The press-release conviction of a biotech CEO and its impact on research

http://articles.washingtonpost.com/2013-09-23/national/42314943_1_intermune-scott-harkonen-actimmune

by bqe • 13 years ago

49 46 13 years ago

articles.washingtonpost.com

DanBC2• 13 years ago

This mild-to-moderate subgroup wasn’t one the researchers said they would analyze when they set up the study. Subdividing patients after the fact and looking for statistically significant results is a controversial practice. In its most extreme form, it’s scorned as “data dredging.” The term suggests that if you drag a net through a bunch of numbers enough times, you’ll come up with something significant sooner or later.

He could have just kept that data secret, and ran another trial but specifically targeted at people with mild to moderate illness. That would have protected him legally, and made the numbers look even better.

That's the kind of thing that many people are campaigning against. Companies should release all the research they do rather than cherry picking the useful (to them) results.

Bakkot• 13 years ago

Actually, that would have been way better. If they had done the study you suggest, and the result had still been significant, then he would have been entirely justified in reporting what he did.

The issue is that dividing the participants after the fact and then looking for correlation in the existing data reduces the significance of the statistic considerably (we have other statistics for that). The p-value is not representative when used that way.

But if you do another study focused on that group in particular and still get a significant result, you're fine! The problem isn't that they located a group on which the drug worked in a dishonest way, or some such - the problem is that they were dishonest to claim they had significant evidence that the drug worked on that group. If they'd done an additional study on that group in particular, they would have their evidence (or, of course, a null result).

andrewcooke2• 13 years ago

i think the person you were replying to was implying that the same data be used, while what you are arguing is that there should be new observations made (and i agree with you, if the new work is independent; i just wanted to explain why i think the original comment was arguing for greater transparency).

zebra• 13 years ago

After the company research there should be another independent research (by WHO maybe).

fpgeek2• 13 years ago

I'll suggest reading to the end of the article. They did do another trial targeted at people with mild to moderate illness. It failed: "A little more than a year into the study, more people on the drug had died (15 percent) than people on placebo (13 percent)."

aheilbut2• 13 years ago

They don't report whether that difference was significant though, do they...

jonlucc• 13 years ago

I agree that they needed the additional study (which is underway, I believe). However, I think it is important to realize the cost of another study of that size is very expensive and often small vaccine companies can't afford unplanned major studies without going back to the financial drawing board.

JshWright• 13 years ago

He wouldn't even need to keep it secret. It's completely legitimate to say "We were trying to prove XYZ and didn't, but the data does hint that ABC might be true. Let's do another study looking specifically at ABC."

This is how a lot of Science gets done.

jerrytsai2• 13 years ago

As a trained (and hopefully ethical) statistician, I agree with the interpretation that Dr. Harkonen did mis-represent the results of the trial. This article does a pretty good job describing the controversy to a layperson audience, but I do not feel the result is all that controversial.

It is well-known to statistically-minded people that p-values are computations that rely on particular assumptions being made. One of those assumptions is that only a single, pre-specified hypothesis is being tested. By making additional comparisons, the p-value that was reported by Dr. Harkonen mis-represented the true significance of the trial. Perhaps factually the p-value was 0.004, but publicizing the p-value as if it were obtained by a fair trial, as opposed to finding it in a hunt for (quasi-)statistical significance, was a manipulation of the facts to support one's personal interests. That's not science; it's bias, and self-serving bias at that.

mbreese4• 13 years ago

I'm not as convinced as you are.

Just because the original study wasn't found to be significant, that doesn't mean that an already-existing sub group wasn't significant. They used an existing clinical trait as a separate classifier to look at the patients in a different way. That isn't too controversial (if you have a high enough patient count, which was probably the biggest fault of this post-hoc analysis).

Then again, I'm a biologist. We're trained to not trust statisticians. (Or course, we're also trained to not speak in absolutes and cover every statement in doubt, so he failed in that regard too).

dalek_cannes• 13 years ago

I initially thought he was partially justified in claiming the number with the 'mild-to-medium patients' qualification if there was a real benefit in the drug that the study had not been designed to detect. Except that a follow up study focusing on the mild-to-medium subgroup failed to show statistically significant benefits.

jerrytsai2• 13 years ago

What is likely, although we cannot of course know for sure, is that the doctor looked at more than disease severity (the "existing clinical trait") as a separate classifier, hunting for subgroups for which the p-value indicated a promising trend.

