Can a Form Letter from FDA "Blow Your Mind"?

Adam Feuerstein appears to be a generally astute observer of the biotech scene. As a finance writer, he's accosted daily with egregiously hyped claims from small drug companies and their investors, and I think he tends to do an excellent job of spotting cases where breathless excitement is unaccompanied by substantive information.

However, Feuerstein's healthy skepticism seems to have abandoned him last year in the case of a biotech called Sarepta Therapeutics, who released some highly promising - but also incredibly limited - data on their treatment for Duchenne muscular dystrophy. After a disappointing interaction with the FDA, Sarepta's stock dropped, and Feuerstein appeared to realize that he'd lost some objectivity on the topic.

However, with the new year comes new optimism, and Feuerstein seems to be back to squinting hard at tea leaves - this time in the case of a form letter from the FDA.

He claims that the contents of the letter will "blow your mind". To him, the key passage is:

We understand that you feel that eteplirsen is highly effective, and may be confused by what you have read or heard about FDA's actions on eteplirsen. Unfortunately, the information reported in the press or discussed in blogs does not necessarily reflect FDA's position. FDA has reached no conclusions about the possibility of using accelerated approval for any new drug for the treatment of Duchenne muscular dystrophy, and for eteplirsen in particular.

Feuerstein appears to think that the fact that FDA "has reached no conclusions" may mean that it may be "changing its mind". To which he adds: "Wow!"

Adam Feuerstein: This time,
too much froth, not enough coffee?

I'm not sure why he thinks that. As far as I can tell, the FDA will never reach a conclusion like this before its gone through the actual review process. After all, if FDA already knows the answer before the full review, what would the point of the review even be? It would seem a tremendous waste of agency resources. Not to mention how non-level the playing field would be if some companies were given early yes/no decisions while others had to go through a full review.

It seems fair to ask: is this a substantive change by FDA review teams, or would it be their standard response to any speculation about whether and how they would approve or reject a new drug submission? Can Feuerstein point to other cases where FDA has given a definitive yes or no on an application before the application was ever filed? I suspect not, but am open to seeing examples.

A more plausible theory for this letter is that the FDA is attempting a bit of damage control. It is not permitted to share anything specific it said or wrote to Sarepta about the drug, and has come under some serious criticism for “rejecting” Sarepta’s Accelerated Approval submission. The agency has been sensitive to the DMD community, even going so far as to have Janet Woodcock and Bob Temple meet with DMD parents and advocates last February. Sarepta has effectively positioned FDA as the reason for it’s delay in approval, but no letters have actually been published, so the conversation has been a bit one-sided. This letter appears to be an attempt at balancing perspectives a bit, although the FDA is still hamstrung by its restriction on relating any specific communications.

Ultimately, this is a form letter that contains no new information: FDA has reached no conclusions because FDA is not permitted to reach conclusions until it has completed a fair and thorough review, which won't happen until the drug is actually submitted for approval.

We talk about "transparency" in terms of releasing clinical trials data, but to me there is a great case to be made for increase regulatory transparency. The benefits to routine publication of most FDA correspondence and meeting results (including such things as Complete Response letters, explaining FDA's thinking when it rejects new applications) would actually go a long way towards improving public understanding of the drug review and approval process.

Half of All Trials Unpublished*

(*For certain possibly nonstandard uses of the word "unpublished")

This is an odd little study. Instead of looking at registered trials and following them through to publication, this study starts with a random sample of phase 3 and 4 drug trials that already had results posted on ClinicalTrials.gov - so in one, very obvious sense, none of the trials in this study went unpublished.

Timing and Completeness of Trial Results Posted at ClinicalTrials.gov and Published in Journals
Carolina Riveros, Agnes Dechartres, Elodie Perrodeau, Romana Haneef, Isabelle Boutron, Philippe Ravaud

But here the authors are concerned with publication in medical journals, and they were only able to locate journal articles covering about half (297/594) of trials with registered results. 

It's hard to know what to make of these results, exactly. Some of the "missing" trials may be published in the future (a possibility the authors acknowledge), some may have been rejected by one or more journals (FDAAA requires posting the results to ClinicalTrials.gov, but it certainly doesn't require journals to accept trial reports), and some may be pre-FDAAA trials that sponsors have retroactively added to ClinicalTrials.gov even though development on the drug has ceased.

It would have been helpful had the authors reported journal publication rates stratified by the year the trials completed - this would have at least given us some hints regarding the above. More than anything I still find it absolutely bizarre that in a study this small, the entire dataset is not published for review.

One potential concern is the search methodology used by the authors to match posted and published trials. If the easy routes (link to article already provided in ClinicalTrials.gov, or NCT number found in a PubMed search) failed, a manual search was performed:

The articles identified through the search had to match the corresponding trial in terms of the information registered at ClinicalTrials.gov (i.e., same objective, same sample size, same primary outcome, same location, same responsible party, same trial phase, and same sponsor) and had to present results for the primary outcome. 

So it appears that a reviewed had to score the journal article as an exact match on 8 criteria in order for the trial to be considered the same. That could easily lead to exclusion of journal articles on the basis of very insubstantial differences. The authors provide no detail on this; and again, that would be easy to verify if the study dataset was published. 

The reason I harp on this, and worry about the matching methodology, is that two of the authors of this study were also involved in a methodologically opaque and flawed study about clinical trial results posted in the JCO. In that study, as well, the authors appeared to use an incorrect methodology to identify published clinical trials. When I pointed the issues out, the corresponding author merely reiterated what was already (insufficiently) in the paper's Methodology section.

