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Rethinking ME/CFS Diagnostic Reference Intervals via Machine Learning & Utility of Activin B for Defining Symptom Severity (2019) Lidbury et al.

Discussion in 'ME/CFS research' started by John Mac, Jul 19, 2019.

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  1. John Mac

    John Mac Senior Member (Voting Rights)

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    https://www.mdpi.com/2075-4418/9/3/79
     
    Last edited by a moderator: Jul 19, 2019
    John Mac, Jul 19, 2019
    #1
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  2. Sly Saint

    Sly Saint Senior Member (Voting Rights)

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    Looked up 'Random Forest modelling' on wikipedia ....none the wiser, way too complex ;
    I was hoping for something more along the line as 'life is like a box of chocolates':confused:
     
    Sly Saint, Jul 19, 2019
    #2
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  3. Subtropical Island

    Subtropical Island Senior Member (Voting Rights)

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    Which are the “five routine pathology blood test markers that collectively predicted ME/CFS” over half the time?
    Does it say?
     
    Subtropical Island, Jul 20, 2019
    #3
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  4. Ravn

    Ravn Senior Member (Voting Rights)

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    Can anyone explain this seeming contradiction? My brain simply computes this as illogical - what have I misunderstood?

    1) A previous study found higher activin B in ME than HC.

    2) They changed the test to better detect low levels of activin B.

    3) The new study found lower activin B in ME than HC.

    The authors say the change in the test could explain the different results. But, based on the first study, shouldn't the more sensitive test have found more low results in the HC, not in ME?

    Another brain teaser: several of the results in the tables show the same unintuitive pattern we have recently seen in at least 2 other studies (McGregor and ???), namely that more severely affected patients look more like HC than less severely affected patients. This weird pattern is beginning to look like more than just a coincidence.
     
    Ravn, Jul 20, 2019
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  5. Ravn

    Ravn Senior Member (Voting Rights)

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    I think they mean these (but I got rather muddled trying to read this paper so please correct if I'm mistaken):
     
    Ravn, Jul 20, 2019
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  6. Andy

    Andy Committee Member

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    Less severely affected still trying to be more active so more likely to be in a rolling PEM state, whereas the more severely affected are forced to pace themselves far more to avoid that state due to how much more it would affect them?
     
    Andy, Jul 20, 2019
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  7. Forbin

    Forbin Senior Member (Voting Rights)

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    Wild guess - perhaps the test reflects "stability." Healthy controls and severe patients may both represent "stable" states (one of which is highly impaired). It might be that the patients that fall between these two extremes are "unstable," with the test results somehow reflecting that ongoing struggle. It would be somewhat like Dr. Klimas' bi-stable hypothesis.

    1 & 3 are stable, but 2 is caught between forces pulling it in both directions (2 is also impaired, but not as much as 3).

    1234.jpg
     
    Last edited: Jul 20, 2019
    Forbin, Jul 20, 2019
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  8. Ravn

    Ravn Senior Member (Voting Rights)

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    Either one could conceivably explain why mildly affected patients can look worse on paper than severely affected ones.

    More tricky though are McGregor's study results because he was comparing HC to ME without current PEM to ME with current PEM. It was the patients with PEM - which I would consider an unstable state, and an 'unpaced' one if there is such a word - that looked most like HC.

    Only one thing's for sure: ME is tricky...

    Anyway, back to the current study here: has anyone figured out what's going on with the activin B being down now when it was up in the previous study?
     
    Ravn, Jul 20, 2019
    #8
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  9. Adrian

    Adrian Administrator Staff Member

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    I've only skimmed the paper but this worried me:

    When using ML you typically split the data into training, validation and test sets and quote results on the test set not on the entire data. I can't see any information about the relative splits of the training and test data which makes me suspicious that they have trained with all the data (which would be bad)!. When small amounts of data exist often an n-fold cross validation is used instead but I'm not seeing mention of this either. But I have only skimmed the paper and they may have just not thought it important to say how they split their 97 samples into training, validation and test sets.
     
    Adrian, Jul 23, 2019
    #9
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  10. ME/CFS Skeptic

    ME/CFS Skeptic Senior Member (Voting Rights)

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    Just read the study and can't make much sense of it either.

    Also: it seems to be the middle group, the moderately affected who show the largest differences with healthy controls. In the other two groups differences were not statistically different from controls. Do not see much evidence here for a potential biomarker.
     
    ME/CFS Skeptic, Jul 23, 2019
    #10
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  11. Sly Saint

    Sly Saint Senior Member (Voting Rights)

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    podcast

    Dr Brett Lidbury | Rethinking Myalgic Encephalomyelitis/Chronic Fatigue Syndrome Using Machine Learning
    Jun 14, 2022

    transcript also available

    https://www.scipod.global/dr-brett-...onic-fatigue-syndrome-using-machine-learning/
     
    Sly Saint, Jun 15, 2022
    #11

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