Discussion in 'Phoenix Rising Articles' started by Mark, Jun 24, 2013.
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I only skimmed the article but it does appear something is being done. While 6,000 publications sounds impressive at first, it is nothing compared to other diseases and most of that 6,000 is low-fidelity noise. Therefore, while I like the idea of the "COSS" data harvesting, I hope that it was not affected by GIGO and a lack of diversity in the drug trials which probably mostly involved psychopharmacology.
This was my concern also. They seemed to be honing in on psychiatric fatigue -- not necessarily a psychological condition, but related to neurotransmitters serotonin, dopamine, etc. This could easily be false conclusion based on the bias toward seeing "fatigue" as the primary symptom and including so much garbage psychological research in their study.
Maybe it's because it's late and I'm tired, but I don't find this report encouraging.
Perhaps Question 4 and the Answer helps in this regard? Must admit that my own concerns were raised when I considered what was out there in terms of published papers and the areas that they focused upon.
I mean if you repeated the search in 5 years hence or limited your search to perhaps more recent years - I wonder what impact that would have on any results i.e. perhaps more 'biomedical' papers? But then I don't know the full results - as far as I know they will publish the search but haven't done yet.
When it came to their drug and symptom search however, I hope the two drugs they are looking at might address more than the 'usual' depression-associated cabal.
Having said that, we were talking about these particular issues on this thread most recently. I should perhaps have linked to it in the article. My 'bad'
I see that CAA and OMI-MERIT (and others) are exhibiting more signs of networking and coming together in their applications for this Patient Centered Outcomes Research Institute (PCORI) funding:
Thanks Firestormm re Question #4. I had a quick look and am too busy to really take a deeper look at it all again, so I could be speaking from ignorance here or am missing something important, but I just find it odd that out of all that harvested data, all they could really come up with so far is a few symptoms and drugs mostly related to monoamine neurotransmitters.
Serotonin > Dopamine > Acetylcholine > Histamine >= Epinephrine.
If it really was that simple, then awesome. But many of the key symptoms or pathophysiological components mentioned in one of the fuzzy slides had no apparent correlation to these. Am I correct in stating that so far the searches have focused on correlating CFS to adverse affects reported in other drug trials? I guess it is a drug development endeavor, but such a database sounds like it would have great potential for a lot more than that.
I see no mention of oxidative stress, which has been one of the most consistent findings in CFS. Granted it could be an epiphenomenon, but still, there are drugs and other substances which could help.
[deleted speculation about which drugs will and will not be used]
Edit: Saw this on the other thread:
From the FDA slide -
Since we don't really have "objective" symptoms, we can only go by the "subjective", which is pain, fatigue, headache..etc
I think that these were the type of key words that the COSS was searching for when trying to find corresponding effective treatments.
The problem that I see with doing a search for these items is that one will find all types of illnesses with common symptoms. I am not sure that this search engine can search for a cluster of symptoms which is really what is required for a diagnosis of ME/CFS. One symptom by itself means nothing. If one searches for these symptoms without PEM for example what does it mean for us?
Although at first, when I heard about this work, I was impressed with it's sophistication, I am not sure if this can be applies to such a complex illness as ours.
Thanks to Gabby and to Russell (I think this is your debut?) for a really interesting article - I saw how long the transcript was (and how mangled in places) so it was great to get the essence of it all distilled down like this.
Munos's stuff was amazing: I don't know how much hard evidence there is that this approach works, but it makes great sense, and he sells it brilliantly. The "Build it and They will come" approach is very appealing as it gives us something concrete we can do to make a difference.
CFIDS/Biovista: I share those concerns about searching a large but iffy literature with the risk of GIGO, and the subjective nature of the symptoms. On the other hand, if it's being done as a way to identify candidate drugs or mechanisms, then it could be useful. Likewise, asking physcians which drugs work is a very good idea, though a shame they only had 15 Physicians involved (50% of 30). But if those 15 include people like Dan Peterson who specialise in ME/CFS it could represent an oasis of clinical experience.
You might have to excuse me - been a long morning - but what is GIGO and how does it apply in this context? You've both referred to it and I can't get my head around the acronym much less - I suspect - it's use.
Muchas gracias amigos
By GIGO, I think they mean as a slang for "garbage in, garbage out". In IT context meaning that regardless of how accurate a program's logic is, the results will be incorrect if the input is invalid.
Brilliant! Thanks Nielk. Phew. I thought I was cracking up!
GIGO is a very useful word(?) in this context. It says a lot in not much space. GIGO is my only real concern about this research, but I think it is a huge concern. I don't think psychological papers should be used in a search of appropriate medications for this illness. Such papers are not based on sound medical knowledge, but on psychological theories -- not something I want as the basis for choosing a medication.
Asking 15 good ME/CFS biomedical specialists which drugs work, or even what they believe the symptoms to be, would be a lot more effective.
Classifying medication use in clinical research.
Rizzo D, Creti L, Bailes S, Baltzan M, Grad R, Amsel R, Fichten CS, Libman E.
Jewish General Hospital, Montreal, Canada.
J Prim Care Community Health. 2011 Jan 1;2(1):26-32. doi: 10.1177/2150131910385843. Epub 2010 Oct 27.
BACKGROUND: Medication use data are usually collected in clinical research. Yet no standardized method for categorizing these exists, either for sample description or for the study of medication use as a variable.
OBJECTIVE: The present investigation was designed to develop a simple, empirically based classification scheme for medication use categorization.
METHOD: The authors used factor analysis to reduce the number of possible medication groupings. This permitted a pattern of medication usage to emerge that appeared to characterize specific clinical constellations. To illustrate the technique's potential, the authors applied this classification system to samples where sleep disorders are prominent: chronic fatigue syndrome and sleep apnea.
RESULTS: The authors' classification approach resulted in 5 factors that appear to cohere in a logical fashion. These were labeled Cardiovascular or Metabolic Syndrome Medication, Symptom Relief Medication, Psychotropic Medication, Preventative Medication, and Hormonal Medication.
CONCLUSIONS: The findings show that medication profile varies according to clinical sample. The medication profile for participants with sleep apnea reflects known comorbid conditions; the medication profile associated with chronic fatigue syndrome appears to reflect the common perception of this condition as a psychogenic disorder.
KEYWORDS: factor analysis, medication classification, medication grouping, method, principal components analysis
Jennie's latest blog 'Data Queen' is an interesting example of personal data collection including use of the 'fitbit' mentioned by Dr Munos at the conference.
I have never personally gone down this route to any great extent or for very long - I found self-monitoring even to the extent of diaries and graphs etc. at the recommendation of my medics became obsessive, distracting and time-consuming; and the medics never really took my records on-board: it never led to anything proactive in terms of treatment.
BUT that's just me and I am in my 14th year - and it does seem to help my friends.
I think I would happily wear and use a 'fitbit' if the data collected could be submitted to some sort of central database for study.The idea of something that collects the data independently is appealing.
I wore a Fitbit for the four day study at Mt. Sinai. It was very comfortable to wear. You register it on the Fitbit website and it wirelessly downloads your information. I am thinking about buying one myself.
You can also try a Google Site Search
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