I find it strange beyond belief, and more than a little hypocritical, that researchers would use a public, taxpayer-funded database as the basis of their studies, and yet refuse to provide their data for public review. There are no technological or logistical issues preventing this kind of sharing, and there is an obvious ethical point in favor of transparency.

But if the authors are reasonably close to correct in their results, I'm not sure what to make of this study. 

The Nature article covering this study contend that

[T]he [ClinicalTrials.gov] database was never meant to replace journal publications, which often contain longer descriptions of methods and results and are the basis for big reviews of research on a given drug.

I suppose that some journal articles have better methodology sections, although this is far from universally true (and, like this study here, these methods are often quite opaquely described and don't support replication). As for results, I don't believe that's the case. In this study, the opposite was true: ClinicalTrial.gov results were generally more complete than journal results. And I have no idea why the registry wouldn't surpass journals as a more reliable and complete source of information for "big reviews".

Perhaps it is a function of my love of getting my hands dirty digging into the data, but if we are witnessing a turning point where journal articles take a distant back seat to the ClinicalTrials.gov registry, I'm enthused. ClinicalTrials.gov is public, free, and contains structured data; journal articles are expensive, unparsable, and generally written in painfully unclear language. To me, there's really no contest. 

Carolina Riveros, Agnes Dechartres, Elodie Perrodeau, Romana Haneef, Isabelle Boutron, & Philippe Ravaud (2013). Timing and Completeness of Trial Results Posted at ClinicalTrials.gov and Published in Journals PLoS Medicine DOI: 10.1371/journal.pmed.1001566

Every Unhappy PREA Study is Unhappy in its Own Way

“Children are not small adults.” We invoke this saying, in a vague and hand-wavy manner, whenever we talk about the need to study drugs in pediatric populations. It’s an interesting idea, but it really cries out for further elaboration. If they’re not small adults, what are they? Are pediatric efficacy and safety totally uncorrelated with adult efficacy and safety? Or are children actually kind of like small adults in certain important ways?

Pediatric post-marketing studies have been completed for over 200 compounds in the years since BPCA (2002, offering a reward of 6 months extra market exclusivity/patent life to any drug conducting requested pediatric studies) and PREA (2007, giving FDA power to require pediatric studies) were enacted. I think it is fair to say that at this point, it would be nice to have some sort of comprehensive idea of how FDA views the risks associated with treating children with medications tested only on adults. Are they in general less efficacious? More? Is PK in children predictable from adult studies a reasonable percentage of the time, or does it need to be recharacterized with every drug?

Essentially, my point is that BPCA/PREA is a pretty crude tool: it is both too broad in setting what is basically a single standard for all new adult medications, and too vague as to what exactly that standard is.

In fact, a 2008 published review from FDA staffers and a 2012 Institute of Medicine report both show one clear trend: in a significant majority of cases, pediatric studies resulted in validating the adult medication in children, mostly with predictable dose and formulation adjustments (77 of 108 compounds (71%) in the FDA review, and 27 of 45 (60%) in the IOM review, had label changes that simply reflected that use of the drug was acceptable in younger patients).

So, it seems, most of the time, children are in fact not terribly unlike small adults.

But it’s also true that the percentages of studies that show lack of efficacy, or bring to light a new safety issue with the drug’s use in children, is well above zero. There is some extremely important information here.

To paraphrase John Wanamaker: we know that half our PREA studies are a waste of time; we just don’t know which half.

This would seem to me to be the highest regulatory priority – to be able to predict which new drugs will work as expected in children, and which may truly require further study. After a couple hundred compounds have gone through this process, we really ought to be better positioned to understand how certain pharmacological properties might increase or decrease the risks of drugs behaving differently than expected in children. Unfortunately, neither the FDA nor the IOM papers venture any hypotheses about this – both end up providing long lists of examples of certain points, but not providing any explanatory mechanisms that might enable us to engage in some predictive risk assessment.

While FDASIA did not advance PREA in terms of more rigorously defining the scope of pediatric requirements (or, better yet, requiring FDA to do so), it did address one lingering concern by requiring that FDA publish non-compliance letters for sponsors that do not meet their commitments. (PREA, like FDAAA, is a bit plagued by lingering suspicions that it’s widely ignored by industry.)

The first batch of letters and responses has been published, and it offers some early insights into the problems engendered by the nebulous nature of PREA and its implementation.

These examples, unfortunately, are still a bit opaque – we will need to wait on the FDA responses to the sponsors to see if some of the counter-claims are deemed credible. In addition, there are a few references to prior deferral requests, but the details of the request (and rationales for the subsequent FDA denials) do not appear to be publicly available. You can read FDA’s take on the new postings on their blog, or in the predictably excellent coverage from Alec Gaffney at RAPS.

Looking through the first 4 drugs publicly identified for noncompliance, the clear trend is that there is no trend. All these PREA requirements have been missed for dramatically different reasons.

Here’s a quick rundown of the drugs at issue – and, more interestingly, the sponsor responses:

1. Renvela - Genzyme (full response)

Genzyme appears to be laying responsibility for the delay firmly at FDA’s feet here, basically claiming that FDA continued to pile on new requirements over time:

Genzyme’s correspondence with the FDA regarding pediatric plans and design of this study began in 2006 and included a face to face meeting with FDA in May 2009. Genzyme submitted 8 revisions of the pediatric study design based on feedback from FDA including that received in 4 General Advice Letters. The Advice Letter dated February 17, 2011  contained further recommendations on the study design, yet still required the final clinical study report  by December 31, 2011.

