{"id":59106,"date":"2015-08-15T13:46:27","date_gmt":"2015-08-15T17:46:27","guid":{"rendered":"http:\/\/1boringoldman.com\/?p=59106"},"modified":"2015-08-15T21:32:56","modified_gmt":"2015-08-16T01:32:56","slug":"increasingly-questionable","status":"publish","type":"post","link":"https:\/\/1boringoldman.com\/index.php\/2015\/08\/15\/increasingly-questionable\/","title":{"rendered":"increasingly questionable &#8230;"},"content":{"rendered":"\n<p align=\"justify\" class=\"small\"><img decoding=\"async\" width=\"160\" vspace=\"4\" border=\"0\" hspace=\"4\" align=\"left\" src=\"http:\/\/1boringoldman.com\/images\/star-d-1.gif\" \/><a target=\"_blank\" href=\"https:\/\/www.youtube.com\/watch?v=fiNhZ71AfDM\">STAR*D<\/a> was an elaborate NIMH study aiming to define some sequencing method that would improve the response to antidepressants using the algorithm on the left [as seen from space]. The main outcomes were a database mined for several hundred publications, a self-rating depression scale [QIDS-SR], and a template for future studies called <em>naturalistic<\/em> at the time &#8211; no control group, no blinding, and progress was monitored by a telephone version of the QIDS-SR. From my point of view, it was <a href=\"http:\/\/1boringoldman.com\/index.php\/2011\/04\/03\/a-thirty-five-million-dollar-misunderstanding\/\" target=\"_blank\">a thirty-five million dollar misunderstanding&hellip;      <\/a><\/p>\n<div align=\"justify\" class=\"small\">But the idea that there is some way to predict who might respond to which antidepressant definitely has staying power. Borrowing the term <em><font color=\"#200020\">personalized medicine<\/font><\/em> from physical medicine, the search for predictor of response continues. There are two large ongoing studies [<a target=\"_blank\" href=\"http:\/\/www.brainresource.com\/research\/ispot\/ispotd\">iSPOT-D<\/a> and <a target=\"_blank\" href=\"http:\/\/embarc.utsouthwestern.edu\/\">EMBARC<\/a>] aiming towards locating biosignatures that might predict a response, and they are both beginning to report findings [<a href=\"http:\/\/1boringoldman.com\/index.php\/2011\/05\/05\/godzilla-vs-ghidorah-the-three-headed-monster-from-outer-space\/\">Godzilla vs. Ghidorah ,,,<\/a>, ]. Here&#8217;s one from the <font color=\"#200020\">STAR*D<\/font> director reporting on an aspect of <font color=\"#200020\">iSPOT-D&#8230;<\/font>            <\/div>\n<blockquote>\n<div align=\"center\" class=\"big\"><a href=\"http:\/\/www.ncbi.nlm.nih.gov\/pubmed\/25815419\" target=\"_blank\">Depression Subtypes in Predicting Antidepressant Response: A Report From the iSPOT-D Trial<\/a><\/div>\n<div align=\"center\" class=\"small\">by Bruce A. Arnow, Christine Blasey, Leanne M. Williams, Donna M. Palmer, William Rekshan, Alan F. Schatzberg, Amit Etkin, Jayashri Kulkarni, James F. Luther, and A. John Rush.<\/div>\n<div align=\"center\" class=\"middle\">                                                                                                            <strong><font color=\"#004400\">American Journal of Psychiatry<\/font><\/strong>. 2015 172[8]:743-750.<\/div>\n<p>           <\/p>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Objective<\/font><\/strong><\/em><\/u>: The  study aims were 1] to describe the proportions of individuals who met  criteria for melancholic, atypical, and anxious depressive subtypes, as  well as subtype combinations, in a large sample of depressed  outpatients, and 2] to compare subtype profiles on remission and change  in depressive symptoms after acute treatment with one of three  antidepressant medications.<\/div>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Method<\/font><\/strong><\/em><\/u>: Participants  18&ndash;65 years of age [N=1,008] who met criteria for major depressive  disorder were randomly assigned to 8 weeks of treatment with  escitalopram, sertraline, or extended-release venlafaxine. Participants  were classified by subtype. Those who met criteria for no subtype or  multiple subtypes were classified separately, resulting in eight  mutually exclusive groups. A mixed-effects model using the  intent-to-treat sample compared the groups&rsquo; symptom score trajectories,  and logistic regression compared likelihood of remission [defined as a  score &le;5 on the 16-item Quick Inventory of Depressive  Symptomatology&ndash;Self-Report].