{"id":69683,"date":"2016-12-25T18:00:28","date_gmt":"2016-12-25T23:00:28","guid":{"rendered":"http:\/\/1boringoldman.com\/?p=69683"},"modified":"2016-12-25T21:58:05","modified_gmt":"2016-12-26T02:58:05","slug":"an-explanation-and-a-surprise","status":"publish","type":"post","link":"https:\/\/1boringoldman.com\/index.php\/2016\/12\/25\/an-explanation-and-a-surprise\/","title":{"rendered":"an explanation and a surprise&#8230;"},"content":{"rendered":"\n<p class=\"small\" align=\"justify\">So, picking up from <a href=\"http:\/\/1boringoldman.com\/index.php\/2016\/12\/23\/explanation-would-be-welcome\/\">explanation would be welcome&hellip;<\/a> and looking at the enrollments in <a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT02932943\" target=\"_blank\">RAP-MD-01<\/a>, <a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT0243564\" target=\"_blank\">RAP-MD-02<\/a>, and <a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT02943577\" target=\"_blank\">RAP-MD-03<\/a> that seem so high in those Rapastinel Clinical Trials. The way trialists pick their sample size is to do a <font color=\"#200020\">Power Analysis<\/font>. Using the Standard Deviation from a previous similar study, then pick the difference in means between the control and experimental values you would consider meaningful, and it spits out a sample size. Here&#8217;s the formula:<\/p>\n<p align=\"center\"><img decoding=\"async\" src=\"http:\/\/1boringoldman.com\/images\/power-1.gif\" width=\"350\" border=\"0\" \/><\/p>\n<p class=\"small\" align=\"justify\">These studies use <font color=\"#200020\">Montgomery-Asberg Depression Rating Scale [MADRS]<\/font>, and I can&#8217;t find any data to give me a <font color=\"#200020\">Standard Deviation for Rapastinel using MADRS<\/font>, nor do I know that scale well enough to select a mean difference. But, if you&#8217;ll allow me a bit of numeric mojo, I can use the <font color=\"#200020\">Z Scores <\/font>for<font color=\"#200020\"> p=0.05 <\/font>and an<font color=\"#200020\"> 80% power<\/font> [both standard], si I simplified the equation. I noticed that it has <font color=\"#200020\">a clause that contains the formula for the <\/font><font color=\"#200020\">Cohen&#8217;s <em>d<\/em><\/font><font color=\"#200020\"> Effect Size so I substituted and<\/font> come up with a formula that calculates the sample size for the group for any given <font color=\"#200020\">Effect Size<\/font> [could that be right?]. The table on the right gives some example values:           <\/p>\n<p align=\"center\"><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/1boringoldman.com\/images\/power-3.gif\" width=\"446\" height=\"162\" border=\"0\" \/><\/p>\n<p class=\"small\" align=\"justify\">Looking at the group sample sizes for <a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT02932943\" target=\"_blank\">RAP-MD-01<\/a>, <a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT0243564\" target=\"_blank\">RAP-MD-02<\/a>, and <a href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT02943577\" target=\"_blank\">RAP-MD-03<\/a>, we have 700&divide;2&nbsp;=&nbsp;<font color=\"#200020\">350<\/font>, 2333&divide;3 = <font color=\"#200020\">778<\/font>, and 1556&divide;2 = <font color=\"#200020\">778<\/font> respectively. Applying the formula, that gives <font color=\"#200020\">Cohen&#8217;s <em>d<\/em><\/font> values of <font color=\"#200020\">0.21<\/font>,<font color=\"#200020\"> 0.14<\/font>, and<font color=\"#200020\"> 0.14<\/font>. So if my formula works, using Cohen&#8217;s rough guidance<font color=\"#200020\"> [0.25 is a weak Effect, 0.50 is moderate Effect, and 0.75+ is a strong Effect<\/font>] these studies are powered to detect statistically significant differences at <font color=\"#200020\">Effect Sizes<\/font> that are for all intents and purposes no Effect at all, clinically insignificant. By this read,<em><font color=\"#200020\"> these studies are dramatically overpowered<\/font><\/em>.