This highlights one of PREA’s real problems: the requirements as specified in most drug approval letters are not specific enough to fully dictate the study protocol. Instead, there is a lot of back and forth between the sponsor and FDA, and it seems that FDA does not always fully account for their own contribution to delays in getting studies started.

2. Hectorol - Genzyme (full response)

In this one, Genzyme blames the FDA not for too much feedback, but for none at all:

On December 22, 2010, Genzyme submitted a revised pediatric development plan (Serial No. 212) which was intended to address FDA feedback and concerns that had been received to date. This submission included proposed protocol HECT05310. [...] At this time, Genzyme has not received feedback from the FDA on the protocol included in the December 22, 2010 submission.

If this is true, it appears extremely embarrassing for FDA. Have they really not provided feedback in over 2.5 years, and yet still sending noncompliance letters to the sponsor? It will be very interesting to see an FDA response to this.

3. Cleviprex – The Medicines Company (full response)

This is the only case where the pharma company appears to be clearly trying to game the system a bit. According to their response:

Recognizing that, due to circumstances beyond the company’s control, the pediatric assessment could not be completed by the due date, The Medicines Company notified FDA in September 2010, and sought an extension. At that time, it was FDA’s view that no extensions were available. Following the passage of FDASIA, which specifically authorizes deferral extensions, the company again sought a deferral extension in December 2012. 

So, after hearing that they had to move forward in 2010, the company promptly waited 2 years to ask for another extension. During that time, the letter seems to imply that they did not try to move the study forward at all, preferring to roll the dice and wait for changing laws to help them get out from under the obligation.

4. Twinject/Adrenaclick – Amedra (full response)

The details of this one are heavily redacted, but it may also be a bit of gamesmanship from the sponsor. After purchasing the injectors, Amedra asked for a deferral. When the deferral was denied, they simply asked for the requirements to be waived altogether. That seems backwards, but perhaps there's a good reason for that.

---

Clearly, 4 drugs is not a sufficient sample to say anything definitive, especially when we don't have FDA's take on the sponsor responses. However, it is interesting that these 4 cases seem to reflect an overall pattern with BCPA and PREA - results are scattershot and anecdotal. We could all clearly benefit from a more systematic assessment of why these trials work and why some of them don't, with a goal of someday soon abandoning one-size-fits-all regulation and focusing resources where they will do the most good.

Brazen Scofflaws? Are Pharma Companies Really Completely Ignoring FDAAA?

Results reporting requirements are pretty clear. Maybe critics should re-check their methods?

Ben Goldacre has rather famously described the clinical trial reporting requirements in the Food and Drug Administration Amendments Act of 2007 as a “fake fix” that was being thoroughly “ignored” by the pharmaceutical industry.

Pharma: breaking the law in broad daylight?

He makes this sweeping, unconditional proclamation about the industry and its regulators on the basis of  a single study in the BMJ, blithely ignoring the fact that a) the authors of the study admitted that they could not adequately determine the number of studies that were meeting FDAAA requirements and b) a subsequent FDA review that identified only 15 trials potentially out of compliance, out of a pool of thousands.


Despite the fact that the FDA, which has access to more data, says that only a tiny fraction of studies are potentially noncompliant, Goldacre's frequently repeated claims that the law is being ignored seems to have caught on in the general run of journalistic and academic discussions about FDAAA.

And now there appears to be additional support for the idea that a large percentage of studies are noncompliant with FDAAA results reporting requirements, in the form of a new study in the Journal of Clinical Oncology: "Public Availability of Results of Trials Assessing Cancer Drugs in the United States" by Thi-Anh-Hoa Nguyen, et al.. In it, the authors report even lower levels of FDAAA compliance – a mere 20% of randomized clinical trials met requirements of posting results on clinicaltrials.gov within one year.

Unsurprisingly, the JCO results were immediately picked up and circulated uncritically by the usual suspects.

I have to admit not knowing much about pure academic and cooperative group trial operations, but I do know a lot about industry-run trials – simply put, I find the data as presented in the JCO study impossible to believe. Everyone I work with in pharma trials is painfully aware of the regulatory environment they work in. FDAAA compliance is a given, a no-brainer: large internal legal and compliance teams are everywhere, ensuring that the letter of the law is followed in clinical trial conduct. If anything, pharma sponsors are twitchily over-compliant with these kinds of regulations (for example, most still adhere to 100% verification of source documentation – sending monitors to physically examine every single record of every single enrolled patient - even after the FDA explicitly told them they didn't have to).

I realize that’s anecdotal evidence, but when such behavior is so pervasive, it’s difficult to buy into data that says it’s not happening at all. The idea that all pharmaceutical companies are ignoring a highly visible law that’s been on the books for 6 years is extraordinary. Are they really so brazenly breaking the rules? And is FDA abetting them by disseminating incorrect information?

Those are extraordinary claims, and would seem to require extraordinary evidence. The BMJ study had clear limitations that make its implications entirely unclear. Is the JCO article any better?

Some Issues

In fact, there appear to be at least two major issues that may have seriously compromised the JCO findings:

1. Studies that were certified as being eligible for delayed reporting requirements, but do not have their certification date listed.

The study authors make what I believe to be a completely unwarranted assumption:

In trials for approval of new drugs or approval for a new indication, a certification [permitting delayed results reporting] should be posted within 1 year and should be publicly available.

