A woman who can smell Parkinson's disease
bbc.co.uk
bbc.co.uk
One of the reasons people give for the difference in smell are the difference in foods that different cultures eat. I definitely know this is not the case, as everyone on that ship was eating the exact same food, and their smells were extremely distinct.
I understand that lack of science applied to my specific anecdotes, but I think there's something to be said for having a keen sense of smell, since people are already geared towards smelling other people's sweat to determine immunocompatibility[4].
[1] A black person's sweat is the one I can identify with absolute certainty, as it's completely unmistakable for anything else
[2] A white person's sweat smells like a distinct type of onion to me
[3] I couldn't really identify his race if it were just this shirt, but had that one by process of elimination.
[4] https://en.wikipedia.org/wiki/Major_histocompatibility_compl...
After all, the prevalence is 0.3% in the general population. The odds at least one of the six in the control group had parkinson's is around 2% (even less considering it's already a filtered audience in a way). Not impossible but very unlikely, which incidentally makes her insistence of that single particular person to have PD all the more interesting.
There's definitely something there, looking forward to more testing.
If it was a controlled test, why should she need to be "adamant" about anything, surely she would have merely identified it.
I have a red coin and a green coin. I hide the two coins behind my back and ask you to pick the red coin. You pick my left hand, revealing a red coin. You then tell me to reveal my right hand because it also has a red coin. Even though I told you I only have a red coin and a green coin.
I don't believe you. Why should I? I selected a red coin and a green coin and you had already guessed which hand held the red coin. You stand firm. You're absolutely certain my other hand contains a red coin. I open my right hand and reveal a red coin.
You wouldn't need to be "adamant" if you told me that my right hand held a green coin. I know it was a green coin - I placed it there!
She had to be "adamant" because everyone thought she was surely wrong. After all - that was one of the control members. They believed she was wrong. Turns out she was right.
Dr Kunath adds: "She got the six Parkinson's but then she was adamant one of the 'control' subjects had Parkinson's.
"But he was in our control group so he didn't have Parkinson's.
"According to him and according to us as well he didn't have Parkinson's.
"But eight months later he informed me that he had been diagnosed with Parkinson's.
"So Joy wasn't correct for 11 out of 12, she was actually 12 out of 12 correct at that time.
"That really impressed us and we had to dig further into this phenomenon."
Reminds me of the story I heard about a doctor who was diagnosing an STD a lot earlier than average. They put two other doctors in the room with him to try to spot what he was seeing and identified the eye flutter as a new symptom, I think for syphilis.
"I heard a story about this woman that was swimming in the ocean, and dolphins started swimming with her, and the dolphins kept poking her in the chest above her breast. She got scared and they took her out of the water, and she had a big bruise right on the top of her breast. They took her to the doctor to examine her, and they did a mammogram, and found that she had cancer right in that spot."
– Jim Jarmusch, 'Fishing with John'
[0] http://www.dolphin-institute.org/our_research/dolphin_resear...
http://www.livescience.com/38087-can-dolphins-detect-pregnan...
In 1986, Peter Davies was on holiday in Kenya after graduating from Louisiana State University. On a hike through the bush, he came across a young bull elephant standing with one leg raised in the air. The elephant seemed distressed, so Peter approached it very carefully. He got down on one knee, inspected the elephants foot, and found a large piece of wood deeply embedded in it. As carefully and as gently as he could, Peter worked the wood out with his knife, after which the elephant gingerly put down its foot.
The elephant turned to face the man and with a rather curious look on its face, stared at him for several tense moments. Peter stood frozen, thinking of nothing else but being trampled. Eventually the elephant trumpeted loudly, turned and walked away. Peter never forgot that elephant or the events of that day.
Twenty years later, Peter was walking through the Chicago Zoo with his teenaged son. As they approached the elephant enclosure, one of the creatures turned and walked over to near where Peter and his son Cameron were standing. The large bull elephant stared at Peter, lifted its front foot off the ground, then put it down. The elephant did that several times then trumpeted loudly, all the while staring at the man.
