Transforming growth factor beta (TGF-β) in adolescent chronic fatigue syndrome (2017) Wyller et al.

https://www.ncbi.nlm.nih.gov/pubmed/29202780
https://translational-medicine.biomedcentral.com/articles/10.1186/s12967-017-1350-1

 

There's some useful demographic data included in this study but while Wyller continues to promote his 'sustained arousal' theory (fair enough - it has some face validity) his own previous work suggests that sympathetic inhibition not only doesn't work but may also exacerbate objective impairments in physical activity :

Disease mechanisms and clonidine treatment in adolescent chronic fatigue syndrome: a combined cross-sectional and randomized clinical trial.

https://www.ncbi.nlm.nih.gov/pubmed/24493300

 

Only 38% met CCC criteria, and 73% Fukuda. This study would have been more interesting if they'd studied ME or even CFS. They recruited with Oxford:

Average CFQ score for patients was 19.3 (8.7 for controls), which seems pretty low. Steps walked per day was 4,662 versus 10,293 for healthy controls. Some patients had been sick for as little as 4 months.

For TGF-B1 and B3 comparisons between CFS subgroups (Oxford, Fukuda, CCC) they switched from using mean (average) to using median (middle value) with no explanation. Another group did this in the past with stimulants to hide a big deterioration resulting from the drug.

And here comes the babble:

They have TGF data for individual patients and controls at https://static-content.springer.com.../MediaObjects/12967_2017_1350_MOESM2_ESM.xlsx but not with subgrouping of patients according to criteria they meet, which is what would be needed to do the calculations for the means where they only showed medians.

 

I would generally favor the median as it is more robust to outliers and makes less assumptions about linearity of any scale.

 

In which case they're still using the mean for TGF-B2. The lack of consistency itself is the red flag.

 

Yes and I don't see why they can't quote both.

Sometimes differences between the mean and median are informative in terms of the distribution but it would be better if they gave scatter plots. I thought this was becoming common. That lets the reader see the distribution of the data.

 

Didn't this group disprove the "sustained arousal" hypothesis with several of their studies including a drug trial. Why are they still talking about it?

 

Hard to prove a negative. They tested their theory, and failed to find support for it.... but why give up on it just because of that!!