New POLL Article! and Obit

I just posted a new article and discussion on POLL. Please check it out, and comment freely.

The article, Evidence b(i)ased medicine—selective reporting from studies sponsored by pharmaceutical industry: review of studies in new drug applications , compares the studies submitted to the Swedish regulatory agency for approval of 5 SSRI's, with the articles that were eventually published based on those studies.

They note 3 problematic areas.

1. Multiple Publication-individual studies yielded multiple publications, without acknowledging that they came from the same study. Also, subsets of data from multiple studies were pooled to create new publications.
2. Selective Publication-studies that made the drug look good were published more often than studies that showed no difference from placebo.
3. Selective Reporting-studies ignored the results of intention to treat analyses in favor of per protocol analyses, which make the drug look better.

In case you've forgotten, in an intention to treat analysis, subjects who dropped out of a study, for whatever reason, are analyzed as thought they had completed the study, with the last available result carried forward.
In a per protocol analysis, subjects who drop out are ignored in the final analysis. Since many subjects drop out due to adverse effects, or lack of effect, if you don't include those subjects, your results will look better (the subjects who tolerate the drug well and do better on it are more likely to remain in the trial).

Please check out the study and comment (I already wrote that, but it bears repeating).

On another, related note, Ann Wolpert, MIT's director of libraries since 1996, died last month. The reason this is relevant is because she was a big believer in open access, and beginning in 2000, developed DSpace,

"an open-source digital archive for research that has been adopted by more than 1,000 institutions worldwide. DSpace ensure(s) that there (is) a common, permanent platform for library material. Then, in 2009, she conceived the MIT Faculty Open Access Policy, where professors give the Institute permission to disseminate journal articles for open access through DSpace@MIT. In turn, those articles can be republished on open Web sites like the Public Library of Science or PLOS. It was the first policy of its kind in the United States, and has been imitated by other universities around the globe." (Jason Pontin, MIT Technology Review Editor)


“(Wolpert) believed in open access, but it went deeper than that...Her central insight was that in the age of the Internet, a great research library could serve not only as a window into scholarly output for given members of university and research communities, but also as a window for the world at large into the scholarly enterprise. That was a great and thrilling idea...” (Hal Abelson, Class of 1922 Professor of Computer Science and Engineering at MIT and founding director of both Creative Commons and the Free Software Foundation (source))

 POLL, our free online journal club that uses open access articles, was created in the spirit of Wolpert's work. Please make use of it.

Ann Wolpert

Open Source-Please Comment

I have an idea, in very rudimentary form, and I'd like to get peoples' opinions on it.

But first, an amusing anecdote:

The attending who taught me ECT was a character. He'd been doing ECT forever, and his approach was quite old-school. When the patient started to seize, as noted by the twitching toe, he would determine the length of the seizure by counting, 1-Mississippi, 2-Mississippi, 3 Mississippi...
One time, I suggested we look at the clock, and he said, "No, no, this is better." 1-Mississippi was his definition of clinical rigor. Clearly, this was not science.

I read somewhere, some time ago, that the DSM (3?) committee voted on the criteria for MDD. "Those in favor of worthlessness/guilt? Approved! Those in favor of helplessness/hopelessness? Not approved!"

Clearly, this was not science.

But here's the interesting part. How was it determined that 126 was the cutoff for diabetes? I'm not going to look up the history, but I imagine it started with the idea that diabetes was a disease, whose symptoms included ketosis, polyuria, polyphagia, polydypsia, etc. And after seeing many patients with this condition, some clever person figured out that it had something to do with glucose. And later, they realized that if a patient's glucose level is too high, that patient has diabetes. And then "too high" needed to be defined. Presumably, they took a lot of patients who had known diabetes and compared them with normal controls by testing glucose levels. And eventually, they figured out that most patients with diabetes had glucose levels > 126, and most patients without diabetes had levels < 126.

That is science. And it involved a lot of data over a long period of time. Now, granted, they had a test they were looking at-plasma glucose concentration. And there are no convenient lab tests in psychiatry. But there is data.

Not the data you get from a drug-company-sponsored study, where fancy statisticians are hired to produce any desired reality (see, for example, this post). And not the data you get from a 20 person committee voting on a diagnosis.

But what if it was a 200 person committee? Or 2000? Or 20,000? Imagine 20,000 mental health practitioners chiming in on which symptoms they've seen the most. Or which meds they've found most effective. Or least. Or what type of therapy works best for what type of patient. One anecdote is meaningless. But 20,000 anecdotes? Not so meaningless.

I'm talking about the power of the internet. There was a time when the largest number of clinicians you could get in one place was at an APA meeting. Or a survey sent out by snail mail. Now, there's worldwide access at all times. Who needs the DSM when there's the possibility of open source psychiatric data and unlimited discussion?

Would this do anything to determine etiology? No. Not in and of itself, anyway. Would it be valid or accurate? Who knows? People are skeptical about Wikipedia, but is there any more cause for skepticism there than in an old-fashioned encyclopedia article written by one biased individual? Or one closeted committee?

Facebook changed the world by recognizing that a huge collection of connected individuals is a very powerful thing. Why can't we make that idea work to our patients' benefits?

Please comment on this post. I'd like to get a sense of what people imagine this could be like.