The principle behind the proscription against multiple comparisons is well-known to statisticians. If we consider a 1 chance in 20 result to be statistically significant, then, randomly, on average 20 "trials" will yield one statistically significant result.

By dividing the patients into disease severity subgroups, Dr. Harkonen increased the number of "trials" from 1 to 4, thereby elevating the likelihood of yielding an effect that appeared to be statistically significant. If he also examined other subgroups in his quest to find a positive result, then he elevated the likelihood of finding a positive result toward certainty.

Our desire to find patterns and see cause and effect make us prone to confirmation bias. We can guard against this bias with care, including the use of statistics. It was not a surprise that a subsequent study looking only at the "mild-to-moderate" group did not demonstrate any benefit of the treatment. The belief that the treatment would benefit "mild-to-moderate" patients was speciously derived.

JoeAltmaier• 13 years ago

Alternate title: "Man commits fraud to profit from terminally ill patients, gets slap on wrist"?

jonnathanson3• 13 years ago

Was this article written by Dr. Harkonen's publicist or something?

The case seems pretty clear: he knowingly misrepresented the results of a drug trial for the financial benefit of his firm and, by association, himself. He did this at the possible expense of critically to terminally ill patients, and at the further expense of the scientific and medical integrity of his research. And he received 6 months of house arrest at his cushy, 3-story San Francisco home as punishment. Forgive me if I don't strain myself reaching for my violin.

I sincerely hope this piece is not representative of the journalistic integrity of the Post under its new ownership. The article's blatant slant, its casual blending of editorial opinion and facts-based reporting, and its weirdly patronizing tone (ex: "the so-called 'p-value'") do no justice to the reputation of the newspaper.

The author opens with a rather silly rhetorical question, one with an obvious answer:

"Is it a crime for a medical researcher to hype his results? To put a heavy spin on the findings when there are millions of dollars, and possibly lives, at stake?"

Yes. Yes, it is. Especially when there are millions of dollars, and possibly lives, at stake. You don't get to cut corners in the scientific method because you think you're on to something.

nkurz3• 13 years ago

I got the opposite impression. In fact, I think this may be the best medical statistics article I've ever seen in the popular press:

  But there was a problem. This mild-to-moderate subgroup
  wasn’t one the researchers said they would analyze when
  they set up the study. Subdividing patients after the
  fact and looking for statistically significant results
  is a controversial practice. In its most extreme form,
  it’s scorned as “data dredging.” The term suggests that
  if you drag a net through a bunch of numbers enough
  times, you’ll come up with something significant sooner
  or later."

I don't presume it has anything to do with Bezos, but if it does, I hope stays on a buying spree! I was inspired to find out more about the author: http://www.washingtonpost.com/david-brown/2011/02/28/AB2Y0sM...

It turns out he's a part-time journalist and part-time licensed physician: "He works four days a week at the Post and two-thirds of a day at a general internal medicine clinic in Baltimore supervising third-year medical students."

I also didn't find it biased toward Harkonen at all. Consider the closing:

  InterMune did run another trial. It was big — 826
  patients at 81 hospitals — in order to maximize the
  chance of getting clear-cut results. It enrolled only
  people with mild to moderate lung damage, the subgroup
  whose success was touted in the press release.

  And it failed. A little more than a year into the study,
  more people on the drug had died (15 percent) than people
  on placebo (13 percent). That was the death knell for the
  drug.

It even links to the actual study: http://www.ncbi.nlm.nih.gov/pubmed/19570573?dopt=Abstract

I don't know if I've ever seen a major newspaper link directly to a primary scientific paper as a source. I encourage you to read it again and see if your view changes. I've read it twice now and think it is an absolutely stellar piece of science writing, worthy of a Best Science Writing compilation.

jonnathanson3• 13 years ago

I'll give it another read in light of what you're saying, but in the meantime, to clarify one line:

"I don't presume it has anything to do with Bezos, but if it does, I hope stays on a buying spree!"

I don't presume it has anything to do with Bezos, either. I would assume (?) he hasn't really taken the reins yet, at any rate. I've since edited that statement for clarity. Not trying to blame him for anything, or attribute this to him in any way. Rather, I am hopeful that the quality improves under him.

paulftw• 13 years ago

Tone of the article was certainly skewed in Harkonen's favor, so I stopped mid-second page and turned to HN comments.