It’s unclear to me why the authors think the certifications “should be” publicly available. In re-reading FDAAA section 801, I don’t see any reference to that being a requirement. I suppose I could have missed it, but the authors provide a citation to a page that clearly does not list any such requirement.

But their methodology assumes that all trials that have a certification will have it posted:

If no results were posted at ClinicalTrials.gov, we determined whether the responsible party submitted a certification. In this case, we recorded the date of submission of the certification to ClinicalTrials.gov.

If a sponsor gets approval from FDA to delay reporting (as is routine for all drugs that are either not approved for any indication, or being studied for a new indication – i.e., the overwhelming majority of pharma drug trials), but doesn't post that approval on the registry, the JCO authors deem that trial “noncompliant”. This is not warranted: the company may have simply chosen not to post the certification despite being entirely FDAAA compliant.

2. Studies that were previously certified for delayed reporting and subsequently reported results

It is hard to tell how the authors treated this rather-substantial category of trials. If a trial was certified for delayed results reporting, but then subsequently published results, the certification date becomes difficult to find. Indeed, it appears in the case where there were results, the authors simply looked at the time from study completion to results posting. In effect, this would re-classify almost every single one of these trials from compliant to non-compliant. Consider this example trial:

• Phase 3 trial completes January 2010
• Certification of delayed results obtained December 2010 (compliant)
• FDA approval June 2013
• Results posted July 2013 (compliant)

In looking at the JCO paper's methods section, it really appears that this trial would be classified as reporting results 3.5 years after completion, and therefore be considered noncompliant with FDAAA. In fact, this trial is entirely kosher, and would be extremely typical for many phase 2 and 3 trials in industry.

Time for Some Data Transparency

The above two concerns may, in fact, be non-issues. They certainly appear to be implied in the JCO paper, but the wording isn't terribly detailed and could easily be giving me the wrong impression.

However, if either or both of these issues are real, they may affect the vast majority of "noncompliant" trials in this study. Given the fact that most clinical trials are either looking at new drugs, or looking at new indications for new drugs, these two issues may entirely explain the gap between the JCO study and the unequivocal FDA statements that contradict it.

I hope that, given the importance of transparency in research, the authors will be willing to post their data set publicly so that others can review their assumptions and independently verify their conclusions. It would be more than a bit ironic otherwise.

[Image credit: Shamless lawlessness via Flikr user willytronics.]

Thi-Anh-Hoa Nguyen, Agnes Dechartres, Soraya Belgherbi, and Philippe Ravaud (2013). Public Availability of Results of Trials Assessing Cancer Drugs in the United States JOURNAL OF CLINICAL ONCOLOGY DOI: 10.1200/JCO.2012.46.9577

Can FDA's New Transparency Survive Avandia?

PDUFA V commitments signal a strong commitment to tolerance of open debate in the face of uncertainty.

I can admit to a rather powerful lack of enthusiasm when reading about interpersonal squabbles. It’s even worse in the scientific world: when I read about debates getting mired in personal attacks I tend to simply stop reading and move on to something else.

However, the really interesting part of this week’s meeting of an FDA joint Advisory Committee to discuss the controversial diabetes drug Avandia – at least in the sense of likely long-term impact – is not the scientific question under discussion, but the surfacing and handling of the raging interpersonal battle going on right now inside the Division of Cardiovascular and Renal Products. So I'll have to swallow my distaste and follow along with the drama.

Two words that make us mistrust Duke:
 Anil Potti Christian Laettner

Not that the scientific question at hand – does Avandia pose significant heart risks? – isn't interesting. It is. But if there’s one thing that everyone seems to agree on, it’s that we don’t have good data on the topic. Despite the re-adjudication of RECORD, no one trusts its design (and, ironically, the one trial with a design to rigorously answer the question was halted after intense pressure, despite an AdComm recommendation that it continue).  And no one seems particularly enthused about changing the current status of Avandia: in all likelihood it will continue to be permitted to be marketed under heavy restrictions. Rather than changing the future of diabetes, I suspect the committee will be content to let us slog along the same mucky trail.

The really interesting question, that will potentially impact CDER for years to come, is how it can function with frothing, open dissent among its staffers. As has been widely reported, FDA reviewer Tom Marciniak has written a rather wild and vitriolic assessment of the RECORD trial, excoriating most everyone involved. In a particularly stunning passage, Marciniak appears to claim that the entire output of anyone working at Duke University cannot be trusted because of the fraud committed by Duke cancer researcher Anil Potti:

I would have thought that the two words “Anil Potti” are sufficient for convincing anyone that Duke University is a poor choice for a contractor whose task it is to confirm the integrity of scientific research. 

(One wonders how far Marciniak is willing to take his guilt-by-association theme. Are the words “Cheng Yi Liang” sufficient to convince us that all FDA employees, including Marciniak, are poor choices for deciding matter relating to publicly-traded companies? Should I not comment on government activities because I’m a resident of Illinois (my two words: “Rod Blagojevich”)?)

Rather than censoring or reprimanding Marciniak, his supervisors have taken the extraordinary step of letting him publicly air his criticisms, and then they have in turn publicly criticized his methods and approach.

I have been unable to think of a similar situation at any regulatory agency. The tolerance for dissent being displayed by FDA is, I believe, completely unprecedented.

And that’s the cliffhanger for me: can the FDA’s commitment to transparency extend so far as to accommodate public disagreements about its own approval decisions? Can it do so even when the disagreements take an extremely nasty and inappropriate tone?

