Interesting article on big data in diagnosis

Peggy Zuckerman peggyzuckerman at GMAIL.COM
Wed Jun 8 16:44:27 UTC 2016


Well-said, Brian, and similar to my own reaction.  I do think that the
generally vague symptoms that might precede many cancers make this a pretty
difficult task.  It might be a far more effective search to pursue Google
inquiries about 'unexplained weight loss".

Just recently there was a story of the patient whose rare disease was
diagnosed by other patients, once she was able to explain her symptoms to a
patient audience.

Peggy

Peggy Zuckerman
www.peggyRCC.com

On Wed, Jun 8, 2016 at 9:10 AM, Jackson, Brian <brian.jackson at aruplab.com>
wrote:

> I’m disappointed.  NYTimes is usually one of the good guys in terms of
> high quality science journalism, but this article is the sort of uncritical
> hype that I usually see from lesser sources.  I suspect this is because the
> reporter in this case, John Markov, specializes in covering the IT
> industry.  I doubt any of NYTimes’ excellent health and medicine reporters
> would have touched this story, because there’s really not much there in
> terms of newsworthy science:
>
>
>
> 1.       The authors basically just demonstrated that you can find a
> signal within web searches that correlates diagnosis-related searches with
> previous symptom-related searches.  Which is sort of interesting in the
> sense that you could use this approach to study consumer health behaviors,
> etc.
>
> 2.       The initial symptoms used in the study were cherry-picked to be
> somewhat specific for pancreatic cancer, esp. when seen in combination.  In
> principle you could do the same for other cancers, e.g. “large hard lump in
> my breast” or “worsening constipation and blood in stool” but by the time
> such symptoms become diagnostically specific, the cancers are often quite
> advanced.
>
> 3.       The study provides zero new information about pancreatic cancer
> diagnosis, let alone ways to improve diagnosis.
>
> 4.       It’s not clear to me whether they tested their model on a
> different data set than they used to train the model.  Unless I’m missing
> something in their methodology, this would be a pretty blatant violation,
> and would invalidate their calculated performance measures (true-positive,
> etc.)
>
> 5.       Cancer screening only works under a pretty narrow set of
> assumptions.  These assumptions are satisfied for cervical and colorectal
> cancer, but not for the vast majority of cancers at this point in time.
> Framing the journal article around screening discredits the authors, and
> the same could be said about the news article and journalist.
>
>
>
> --Brian Jackson
>
>
>
> *From:* David L Meyers [mailto:dm0015 at COMCAST.NET]
> *Sent:* Tuesday, June 07, 2016 8:51 PM
> *To:* IMPROVEDX at LIST.IMPROVEDIAGNOSIS.ORG
> *Subject:* [IMPROVEDX] Interesting article on big data in diagnosis
>
>
>
>
> http://www.nytimes.com/2016/06/08/technology/online-searches-can-identify-cancer-victims-study-finds.html?hp&action=click&pgtype=Homepage&clickSource=story-heading&module=first-column-region&region=top-news&WT.nav=top-news
>
> David
>
> David L Meyers, MD FACEP
>
> Listserv Moderator/Board member
>
> Society to Improve Diagnosis in Medicine
>
> Save the Date: Diagnostic Error in Medicine, November 6-8, 2016, Los
> Angeles, CA
> Save the Date: DEM-Europe, June30-July 1, 2016, Rotterdam, The Netherlands
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Moderator: David Meyers, Board Member, Society to Improve Diagnosis in Medicine


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