Remembering the encounter in 1986, Peter could not help wondering if this was the same elephant. Peter summoned up his courage, climbed over the railing and made his way into the enclosure. He walked right up to the elephant and stared back in wonder. The elephant trumpeted again, wrapped its trunk around one of Peter legs and slammed him against the railing, killing him instantly.
Probably wasn't the same fucking elephant.
I absolutely loved "Fishing with John" - that doesn't make the cancer-detecting dolphin a true story, though.
So we know that something is going on here. The next steps are to control potential confounding variables and to determine the sensitivity and specificity of the test, if it's shown that she's not actually detecting some confounding variable. This is where you go double-blind, you use larger sample sizes, et cetera, now that you have money. You have money because the preliminary research was promising.
And we're not just getting a good test out of this. If there's an actual chemical that she's smelling, then there's some chemical process that's going on in people with Parkinson's which isn't happening in people without Parkinson's (or vice versa). Tracing these chemical pathways could give us clues to the etiology of the disease, which would be a REALLY BIG DEAL. Or maybe it's just a rabbit hole.
Hypothesis generation is important, because it helps us design the next experiment, but this experiment is already very interesting.
You just have to ignore the people who shout "correlation is not causation" at every opportunity, appropriate or not.
See also: "You're not Google's customer, you're the product"
The statement is only important to people doing statistical analysis not experimental science.
It sure does. It might not prove causation, or it might not necessitate causation, but it very much implies it.
Somehow people forget that "imply" means: "indicate the truth or existence of (something) by suggestion rather than explicit reference".
In this -- the dictionary and everyday sense -- correlation DOES imply (suggest) causation. It just doesn't secure it.
Definitions differ depending on the context, both definitions are valid.
There's got to be some other required factor before correlation can imply causation. Like "if there's reason to believe something is relevant, and there is correlation, then that implies causation. "
http://www.tylervigen.com/spurious-correlations
You say this implies causation... I have my doubts in any sense of the word implies.
For sure, a correlation could lead to something to investigate, but look at enough data and you will find plenty of correlations that mean nothing. A lot depends on how the correlation is discovered (number of variables involved etc.).
Couples divorcing people their partner got fat on margarine?
Besides that's not the best way to check correlation charts. You first have to remove bias components influencing both curves, e.g. the mere act that both are rising over time.
When you do that, do they still match each other, e.g. following increases and decreases? I very much doubt so. So this plot doesn't actually show correlation -- just that both "increase" over time in a similar way.
The same kind of "same plot trends" happens or every set of things that e.g. both have an exponential growth curve -- but it's not correlation unless both change consistently as the other changes.
Perhaps we should say, “Correlation correlates with causation.”
(Because causation is a subset of correlation.)
"Correlation doesn't imply causation, but it does waggle its eyebrows suggestively and gesture furtively while mouthing 'look over there'."
[0] - https://xkcd.com/552/
They "found that a compound emitted by mold, called 1-octen-3-ol but more commonly known as mushroom alcohol" "attacked two genes involved in the creation of dopamine"
And speculate I think that could be related to the drop of in dopamine production in Parkinsons.
It would be interesting to try some such "volatile organic compounds emitted by fungi" with the lady who can smell Parkinson's to see it the smell was similar.
http://www.medicalnewstoday.com/articles/268848.php
Also a 1990 article suggesting it's "the fungus, called Nocardia asteroides." I guess nothing much happening since 1990 suggests that didn't work out.
http://articles.latimes.com/1990-05-17/news/mn-286_1_nocardi...
I'm on the look out for stuff for my dad who seems to have it. The data in the New Scientist article looks promising - all 12 of the patients started to improve, some dramatically and as to side effects the "team saw no unwanted effects".