<\/div>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Results<\/font><\/strong><\/em><\/u>: Thirty-nine  percent of participants exhibited a pure-form subtype, 36% met criteria  for more than one subtype, and 25% did not meet criteria for any  subtype. All subtype groups exhibited a similar significant trajectory  of symptom reduction across the trial. Likelihood of remission did not  differ significantly between subtype groups, and depression subtype was  not a moderator of treatment effect.<\/div>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Conclusions<\/font><\/strong><\/em><\/u>: There  was substantial overlap of the three depressive subtypes, and  individuals in all subtype groups responded similarly to the three  antidepressants. The consistency of these findings with those of the  Sequenced Treatment Alternatives to Relieve Depression trial suggests  that subtypes may be of minimal value in antidepressant selection.<\/div>\n<\/blockquote>\n<div class=\"small\">&#8230; that we all already know, since clinical subtype is a usual add-on to any antidepressant Clinical Trial and is regularly unrevealing. Here&#8217;s another in the search for biomarkers of antidepressant response:<\/div>\n<blockquote>\n<div align=\"center\" class=\"big\"><a target=\"_blank\" href=\"http:\/\/www.ncbi.nlm.nih.gov\/pubmed\/25815420\">ABCB1 Genetic Effects on Antidepressant Outcomes: A Report From the iSPOT-D Trial<\/a><\/div>\n<div align=\"center\" class=\"small\">by Alan F. Schatzberg, Charles DeBattista, Laura C. Lazzeroni, Amit Etkin, Greer M. Murphy, Jr., and Leanne M. Williams<\/div>\n<div align=\"center\" class=\"middle\"><strong><font color=\"#004400\">American Journal of Psychiatry<\/font><\/strong>. 2015 172[8]:751-759.<\/div>\n<p>           <\/p>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Objective:<\/font><\/strong><\/em><\/u>: The  ABCB1 gene encodes P-glycoprotein, which limits brain concentrations of  certain antidepressants. ABCB1 variation has been associated with  antidepressant efficacy and side effects in small-sample studies.  Cognitive impairment in major depressive disorder predicts poor  treatment outcome, but ABCB1 genetic effects in patients with cognitive  impairment are untested. The authors examined ABCB1 genetic variants as  predictors of remission and side effects in a large clinical trial that  also incorporated cognitive assessment.<\/div>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Method:<\/font><\/strong><\/em><\/u>: The  authors genotyped 10 ABCB1 single-nucleotide polymorphisms [SNPs] in  683 patients with major depressive disorder treated for at least 2  weeks, of whom 576 completed 8 weeks of treatment with escitalopram,  sertraline, or extended-release venlafaxine [all substrates for  P-glycoprotein] in a large randomized, prospective, pragmatic trial.  Antidepressant efficacy was assessed with the 16-item Quick Inventory of  Depressive Symptomatology&ndash;Self-Rated [QIDS-SR], and side effects with a  rating scale for frequency, intensity, and burden of side effects.  General and emotional cognition was assessed with a battery of 13 tests.<\/div>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Results:<\/font><\/strong><\/em><\/u>: The  functional SNP rs10245483 upstream from ABCB1 had a significant effect  on remission and side effect ratings that was differentially related to  medication and cognitive status. Common homozygotes responded better and  had fewer side effects with escitalopram and sertraline. Minor allele  homozygotes responded better and had fewer side effects with  venlafaxine, with the better response most apparent for patients with  cognitive impairment.<\/div>\n<div align=\"justify\"><u><em><strong><font color=\"#200020\">Conclusions:<\/font><\/strong><\/em><\/u>: The  functional polymorphism rs10245483 differentially affects remission and  side effect outcomes depending on the antidepressant. The predictive  power of the SNP for response or side effects was not lessened by the  presence of cognitive impairment.