{"id":40041,"date":"2013-09-15T14:48:54","date_gmt":"2013-09-15T18:48:54","guid":{"rendered":"http:\/\/1boringoldman.com\/?p=40041"},"modified":"2013-09-15T15:02:38","modified_gmt":"2013-09-15T19:02:38","slug":"squeezing-blood-from-a-turnip","status":"publish","type":"post","link":"https:\/\/1boringoldman.com\/index.php\/2013\/09\/15\/squeezing-blood-from-a-turnip\/","title":{"rendered":"squeezing blood from a turnip?…"},"content":{"rendered":"
Among the strange stories that will be told looking back on the second age of psycho·<\/strong>pharmacology, none will likely rival the quest to improve the efficacy of the SSRI and other antidepressants. As they rolled onto the market following Prozac’s introduction, there was an intense competition for market share, with the manufacturer of each new drug claiming that it was more efficacious or had less adversity than the the ones before. As time wore on and patent lives began to expire and the promises of the makers faded, the focus turned to how to choose among them – operating on an assumption that the overall efficacy of the class could be improved by finding the right drug for a given patient by giving them in a certain way [algorithms, sequencing, combining] or by enhancing the drugs with some kind of helper strategy [augmentation].<\/div>\n

As doctors and patients encountered the inconsistent performance of these drugs in their offices and clinics, they tried all those strategies mentioned above in non-responders [labeled as having treatment resistant depression<\/em>] and anecdotal solutions abounded [along with the rise of poly·<\/strong>pharmacy, a former no-no]. That future history of the second age of psycho·<\/strong>pharmacology will undoubtedly have a figure like the one on the right showing what might be called the Texas Many-Step<\/em>, a series of studies that attempted to systematize these anecdotal sequencing, combining, augmenting strategies as algorithms. The studies were publicly funded, expensive, and notoriously failed enterprises. TMAP, the opening gambit, was a drug company encouraged scam to get expensive drugs into the public sector – now defunct and still in the courts. The middle three were NIMH funded duds. And the final one is an ongoing NIMH study [AKA dud-in-training]. The history book chapter describing this period might be entitled squeezing blood from a turnip?<\/font><\/strong><\/em> I’ve chased off readers with my preoccupation with these studies, so I’ll skip the details [put any of them into search<\/a> below if you need a refresher].<\/p>\n

Embarc<\/font><\/strong> continues the theme by proposing that there are patients who will uniquely respond to one or another antidepressant and proposes to measure all possible measurable things to find and test the predictors hypothesized to be hidden in the sea of assessed genetic, chemical, or psychometric variables [biomarkers of response]. This NIMH study is matched by a privately funded trial coordinated by Australian brain-training guru Evian Gordon. Comes now a recently reported progress article from this second study [called iSpot-D<\/font><\/strong>, the International Study to Predict Optimized Treatment in Depression]: <\/div>\n
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Brain imaging predictors and the international study to predict optimized treatment for depression: study protocol for a randomized controlled trial<\/a><\/div>\n
by Stuart M Grieve, Mayuresh S Korgaonkar, Amit Etkin, Anthony Harris, Stephen H Koslow, Stephen Wisniewski, Alan F Schatzberg, Charles B Nemeroff, Evian Gordon, and Leanne M Williams<\/div>\n
Trials<\/font><\/strong>. 2013; 14: 224.<\/div>\n
[full text on-line<\/a>]<\/div>\n

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Background<\/font><\/strong><\/u>: Approximately 50% of patients with major depressive disorder [MDD] do not respond optimally to antidepressant treatments. Given this is a large proportion of the patient population, pretreatment tests that predict which patients will respond to which types of treatment could save time, money and patient burden. Brain imaging offers a means to identify treatment predictors that are grounded in the neurobiology of the treatment and the pathophysiology of MDD.<\/div>\n
Methods\/Design<\/font><\/strong><\/u>: The international Study to Predict Optimized Treatment in Depression is a multi-center, parallel model, randomized clinical trial with an embedded imaging sub-study to identify such predictors. We focus on brain circuits implicated in major depressive disorder and its treatment. In the full trial, depressed participants are randomized to receive escitalopram, sertraline or venlafaxine-XR [open-label]. They are assessed using standardized multiple clinical, cognitive-emotional behavioral, electroencephalographic and genetic measures at baseline and at eight weeks post-treatment. Overall, 2,016 depressed participants [18 to 65 years old] will enter the study, of whom a target of 10% will be recruited into the brain imaging sub-study [approximately 67 participants in each treatment arm] and 67 controls. The imaging sub-study is conducted at the University of Sydney and at Stanford University. Structural studies include high-resolution three-dimensional T1-weighted, diffusion tensor and T2\/Proton Density scans. Functional studies include standardized functional magnetic resonance imaging [MRI] with three cognitive tasks [auditory oddball, a continuous performance task, and Go-NoGo] and two emotion tasks [unmasked conscious and masked non-conscious emotion processing tasks]. After eight weeks of treatment, the functional MRI is repeated with the above tasks. We will establish the methods in the first 30 patients. Then we will identify predictors in the first half [n = 102], test the findings in the second half, and then extend the analyses to the total sample.<\/div>\n<\/blockquote>\n
I’m also including the Acknowledgements<\/em> along with the Abstract<\/em> because they relate to the topic of this post [coming soon]:<\/div>\n
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Acknowledgements<\/font><\/strong><\/u>: We acknowledge Brain Resource as the sponsor for the iSPOT-D study [NCT00693849]. Claire Day [Global Study Co-ordinator] is thanked for her pivotal role in making this study happen, and for her boundless enthusiasm and energy. We thank the iSPOT-D Executive Committee for their valuable input into this manuscript and into the study overall [Members: A John Rush [Chair], Lea Williams [Academic PI], Steve Koslow, AmitEtkin, Evian Gordon, Steve Koslow, Stephen R Wisniewski. We also thank those responsible for designing the iSPOT-D protocol [A. John Rush, Lea M Williams, Evian Gordon, Charles B Nemeroff, Alan F Schatzberg]. We gratefully acknowledge the editorial support of Jon Kilner, MS, MA [Pittsburgh, PA, USA]. SMG acknowledges the support of the Sydney University Medical Foundation. Dr Lavier Gomes, Ms Sheryl Foster and the Department of Radiology at Westmead are thanked for their substantial contributions to MRI data acquisition.<\/div>\n<\/blockquote>\n
STAR*D<\/font><\/strong>, COMED<\/font><\/strong>, IMPACT<\/font><\/strong>, EMBARC<\/font><\/strong>, and iSPOT<\/font><\/strong> share more than just their obsession with antidepressant response rates and acronyms:<\/div>\n