The thing that makes me wonder though - what's the state of broad-range chemical sensing? Could a chemical like this be found before if we kept taking broad "smell" samples of everyone and cross-correlating them?
1) The population doesn't reflect a realistic test--if the overall incidence is 0.3%, but the sample size had 50% (or more given her adamant hit), then we need to know whether she was expecting more. 2) More importantly, the incidence in men is 1.49x that of women [1], and age also plays a factor. So given that the sample is already skewed towards a higher incidence of positives, the gender differences might be factored into her senses--especially since it was her husband who was her training set. With n=12, it would be very easy for the probabilities/priors to be much different than truly random. (E.g., the learning function of her nose might be "men + people over 65" which happened to match up with the test and control group quite well.") Or it could tune into medication used to treat the disease.
Great if true, but I am skeptical.
Point 2 is interesting though, and the first thoughtful criticism I've seen in the thread. What if she's both a bit lucky, and also picking up on some correlated marker like age/gender?
Why not just train a dog to smell it?
It seems that _how_ this works is still unclear, if it works at all. Once validated, it seems plausible that a device/trained animal could replicate the results, assuming its not like this guy: https://en.wikipedia.org/wiki/James_Harrison_(blood_donor)
[2] https://en.wikipedia.org/wiki/Multiple_comparisons_problem
Were you just advocating for the devil?
Traditional null hypothesis would be something like "she guesses right 50% of the time", which gives a likelihood of 1/16384 that she would get the correct answer. Let's be cynical, and suppose that she knew or guessed that there were 5-7 patients with Parkinson's, the likelihood is now 1/2538, still pretty low. Even if she knew there were exactly 7 patients with Parkinson's (quite a cynical null hypothesis!) the likelihood is only 1/792. Hey, that's a p-value of 0.0012!
Yes, p-values suck. But, the significance is absolutely there, but we would want to follow this research up with a larger sample size and control more of the variables.
P(skill): Let's choose a prior that someone can smell parkinson's as one in a million, or 10^-6. (Not very well argued, I admit.)
P(data): This exact data's random occurrence probability is 1/2538.
P(data|skill): The probability of the result, taking account that she has the skill, is 1 (this assumes she never errs).
So we get
P(skill|data) = P(data|skill) x P(skill) / P(data)
P(skill) = 1 x 10^-6 / (1/2538) = 0.002538
Intuitively, I would have expected the calculation to yield a much higher number. The prior was very low though.
So I think the grandparent post has some merit. It can be argued that the claim is so extraordinary (the prior) that even twelve "coin tosses" guessed right in a row is more likely.
Of course, she is not a person picked at random, we should look at the population of people claiming to have done these sort of things already on their own. This population would be expected to contain a large portion of people with mental issues and charlatans trying to gain some financial benefit. If she doesn't have a history of either, then the prior jumps up to a very high level already. It is not very likely for a normal person to claim this sort of thing, unless they already have good evidence by themselves already.
But no matter what assumptions were made, no p-val was greater than .001, which is quite low for n=12 with a single test. Our generally accepted threshold is p<.05. She literally had a perfect score.
Also, saying "An actual test would need to allow any possible sample including those that had zero Parkinson's patients" indicates you don't understand experimental design. Splitting the data into equal groups maximizes your chances of detecting something when effect sizes are small, since sensitivity is related to minimum group size. (P-values are hurt more by low sample sizes than they gain by large ones, which is why a 3/9 split is less powerful than a 6/6 split.)
"We don't go to the doctor and have him or her smell our armpits" is an argument to authority. Just because a doctor doesn't use test X does not mean that test X is not useful. Every single diagnosis test we use today was, at some point in the past, unknown and unused by doctors. It is scientific research which gave us those tests. And, because you seem to be uninformed about the subject, I'd like to tell you that there are a number of things that a doctor will smell when they diagnose you. Famously, you can diagnose phenylketonuria by smell, and you can also diagnose diabetes by smell.