<\/p>\n<p class=\"small\" align=\"justify\">And as to the question, why three different clinical trials that are close to identical? That one&#8217;s easy. They need two statistically significant RCTs to be eligible for an FDA Approval. Instead of doing a trial, and if it&#8217;s positive, trying to replicate it, they are doing them simultaneously because it&#8217;s faster. Sinilarly, why so many sites? I really speeds up recruitment.And how are they going to come up with 4589 depressed subjects that are treatment failures [&lt;50% response to an SSRI] and get this study done in two years? I haven&#8217;t a clue. <em><strong><font color=\"#200020\">But the point is clear, this is a race to the finish line, to be the first company to have a Ketamine-like product on the market. <\/font><\/strong><\/em><\/p>\n<p class=\"small\" align=\"justify\"><em><strong><font color=\"#990000\">Surprise\/Flash:<\/font><\/strong> <font color=\"#990000\">So I just went to ClinicalTrials.gov to look up something about RAP-MD-04 that I was about to write about, <\/font><strong><font color=\"#990000\">and there&#8217;s another whole trial! posted on Christmas Day!<\/font><\/strong><\/em><font color=\"#990000\"><strong> <\/strong>It&#8217;s called <\/font><a title=\"Show study NCT03002077: Long-term Safety Study of Rapastinel as Adjunctive Therapy in Patients With Major Depressive Disorder\" href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT03002077?term=rapastinel&#038;rank=1&#038;submit_fld_opt=\"><font color=\"#990000\">Long-term Safety Study of Rapastinel as Adjunctive Therapy in Patients With Major Depressive Disorder<\/font><\/a> <font color=\"#990000\">[RAP-MD-06]. And this is what I had just typed, &quot;But those things aren&#8217;t the most alarming piece of this suite of clinical trials. The fourth trial [RAP-MD-4] is a longer term clinical trial looking at relapse prevention&#8230;&quot; I was about to talk about <em>the potential harms<\/em>. They were talking about an extension study where they were giving an intravenous drug weekly that is a kissing cousin to Ketamine, a hallucinogen. They&#8217;ve reported that Rapastunel isn&#8217;t a hallucinogen based on one published single shot trial. Now they&#8217;re going to give it weekly for up to two years as a preventative, but there&#8217;s no contingency for any continued monitoring over the long haul. And Flash, there&#8217;s appears a safety analysis. Thought broadcasting? I hope not. Anyway, here&#8217;s the new study&#8230;<\/font><\/p>\n<p class=\"small\" align=\"center\"><img loading=\"lazy\" decoding=\"async\" src=\"http:\/\/1boringoldman.com\/images\/rapastinel-4.gif\" width=\"500\" height=\"174\" border=\"0\" \/><\/p>\n<p class=\"small\" align=\"justify\"><font color=\"#990000\">&#8230; <\/font><strong><em><font color=\"#990000\">which looks for all the world like yet another trial using that same cohort<\/font><\/em><\/strong><font color=\"#990000\">. Is that kosher? Basing multiple trials on a single group of subjects? I guess the right thing to do at this point is to back off until Allergan settles down and lands on a scenario that suits them. Is this their first CNS drug trial? They&#8217;re sure making one fine mess of things so far&#8230;<\/font>    <\/p>\n<div class=\"small\" align=\"justify\">So Merry Christmas already!&#8230;<\/div>\n","protected":false},"excerpt":{"rendered":"<p>So, picking up from explanation would be welcome&hellip; and looking at the enrollments in RAP-MD-01, RAP-MD-02, and RAP-MD-03 that seem so high in those Rapastinel Clinical Trials. The way trialists pick their sample size is to do a Power Analysis. Using the Standard Deviation from a previous similar study, then pick the difference in means [&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_forum_subforum_count":0,"footnotes":""},"categories":[5],"tags":[],"class_list":["post-69683","post","type-post","status-publish","format-standard","hentry","category-opinion"],"_links":{"self":[{"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts\/69683","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=69683"}],"version-history":[{"count":35,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts\/69683\/revisions"}],"predecessor-version":[{"id":69718,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/posts\/69683\/revisions\/69718"}],"wp:attachment":[{"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/media?parent=69683"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/categories?post=69683"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/1boringoldman.com\/index.php\/wp-json\/wp\/v2\/tags?post=69683"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}