Posted on Wednesday 22 June 2016
Some day there’ll be a best seller, a popular science book that will tell a story currently still in the making – and near the beginning the book will have a chapter about the interchange between David Healy and Charlie Nemeroff in Toronto in 2000 when Healy lost a new job because he talked about the potentially fatal side effects of SSRI [and Nemeroff, then boss of bosses] undermined his job change in retaliation. And there will be a piece about how Jon Jureidini, a pediatric psychiatrist, publicly protested a published study in 2003 that fraudulently claimed that a SSRI was safe and effective in adolescent depression. And that best-selling-author-to-be will add the efforts of Bernard Carroll and Bob Rubin in 2003 and later 2006 in exposing that same Charlie Nemeroff and others for promoting treatments they had a personal financial interest in without acknowledging those interests. Then there’s Ben Goldacre who will be cited for calling attention to the essential role of data transparency in bringing the truth to light with the AllTrials initiative, or getting at a major mechanism of deceit with his COMPare project. There will be so many more who will figure into this unfolding story. But right now, in spite of a lot of prequels, that book can’t be written because the story’s not over yet. Sure enough, there’s been progress but the main story line continues, lacking an in·place general solution…
Recently, the pioneers have been mighty busy. In September, David Healy, Jon Juriedini, and their colleagues republished the 2001 study that had become a paradigm for a jury-rigged Clinical Trial report, reanalyzing it from the original dataset using the author’s own Protocol and found that despite the earlier claims, the drug was neither effective nor safe in adolescents [Restoring Study 329: efficacy and harms of paroxetine and imipramine in treatment of major depression in adolescence]. Then in March, Jon Juriedini and some other colleagues were back with another SSRIs·in·adolescents·study, this time with access to internal documents showing again how a negative Clinical Trial had been published as positive [The citalopram CIT-MD-18 pediatric depression trial: Deconstruction of medical ghostwriting, data mischaracterisation and academic malfeasance]. This study had been used as a basis for FDA Approval, and used the same technique of altering the a priori protocol – something Ben Goldacre‘s COMPare project calls “outcome switching.”
Health Care Renewalby Bernard CarrollJune 22, 2015
There is a disconnection between the FDA’s drug approval process and the reports we see in medical journals. Pharmaceutical corporations exploit this gap through adulterated, self-serving analyses, and the FDA sits on its hands. I suggest we need a new mechanism to fix the problem – by independent analyses of clinical trials data.When they analyze and publish their clinical trials in medical journals, pharmaceutical corporations have free rein to shape the analyses. The FDA conducts independent analyses of the data submitted by the corporations, and it may deny or delay approval. But the FDA does not challenge the reports that flood our medical journals, both before and after FDA approval. It is no secret that these publications are routinely biased for marketing effect, but the FDA averts its gaze. That failure of the FDA – a posture known as enforcement discretion – has been well documented. The question is why? At the same time, exposing the biases has been difficult for outsiders because the data are considered proprietary secrets.
A Specific ProposalOur primary defense against such perversions of scientific reporting is fidelity to the registered IND protocol and plan of statistical analysis. The solution is not hard to see: We need independent analyses of clinical trials because we cannot trust the corporate analyses. In effect, we need something like the Underwriters Laboratory to verify the statistical analyses of clinical trials. Nobody takes the manufacturing corporation’s word for it concerning the safety and performance of X-ray machines or cardiac defibrillators. Why treat the statistical analysis of drug trials any differently? It’s highly technical work. Who should assume that responsibility? Why not the FDA? After all, they alone see all the data. My specific proposal is for Congress to mandate that the FDA analyze all clinical trials data strictly according to the registered protocols and analysis plans. That requirement should apply to new drugs or to approved drugs being tested for new indications. It should apply also to publications reporting new trials of approved drugs. Corporations and investigators should be prohibited from publishing their own in-house statistical analyses unless verified by FDA oversight.
It is time for Congress to grasp this nettle. The time for enforcement discretion is past, and we need Congress either to direct the FDA to act or to create a new mechanism of oversight. To do nothing would be unthinkable.
There are other suggested solutions beginning to appear and I’ll cover some of them in subsequent blog posts. But this one comes first because it’s the one that makes the most sense to me. In all of the work that went into our Paxil Study 329 paper where my part was the efficacy analysis, I became convinced that insisting that the analyses follow the a priori Protocol and Statistical Analysis Plan to the letter is the only way to insure that the analysis is worthwhile. After we finished our paper, I went back and looked and every questionable trial I’d looked at had suspicious variables. My problem was that finding those Protocols was spotty. My hat’s off to Goldacre’s team for being able to run them down. The other ubiquitous problem was from inappropriate statistical testing. So Carroll’s proposal seems right as rain. The FDA has the capabilities to do the analyses, and already does them in many cases.