This comment also seems to reflect a fundamental misunderstanding of the scientific process. The whole point of scientific research--which requires funding, usually--is to figure out if a hypothesis is true or false. If you already know whether your hypothesis is true or false, you're not doing research, you're replicating results.
When you do preliminary research, it's because you don't have very good information about some particular subject. You're complaining about the shaky ground that they base their research funding on--but these scientists did the right thing. Because the hypothesis seemed improbable, they conducted a dirt cheap experiment. It's an experiment that you could have conducted yourself for $20.
That's exactly what this is. People believe the claim 100% so we do a simple coin flip, and, yes, there it is. It's confirmed! No extraordinary evidence required for this extraordinary claim. Let the research money flow and the BBC reporting commence. If it were my money I would have another lab repeat the experiment.
Additionally, the likelihood that a particular person would be so convinced in their ability to smell Parkinson's that they sufficiently convince a few researchers AND THEN predict with perfect accuracy is much smaller than 1/4096. This isn't a random person picked off the street--this is a person specifically claiming to be able to accomplish a feat and then being successful on the first try at 1/4096 odds (1/2^12).
Combined, I find this result very interesting and strongly believe the validity of this research. Granted, just because something is likely doesn't necessarily make it true, but it's certainly a strong impetus for future research, or even for people with a similar talent to come forward.
We are interested in the following calculation:
P(skill|claim&data) = P(claim&data|skill) x P(skill) / P(claim&data)
So, Bayesian reasoning won't save you here.
1. https://en.wikipedia.org/wiki/Multiple_comparisons_problem
As you can see, a sensitivity of 95% (true positive 95% of the time) with a confidence interval +- 4.3% requires 100 positive subjects. Because the natural rate is 1 in 500, we would need 500*100 = 50,000 total subjects. So you can see how absolutely ludicrous it is to say a woman sniffs the clothes of 12 subjects and is presumed to have a 100% true positive rate with 100% confidence level.
Nobody's claiming she's always 100% accurate. That's also a factor of low sample sizes. But I went ahead and computed the margin of error for you. For n=12, a 95% confidence interval requires a margin of error of 28%, so her true detection ability is, at worst, 72%, which is still higher than anything else we've got.
We consider n=12 generally underpowered only because many real-world effects are way weaker than the ability this woman demonstrated.
The methodology should have been mentioned more in the article, and should be scrutinized, but that doesn't mean it's worthless if she truly diagnosed these people after a (single?) blind experiment.
You jest, but there is actually a suggestion that aluminum in sweat blocking deodorant causes neurological problems like Parkinson's and Alzheimer's.
(The evidence for this is not strong however.)
Ideal would be to check large numbers of undiagnosed people, and then see how many of those she "alerted" on developed the disease, but given the generally-low incidence of Parkinson's I suspect this approach would be impractical. Larger sample sizes than 12 would always be nice, of course.
Not to mention the value in correlating another physiological change with the disease. Maybe research into how this works can get us closer to a cure.
Because there's a good chance you'll receive a treatment that will cause you to die sooner than had you not known about the disease for another decade. C.f. why they pushed back the recommended age for mammograms this week.
1) Wouldn't you want to know say a year in advance, before you made all kinds of hospital visits and it was finally confirmed? I bet you would. Perhaps to start preparing for a different life, career, perhaps to advance future plans of things you'll gradually become less able to do. People want to know.
2) Can you imagine that if somehow, for example, you could detect Parkinson's by smell, that this would open up all kinds of findings, research and understanding about what Parkinson's is, how it works, how it's detected etc, that could potentially lead to better treatment or even a cure? I bet you can imagine there's a positive correlation between understanding something better and the ability to treat it in future.
3) it's simply interesting in and of itself. How curious, isn't it?
And regardless while there isn't a cure per-say for Parkinson's there are treatments which can delay it's progression and the earlier you get them the more time you have.