<\/div>\n<\/blockquote>\n<div align=\"center\"><img loading=\"lazy\" decoding=\"async\" width=\"520\" border=\"0\" height=\"274\" src=\"http:\/\/1boringoldman.com\/images\/ispot-4.gif\" \/><\/div>\n<div align=\"justify\" class=\"small\">That is one pretty graph &#8211; <em><font color=\"#200020\">efficacy on the left, safety on the right, here I am, stuck in the middle with you<\/font><\/em>. This study looked at ten <a target=\"_blank\" href=\"https:\/\/en.wikipedia.org\/wiki\/Single-nucleotide_polymorphism\">SNP<\/a>&#8216;s on a gene that &quot;among blood-brain barrier transporter proteins, P-glycoprotein transports several commonly prescribed antidepressants.&quot; It looks like one&#8217;s genetics has something to do with antidepressant response. <font color=\"#200020\">Lexapro<span class=\"st\">&reg;<\/span> <\/font>or <font color=\"#200020\">Zoloft<span class=\"st\">&reg;<\/span><\/font> for G\/Gs and <font color=\"#200020\">Effexor <\/font><span class=\"st\"><font color=\"#200020\">XR&reg;<\/font> for T\/Ts. However, reading the methodology, one wonders. It looks as if they did the honorable thing and corrected to avoid false positives.<\/span><\/div>\n<blockquote>\n<div align=\"justify\">To account for the testing of multiple SNPs, SNP p values of 0.05\/18&lt;0.0028 ere considered significant using a Bonferroni correction for nine SNPs, each tested for one main effect and one interaction effect. All p values &lt;0.05 are reported for completedness, because of the possibility of false negative results at this significance level.<\/div>\n<\/blockquote>\n<div align=\"justify\" class=\"small\">But buried in the math [which we don&#8217;t quite follow], there&#8217;s one of those &quot;uh-oh&quot; things:          <\/div>\n<blockquote>\n<div align=\"justify\">Remission. In the modified intent-to-treat sample, age [p=0.01] and baseline QIDS-SK score [p&lt;0.001] were significant predictors of remission. Hence, genetic analyses were performed covarying for both. <\/div>\n<p align=\"justify\">Within the significant overall model [X<sup>2<\/sup>=67.58, df=29, p&lt;0.001] only rsl0245483 contributed significantly to prediction of remission. For rsl0245483, there was a significant main effect on remission using multiple testing correction [W=12.64, p&lt;0.001; main effect odds ratio=3.48] and a significant interaction by treatment arm [W=11.18, p=0.001; interaction odds ratio=1.73]. Common allele homozygotes for rsl0245483 responded significantly better to escitalopram [p=0.032] and sertraline [p=0.020] than did minor allele homozygotes. Minor allele homozygotes responded significantly better to venlafaxine [p=0.018]. There were no effects noted in the heterozygotes. The specific contribution of rsl0245483 as a predictor of remission was also verified in univariate models assessing each SNP one at a time. <\/p>\n<div align=\"justify\"><strong><font color=\"#990000\">The effect was similar in whites and nonwhites. In white participants in the modified intent-to-treat sample [N=423], within the significant overall model [X<sup>2<\/sup>=61.51, df=29, p&lt;0.001] rsl0245483 had a significant main effect on remission [W=7.22, p=0.007; main effect odds ratio=3.54] and a significant interaction by treatment arm [W=6.99, p=0.008; interaction odds ratio=1.78], which did not pass the multiple testing threshold. For nonwhites, within the significant overall model [X<sup>2<\/sup>=55.79, df=28, p=0.001], there was a main effect of rsl0245483 on remission [W=11.42, p=0.001; main effect odds ratio=14.38] and a significant interaction between rsl0245483 and treatment [W=9.81, p=0.002; interaction odds ratio=3.54] that met the multiple testing correction threshold.<\/font><\/strong><\/div>\n<\/blockquote>\n<div align=\"justify\" class=\"small\">I would like to be competent in looking at those statistics and knowing what they mean, but in genetics studies, I come up short. These studies are often non-replicable, and I&#8217;m suspicious this will turn out to be one of those too. First off, there&#8217;s no control, no placebo group. So like in STAR*D, we don&#8217;t know what those responder figures really mean. And while they say the effect was similar in whites and nonwhites, the rest of that paragraph doesn&#8217;t confirm the assertion, including a dramatic difference in the odds ratios. One really has to be suspicious with such a paragraph that there a decepticon in the mix. And speaking of STAR*D, &quot;<em><font color=\"#200020\">The authors acknowledge the editorial support of Jon Kilner, M.S., M.A.