints means better trials means faster effective treatments for millions living with Long COVID.

Read the full article here: https://lnkd.in/gCZ6zBCv

Letícia Soares Ezra S. Julia Moore Vogel
 
They recommend lots of questionnaires and even the development of new patient-reported outcome.

How they have missed the use of continuous measurements of activity and body positioning using sensors, and objective long term outcomes like work/education participation, healthcare use, need for help, wages, etc. as proxies of overall health is beyond me.

By following these recommendations, we’ll just end up with more of the same awfully designed trials that will tell us nothing useful.

These people have been in the game long enough. They really should know better by now.
 
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