• Rather than considering that open debate is a good thing, will journalists jump on the drama and portray agency leadership as weak and indecisive?
• Will the usual suspects in Congress be able to exploit this disagreement for their own political gain? How many House subcommittees will be summoning Janet Woodcock in the coming weeks?

I think what Bob Temple and Norman Stockbridge are doing is a tremendous experiment in open government. If they can pull it off, it could force other agencies to radically rethink how they go about crafting and implementing regulations. However, I also worry that it is politically simply not a viable approach, and that the agency will ultimately be seriously hurt by attacks from the media and legislators.

Where is this coming from?

As part of its recent PDUFA V commitment, the FDA put out a fascinating draft document, Structured Approach to Benefit-Risk Assessment in Drug Regulatory Decision-Making. It didn't get a lot of attention when first published back in February (few FDA documents do). However, it lays out a rather bold vision for how the FDA can acknowledge the existence of uncertainty in its evaluation of new drugs. Its proposed structure even envisions an open and honest accounting of divergent interpretations of data:

When they're frothing at the mouth, even Atticus
doesn't let them publish a review

A framework for benefit-risk decision-making that summarizes the relevant facts, uncertainties, and key areas of judgment, and clearly explains how these factors influence a regulatory decision, can greatly inform and clarify the regulatory discussion. Such a framework can provide transparency regarding the basis of conflicting recommendations made by different parties using the same information.

(Emphasis mine.)

Of course, the structured framework here is designed to reflect rational disagreement. Marciniak’s scattershot insults are in many ways a terrible first case for trying out a new level of transparency.

The draft framework notes that safety issues, like Avandia, are some of the major areas of uncertainty in the regulatory process. Contrast this vision of coolly and systematically addressing uncertainties with the sad reality of Marciniak’s attack:

In contrast to the prospective and highly planned studies of effectiveness, safety findings emerge from a wide range of sources, including spontaneous adverse event reports, epidemiology studies, meta-analyses of controlled trials, or in some cases from randomized, controlled trials. However, even controlled trials, where the evidence of an effect is generally most persuasive, can sometimes provide contradictory and inconsistent findings on safety as the analyses are in many cases not planned and often reflect multiple testing. A systematic approach that specifies the sources of evidence, the strength of each piece of evidence, and draws conclusions that explain how the uncertainty weighed on the decision, can lead to more explicit communication of regulatory decisions. We anticipate that this work will continue beyond FY 2013.

I hope that work will continue beyond 2013. Thoughtful, open discussions of real uncertainties are one of the most worthwhile goals FDA can aspire to, even if it means having to learn how to do so without letting the Marciniaks of the world scuttle the whole endeavor.

[Update June 6: Further bolstering the idea that the AdCom is just as much about FDA's ability to transparently manage differences of expert opinion in the face of uncertain data, CDER Director Janet Woodcock posted this note on the FDA's blog. She's pretty explicit about the bigger picture:

There have been, and continue to be, differences of opinion and scientific disputes, which is not uncommon within the agency, stemming from varied conclusions about the existing data, not only with Avandia, but with other FDA-regulated products. 

At FDA, we actively encourage and welcome robust scientific debate on the complex matters we deal with — as such a transparent approach ensures the scientific input we need, enriches the discussions, and enhances our decision-making.

I agree, and hope she can pull it off.]

Our New Glass House: GSK's Commitment to AllTrials

No stones, please.

Yesterday, Alec Gaffney was kind enough to ask my opinion on GSK's signing on to the AllTrials initiative to bring full publication of clinical trial data. Some of my comments made it into his thorough and excellent article on the topic. Today, it seems worthwhile to expand on those comments.

1. It was going to happen: if not now, then soon

As mentioned in the article, I – and I suspect a fair number of other people in the industry -- already thought that full CSR publication was inevitable.  In the last half of 2012, the EMA began moving very decisively in the direction of clinical trial results publication, but that's just the culmination of a long series of steps towards greater transparency in the drug development process. Starting with the establishment of the ClinicalTrials.gov registry in 1997, we have witnessed a near-continuous increase in requirements for public registration and reporting around clinical trials.

It's important to see the AllTrials campaign in this context. If AllTrials didn't exist, something very much like it would have come along. We had been moving in this direction already (the Declaration of Helsinki called for full publication 4 years before AllTrials even existed), and the time was ripe. In fact, the only thing that I personally found surprising about AllTrials is that it started in the UK, since over the past 15 years most of the advances in trial transparency had come from the US.

2. It's a good thing, but it's not earth-shattering

Practically speaking, releasing the full CSR probably won't have a substantial impact on everyday clinical practice by doctors. The real meat of the CSR that doctors care about has already been mandated on ClinicalTrials.gov – full results posting was required by FDAAA in 2008.

There seems to be pretty clear evidence that many (perhaps most) practicing physicians do not read the complete articles on clinical trials already, but rather gravitate to abstracts and summary tables. It is highly doubtful, therefore, that a high percentage of physicians will actually read through a series of multi-hundred-page documents to try to glean fresh nuances about the drugs they prescribe.

Presumably, we'll see synopsizing services arise to provide executive summaries of the CSR data, and these may turn out to be popular and well-used. However, again, most of the really important and interesting bits are going to be on ClinicalTrial.gov in convenient table form (well, sort-of convenient – I admit I sometimes have a fair bit of difficulty sifting through the data that’s already posted there).