<\/font><\/em>&quot; Jon was the medical writer for most of the STAR*D articles. And the two first authors spent years chasing a glucocorticoid blocker in psychotic depression without results [but lots of profit]. Throw in their extensive COIs including commercial genetic testing labs, the financing of Australian entrepreneur Evian Gordon&#8217;s <font color=\"#200020\">brain resources<\/font> and suspicion is well justified.     <\/div>\n<p align=\"justify\" class=\"small\">My take on this whole line of thinking is suffused with suspicion. It seems to me that the assumption that there will be biomarkers that predict antidepressant response is widely held, but I&#8217;m in the dark as to why. At least this study has a hypothesis &#8211; the transport of drugs across the blood-brain barrier.&nbsp; This article is accompanied by a <font color=\"#200020\">Perspective<\/font> article from the NIMH Intramural Research Program [<a href=\"http:\/\/ajp.psychiatryonline.org\/doi\/abs\/10.1176\/appi.ajp.2015.15050644?journalCode=ajp\" target=\"_blank\">Clinically Useful Genetic Markers of Antidepressant Response: How Do We Get There From Here?<\/a>] that suggests [you guessed it] more research.     <\/p>\n<div align=\"justify\" class=\"small\"><a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT00021528\" target=\"_blank\">S<\/a><a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT00021528\" target=\"_blank\">TAR*D<\/a> began in 2001 as an outgrowth of the TMAP program [often referred to as <em><font color=\"#200020\">the infamous <\/font><\/em><a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT00021528\" target=\"_blank\"><img decoding=\"async\" width=\"180\" vspace=\"5\" border=\"0\" align=\"left\" src=\"http:\/\/1boringoldman.com\/images\/hot-rod.gif\" \/><\/a><em><font color=\"#200020\">TMAP program<\/font><\/em>] and has spawned a steady stream of both public and industry financed research into super-charging antidepressants ever since &#8211; now chasing the dream of predictive genetic biomarkers [which might lead to a productive enterprise in commercial testing]. Meanwhile, back at STAR*D, it looks as if someone&#8217;s going to have another shot at it:<\/div>\n<blockquote>\n<div align=\"center\" class=\"big\"><a target=\"_blank\" href=\"http:\/\/www.medscape.com\/viewarticle\/849522\">End of &#8216;Trial and Error&#8217; Approach to Depression, Schizophrenia?<\/a><\/div>\n<div align=\"center\"><strong><font color=\"#200020\">Medscape Medical News <\/font><\/strong><\/div>\n<div align=\"center\" class=\"middle\">by Kenneth Bender<\/div>\n<div align=\"center\" class=\"small\">August&nbsp;14,&nbsp;2015<\/div>\n<p align=\"justify\">&hellip; Somaia Mohamed, MD, PhD, VA Connecticut Health Care System, and  coauthors of the article describing the VAST-D study credit the  Sequenced Treatment Alternatives to Relive Depression [STAR*D] study for  highlighting the frequent inadequate response to initial treatments,  but point out that the study did not ultimately identify optimal  interventions after initial treatment failure.<\/p>\n<div align=\"justify\">They also note that  the STAR*D study did not include an atypical antipsychotic augmentation  treatment arm, because the study was conducted prior to FDA approval of  that indication for an agent in this class. <\/div>\n<p align=\"justify\">The  VAST-D study will incorporate atypical antipsychotic augmentation in  the protocol, and the authors indicate that it will answer two principle  questions unanswered by STAR*D: &quot;For which patients, under what  circumstances, is switching to vs augmenting with other antidepressants  the most effective &#8216;next-step&#8217; strategy, and how does augmentation with  atypical antipsychotics compare to either switching or augmenting with  antidepressants?