3. The real question: Where will we go with patient-level data?

In terms of actual positive impact on clinical research, GSK's prior announcement last October – making full patient-level data available to researchers – was a much bigger deal. That opens up the data to all sorts of potential re-analyses, including more thorough looks at patient subpopulations.

Tellingly, no one else in pharma has followed suit yet. I expect we’ll see a few more major AllTrials signatories in fairly short order (and I certainly intend to vigorously encourage all of my clients to be among the first wave of signatories!), but I don’t know that we’ll see anyone offer up the complete data sets.  To me, that will be the trend to watch over the next 2-3 years.

[Image: Transparent abode courtesy of flikr user seier+seier.]

The World's Worst Coin Trick?

Ben Goldacre – whose Bad Pharma went on sale today – is fond of using a coin-toss-cheating analogy to describe the problem of "hidden" trials in pharmaceutical clinical research. He uses it in this TED talk:

If it's a coin-toss conspiracy, it's the worst
one in the history of conspiracies.

If I flipped a coin a hundred times, but then withheld the results from you from half of those tosses, I could make it look as if I had a coin that always came up heads. But that wouldn't mean that I had a two-headed coin; that would mean that I was a chancer, and you were an idiot for letting me get away with it. But this is exactly what we blindly tolerate in the whole of evidence-based medicine. 

and in this recent op-ed column in the New York Times:

If I toss a coin, but hide the result every time it comes up tails, it looks as if I always throw heads. You wouldn't tolerate that if we were choosing who should go first in a game of pocket billiards, but in medicine, it’s accepted as the norm. 

I can understand why he likes using this metaphor. It's a striking and concrete illustration of his claim that pharmaceutical companies are suppressing data from clinical trials in an effort to make ineffective drugs appear effective. It also dovetails elegantly, from a rhetorical standpoint, with his frequently-repeated claim that "half of all trials go unpublished" (the reader is left to make the connection, but presumably it's all the tail-flip trials, with negative results, that aren't published).

Like many great metaphors, however, this coin-scam metaphor has the distinct weakness of being completely disconnected from reality.

If we can cheat and hide bad results, why do we have so many public failures? Pharmaceutical headlines in the past year were mostly dominated by a series of high-profile clinical trial failures. Even drugs that showed great promise in phase 2 failed in phase 3 and were discontinued. Less than 20% of drugs that start up in human testing ever make it to market ... and by some accounts it may be less than 10%. Pfizer had a great run of approvals to end 2012, with 4 new drugs approved by the FDA (including Xalkori, the exciting targeted therapy for lung cancer). And yet during that same period, the company discontinued 8 compounds.

Now, this wasn't always the case. Mandatory public registration of all pharma trials didn't begin in the US until 2005, and mandatory public results reporting came later than that. Before then, companies certainly had more leeway to keep results to themselves, with one important exception: the FDA still had the data. If you ran 4 phase 3 trials on a drug, and only 2 of them were positive, you might be able to only publish those 2, but when it came time to bring the drug to market, the regulators who reviewed your NDA report would be looking at the totality of evidence – all 4 trials. And in all likelihood you were going to be rejected.

That was definitely not an ideal situation, but even then it wasn't half as dire as Goldacre's Coin Toss would lead you to believe. The cases of ineffective drugs reaching the US market are extremely rare: if anything, FDA has historically been criticized for being too risk-averse and preventing drugs with only modest efficacy from being approved.

Things are even better now. There are no hidden trials, the degree of rigor (in terms of randomization, blinding, and analysis) has ratcheted up consistently over the last two decades, lots more safety data gets collected along the way, and phase 4 trials are actually being executed and reported in a timely manner. In fact, it is safe to say that medical research has never been as thorough and rigorous as it is today.

That doesn't mean we can’t get better. We can. But the main reason we can is that we got on the path to getting better 20 years ago, and continue to make improvements.

Buying into Goldacre's analogy requires you to completely ignore a massive flood of public evidence to the contrary. That may work for the average TED audience, but it shouldn't be acceptable at the level of rational public discussion.

Of course, Goldacre knows that negative trials are publicized all the time. His point is about publication bias. However, when he makes his point so broadly as to mislead those who are not directly involved in the R&D process, he has clearly stepped out of the realm of thoughtful and valid criticism.

I got my pre-ordered copy of Bad Pharma this morning, and look forward to reading it. I will post some additional thoughts on the book as I get through it. In the meantime,those looking for more can find a good skeptical review of some of Goldacre's data on the Dianthus Medical blog here and here.

[Image: Bad Pharma's Bad Coin courtesy of flikr user timparkinson.]

The Accuracy of Patient Reported Diagnoses

Novelist Phillip Roth recently got embroiled in a small spat with the editors of Wikipedia regarding the background inspiration for one of his books.  After a colleague attempted to correct the entry for The Human Stain on Roth's behalf, he received the following reply from a Wikipedia editor:

I understand your point that the author is the greatest authority on their own work, but we require secondary sources.

Report: 0% of decapitees could
accurately recall their diagnosis

The editor's response, as exasperating as it was to Roth, parallels the prevailing beliefs in clinical research about the value and reliability of Patient Reported Outcomes (PROs). On the one hand, who knows the patient better than the patient? On the other hand, our SOPs require expert physician assessment and diagnosis -- we, too, usually require secondary sources.

While recent FDA guidance has helped to solidify our approaches to incorporating PROs into traditionally-structured clinical trials, there are still a number of open questions about how far we can go with relying exclusively on what patients tell us about their medical conditions.  These questions come to the forefront when we consider the potential of "direct to patient" clinical trials, such as the recently-discontinued REMOTE trial from Pfizer, a pilot study that attempted to assess the feasibility of conducting a clinical trial without the use of local physician investigators.