&quot;<\/p>\n<\/blockquote>\n<blockquote>\n<div align=\"center\" class=\"big\"><a target=\"_blank\" href=\"http:\/\/www.psy-journal.com\/article\/S0165-1781%2815%2900556-9\/abstract\">The  VA augmentation and switching treatments for improving depression  outcomes (VAST-D) study: Rationale and design considerations<\/a><\/div>\n<div align=\"center\" class=\"small\">by Somaia Mohamed, Gary R. Johnson, Julia E. Vertrees, Peter D. Guarino, Kimberly Weingart, Ilanit Tal Young, Jean Yoon, Theresa C. Gleason, Katherine A. Kirkwood, Amy M. Kilbourne, Martha Gerrity, Stephen Marder, Kousick Biswas, Paul Hicks, Lori L. Davis, Peijun Chen, Alexandra Mary Kelada, Grant D. Huang, David D. Lawrence, Mary LeGwin, and Sidney Zisook<\/div>\n<div align=\"center\" class=\"middle\"><strong><font color=\"#200020\">Psychiatry Research.<\/font><\/strong> Published Online: August 05, 2015<\/div>\n<p>      <\/p>\n<div><strong><font color=\"#200020\">Highlights<\/font><\/strong><\/div>\n<ul>\n<li>Over 2\/3s of Major Depressive Disorder cases do not achieve remission on initial treatment.<\/li>\n<li><strong><font color=\"#990000\">Urgent need to identify effective next step treatments for MDD.<\/font><\/strong><\/li>\n<li>Switching to bupropion-SR vs. augmenting with bupropion-SR or aripiprazole.<\/li>\n<li>Compare 12-week remission and relapse for up to 6 months after remission.<\/li>\n<li>Seven methodological issues to balance efficacy and effectiveness.<\/li>\n<\/ul>\n<div><strong><font color=\"#200020\">Abstract<\/font><\/strong><\/div>\n<div align=\"justify\">Because  two-thirds of patients with Major Depressive Disorder do not achieve  remission with their first antidepressant, we designed a trial of three  &ldquo;next-step&rdquo; strategies: switching to another antidepressant [bupropion-SR] or augmenting the current antidepressant with either  another antidepressant [bupropion-SR] or with an atypical antipsychotic [aripiprazole]. The study will compare 12-week remission rates and,  among those who have at least a partial response, relapse rates for up  to 6 months of additional treatment. We review seven key  efficacy\/effectiveness design decisions in this mixed  &ldquo;efficacy-effectiveness&rdquo; trial.<\/div>\n<\/blockquote>\n<div align=\"justify\" class=\"small\">&quot;<strong><font color=\"#990000\">Urgent need to identify effective next step treatments for MDD<\/font><\/strong>&quot; assumes there is some such &quot;effective next step&quot; hidden somewhere in the current pharmacopeia yet to be identified. That&#8217;s an increasingly questionable assumption&#8230; <\/div>\n","protected":false},"excerpt":{"rendered":"<p>STAR*D was an elaborate NIMH study aiming to define some sequencing method that would improve the response to antidepressants using the algorithm on the left [as seen from space]. The main outcomes were a database mined for several hundred publications, a self-rating depression scale [QIDS-SR], and a template for future studies called naturalistic at the [&hellip;]<\/p>\n","protected":false},"author":2,"featured_media":0,"comment_status":"open","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_bbp_topic_count":0,"_bbp_reply_count":0,"_bbp_total_topic_count":0,"_bbp_total_reply_count":0,"_bbp_voice_count":0,"_bbp_anonymous_reply_count":0,"_bbp_topic_count_hidden":0,"_bbp_reply_count_hidden":0,"_bbp_forum_subforum_count":0,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-59106","post","type-post","status-publish","format-standard","hentry","category-opinion"],"_links":{"self":[{"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts\/59106","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/users\/2"}],"replies":[{"embeddable":true,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/comments?post=59106"}],"version-history":[{"count":48,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts\/59106\/revisions"}],"predecessor-version":[{"id":59171,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts\/59106\/revisions\/59171"}],"wp:attachment":[{"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/media?parent=59106"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/categories?post=59106"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/tags?post=59106"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}