Among other questions, the REMOTE trial forces us to ask: without physician assessment, how do we know the patients we recruit even have the condition being studied? And if we need more detailed medical data, how easy will it be to obtain from their regular physicians? Unfortunately, that study ended due to lack of enrollment, and Pfizer has not been particularly communicative about any lessons learned.

 Luckily for the rest of us, at least one CRO, Quintiles, is taking steps to methodically address and provide data for some of these questions.  They are moving forward with what appears to be a small series of studies that assess the feasibility and accuracy of information collected in the direct-to-patient arena. Their first step is a small pilot study of 50 patients with self-reported gout, conducted by both Quintiles and Outcomes Health Information Services.  The two companies have jointly published their data in the open-access Journal of Medical Internet Research.

(Before getting into the article's content, let me just emphatically state: kudos to the Quintiles and Outcomes teams for submitting their work to peer review, and to publication in an open access journal. Our industry needs much, much more of this kind of collaboration and commitment to transparency.)

The study itself is fairly straightforward: 50 patients were enrolled (out of 1250 US patients who were already in a Quintiles patient database with self-reported gout) and asked to complete an online questionnaire as well as permit access to their medical records.

The twin goals of the study were to assess the feasibility of collecting the patients' existing medical records and to determine the accuracy of the patients' self-reported diagnosis of gout.

To obtain patients' medical records, the study team used a belt-and-suspenders approach: first, the patients provided an electronic release along with their physicians' contact information. Then, a paper release form was also mailed to the patients, to be used as backup if the electronic release was insufficient.

To me, the results from the attempt at obtaining the medical records is actually the most interesting part of the study, since this is going to be an issue in pretty much every DTP trial that's attempted. Although the numbers are obviously quite small, the results are at least mildly encouraging:

• 38 Charts Received
• 28 required electronic release only
• 10 required paper release
• 12 Charts Not Received
• 8 no chart mailed in time
• 2 physician required paper release, patient did not provide
• 2 physician refused

If the electronic release had been used on its own, 28 charts (56%) would have been available. Adding the suspenders of a follow-up paper form increased the total to respectable 76%. The authors do not mention how aggressively they pursued obtaining the records from physicians, nor how long they waited before giving up, so it's difficult to determine how many of the 8 charts that went past the deadline could also potentially have been recovered.

Of the 38 charts received, 35 (92%) had direct confirmation of a gout diagnosis and 2 had indirect confirmation (a reference to gout medication).  Only 1 chart had no evidence for or against a diagnosis. So it is fair to conclude that these patients were highly reliable, at least insofar as their report of receiving a prior diagnosis of gout was concerned.

In some ways, though, this represents a pretty optimistic case. Most of these patients had been living with gout for many year, and "gout" is a relatively easy thing to remember.  Patients were not asked questions about the type of gout they had or any other details that might have been checked against their records.

The authors note that they "believe [this] to be the first direct-to-patient research study involving collection of patient-reported outcomes data and clinical information extracted from patient medical records." However, I think it's very worthwhile to bring up comparison with this study, published almost 20 years ago in the Annals of the Rheumatic Diseases.  In that (pre-internet) study, researchers mailed a survey to 472 patients who had visited a rheumatology clinic 6 months previously. They were therefore able to match all of the survey responses with an existing medical record, and compare the patients' self-reported diagnoses in much the same way as the current study.  Studying a more complex set of diseases (arthritis), the 1995 paper paints a more complex picture: patient accuracy varied considerably depending on their disease: from very accurate (100% for those suffering from ankylosing spondylitis, 90% for rheumatoid arthritis) to not very exact at all (about 50% for psoriatic and osteo arthritis).

Interestingly, the Quintiles/Outcomes paper references a larger ongoing study in rheumatoid arthritis as well, which may introduce some of the complexity seen in the 1995 research.

Overall, I think this pilot does exactly what it set out to do: it gives us a sense of how patients and physicians will react to this type of research, and helps us better refine approaches for larger-scale investigations. I look forward to hearing more from this team.


Cascade, E., Marr, P., Winslow, M., Burgess, A., & Nixon, M. (2012). Conducting Research on the Internet: Medical Record Data Integration with Patient-Reported Outcomes Journal of Medical Internet Research, 14 (5) DOI: 10.2196/jmir.2202



Also cited: I Rasooly, et al., Comparison of clinical and self reported diagnosis for rheumatology outpatients, Annals of the Rheumatic Diseases 1995 DOI:10.1136/ard.54.10.850

Image courtesy Flickr user stevekwandotcom.

Testing Transparency with the TEST Act

A quick update on my last post regarding the enormously controversial -- but completely unmentioned -- requirement to publicly report all versions of clinical trial protocols on ClinicalTrials.gov: The New England Journal of Medicine has weighed in with an editorial strongly in support of the TEST Act. 

NEJM Editor-in-Chief Jeffrey Drazen at least mentions the supporting documents requirement, but only in part of one sentence, where he confusingly refers to the act "extending results reporting to include the deposition of consent and protocol documents approved by institutional review boards." The word "deposition" does not suggest actual publication, which the act clearly requires. 

I don't think this qualifies as an improvement in transparency about the impact the TEST Act, as written, would have. I'm not surprised when a trade publication like Center Watch recycles a press release into a news item. However, it wouldn't seem like too much to ask that NEJM editorials aspire to a moderately higher standard of critical inquiry.

The Placebo Effect (No Placebo Necessary)

4 out of 5 non-doctors recommend starting
with "regular strength", and titrating up from there...
(Photo from inventedbyamother.com)

The modern clinical trial’s Informed Consent Form (ICF) is a daunting document.  It is packed with a mind-numbing litany of procedures, potential risks, possible adverse events, and substantial additional information – in general, if someone, somewhere, might find a fact relevant, then it gets into the form.  A run-of-the-mill ICF in a phase 2 or 3 pharma trial can easily run over 10 pages of densely worded text.  You might argue (and in fact, a number of people have, persuasively) that this sort of information overload reduces, rather than enhances, patient understanding of clinical trials.

So it is a bit of a surprise to read a paper arguing that patient information needs to be expanded because it does not contain enough information.  And it is yet even more surprising to read about what’s allegedly missing: more information about the potential effects of placebo.

Actually, “surprising” doesn’t really begin to cover it.  Reading through the paper is a borderline surreal experience.  The authors’ conclusions from “quantitative analysis”* of 45 Patient Information Leaflets for UK trials include such findings as

• The investigational medication is mentioned more often than the placebo
• The written purpose of the trial “rarely referred to the placebo”
• “The possibility of continuing on the placebo treatment after the trial was never raised explicitly”

(You may need to give that last one a minute to sink in.)

Rather than seeing these as rather obvious conclusions, the authors recast them as ethical problems to be overcome.  From the article:

Information leaflets provide participants with a permanent written record about a clinical trial and its procedures and thus make an important contribution to the process of informing participants about placebos.

And from the PR materials furnished along with publication:

We believe the health changes associated with placebos should be better represented in the literature given to patients before they take part in a clinical trial.

There are two points that I think are important here – points that are sometimes missed, and very often badly blurred, even within the research community:

1.    The placebo effect is not caused by placebos.  There is nothing special about a “placebo” treatment that induces a unique effect.  The placebo effect can be induced by a lot of things, including active medications.  When we start talking about placebos as causal agents, we are engaging in fuzzy reasoning – placebo effects will not only be seen in the placebo arm, but will be evenly distributed among all trial participants.

2.    Changes in the placebo arm cannot be assumed to be caused by the placebo effect.  There are many reasons why we may observe health changes within a placebo group, and most of them have nothing to do with the “psychological and neurological mechanisms” of the placebo effect.  Giving trial participant information about the placebo effect may in fact be providing them with an entirely inaccurate description of what is going on.

Bishop FL, Adams AEM, Kaptchuk TJ, Lewith GT (2012). Informed Consent and Placebo Effects: A Content Analysis of Information Leaflets to Identify What Clinical Trial Participants Are Told about Placebos. PLoS ONE DOI: 10.1371/journal.pone.0039661

(* Not related to the point at hand, but I would applaud efforts to establish some lower boundaries to what we are permitted to call "quantitative analysis".  Putting counts from 45 brochures into an Excel spreadsheet should fall well below any reasonable threshold.)

Public Reporting of Patient Recruitment?

A few years back, I was working with a small biotech companies as they were ramping up to begin their first-ever pivotal trial. One of the team leads had just produced a timeline for enrollment in the trial, which was being circulated for feedback. Seeing as they had never conducted a trial of this size before, I was curious about how he had arrived at his estimate. My bigger clients had data from prior trials (both their own and their CRO’s) to use, but as far as I could tell, this client had absolutely nothing.

He proudly shared with me the secret of his methodology: he had looked up some comparable studies on ClinicalTrials.gov, counted the number of listed sites, and then compared that to the sample size and start/end dates to arrive at an enrollment rate for each study. He’d then used the average of all those rates to determine how long his study would take to complete.

If you’ve ever used ClinicalTrials.gov in your work, you can immediately determine the multiple, fatal flaws in that line of reasoning. The data simply doesn’t work like that. And to be fair, it wasn’t designed to work like that: the registry is intended to provide public access to what research is being done, not provide competitive intelligence on patient recruitment.

I’m therefore sympathetic, but skeptical, of a recent article in PLoS Medicine, Disclosure of Investigators' Recruitment Performance in Multicenter Clinical Trials: A Further Step for Research Transparency, that proposes to make reporting of enrollment a mandatory part of the trial registry. The authors would like to see not only actual randomized patients for each principal investigator, but also how that compares to their “recruitment target”.

The entire article is thought-provoking and worth a read. The authors’ main arguments in favor of mandatory recruitment reporting can be boiled down to:

• Recruitment is many trials is poor, and public disclosure of recruitment performance will improve it
• Sponsors, patient groups, and other stakeholders will be interested in the information
• The data “could prompt queries” from other investigators

The first point is certainly the most compelling – improving enrollment in trials is at or near the top of everyone’s priority list – but the least supported by evidence. It is not clear to me that public scrutiny will lead to faster enrollment, and in fact in many cases it could quite conceivably lead to good investigators opting to not conduct a trial if they felt they risked being listed as “underperforming”. After all, there are many factors that will influence the total number of randomized patients at each site, and many of these are not under the PI’s control.

The other two points are true, in their way, but mandating that currently-proprietary information be given away to all competitors will certainly be resisted by industry. There are oceans of data that would be of interest to competitors, patient groups, and other investigators – that simply cannot be enough to justify mandating full public release.

Image: Philip Johnson's Glass House from Staib via Wikimedia Commons.