It's great that the journalist found the debunking study and mentioned it. But does the order matter? He goes on and on about how "a sizable proportion of [scientists] might be in jail today".

Most readers would drop half way through, as I did. What will they learn? Oh, there was evidence that drug can be lifesaving but technicality killed the white knight.

The problems with after-the-fact analyses are well known. I reckon there should be a strict mathematical proof why those are wrong. We just got yet another example of that. How else can you keep charlatans out if not by being rough on those who break the rules? Especially when breaking the rules possibly has lethal consequences for less sophisticated yet desperate consumers.

I'm not saying Harkonen is a charlatan, but he certainly jumped the gun. For whatever reason, but he did.

freshhawk2• 13 years ago

    Subdividing patients after the fact and looking for statistically significant
    results is a controversial practice

If by controversial they meant "is considered outright fraud" ... then yes, it is controversial. This is one of the parts that made me see an unacceptable level of bias.

There are a lot of parts that are similar to this, it might do a better than average job of explaining p-values and talking about the realities of experimental design but the tone in every case is dismissive in the "bunch of eggheads worrying about little details" kind of way.

This is so biased I assume there is an agenda here rather than just bad journalism, the other explanation is that the writer is a good writer, researched the unfamiliar terms but didn't understand any of it and is good enough at regurgitating information to make it look like they did understand it. Either way, it's awful science writing even if they did use a lot of science words correctly. I have a higher standard for my hypothetical Best Science Writing awards I guess ... like requiring they get the science right.

jonnathanson3• 13 years ago

I've reread the article a few times since reading your post, and while I might moderate the severity with which I first lashed at the author, I stand by my assessment. Here's my rationale:

1) The tone of the article is skewed in Harkonen's favor right from the outset, particularly in the way the author initially and repeatedly presumes the purity of Harkonen's motives ("saving lives"). In fact, we have no evidence of any motives other than the financial ("billion-dollar market," "$500 million opportunity," etc.).

2) Harkonen's methodology was flawed, full stop. While there might well have been something promising in the cohort he analyzed, a remainder cohort from one study does not take the place of a full set of clinical trials. Medical and statistical ethics would demand another study be conducted of the cohort Dr. Harkonen identified as more promising. Jumping the gun was unwarranted and possibly reckless. (As it turns out, a full study was later conducted, and indeed it proved the recklessness with which Harkonen leapt to his early conclusions).

3) Harkonen grossly misstated the results of the study in his press release, and, while it's hard to prove his intent, he is on record stating his financial upside in so doing. The author devotes all of a couple lines to this crucial point, then trots out a couple of irrelevant character-witness quotes to pave it over. (One quote essentially states 'If this is a crime, then a lot of scientists are in trouble!' Well, it is a crime. And if lots of other scientists are similarly cherrypicking their data and making misleading statements about it, then I'd say we have a serious problem on our hands.)

4) Your point about the closing statement in the article doesn't indicate absence of bias in favor of Harkonen. It adds some balance, yes. But it's buried at the bottom of the piece, where the typical reader either won't find it, or will glaze over it.

5) The opening paragraphs of the article, by contrast, paint a tragic portrait of an eminent and well-meaning doctor humiliated and punished for the crime of simply being overeager to help people (with the strong implication that his humiliation and punishment were unjust).

6) The author makes the repeated assertion that there is 'nothing factually inaccurate' about the content of Harkonen's press release. This is true by the letter, but not by the spirit. Harkonen cherrypicked the "facts" that he portrayed, accurately or otherwise, in that press release. And the later study bears out the potentially disastrous consequences of his having done so, negligently and recklessly.

I'll grant you that "fraud" seems a little extreme in this case, and that's where the controversy lies. But we can demonstrate mens rea, and at the very least, Harkonen committed an act of criminal negligence. That he stood to gain significantly from his misleading statements is strong circumstantial evidence in favor of fraud, though the article doesn't give us enough facts to make a definitive claim there. At the very least, we see no evidence that Harkonen was doing this to save lives -- a point the author strongly and repeatedly implies throughout the article.

mnbvcxza• 13 years ago

Who's got the Dune quote for this?

foobarbazqux• 13 years ago

Science is made up of so many things that appear obvious after they are explained.

seehafer• 13 years ago

HE WHO CONTROLS THE [STOCK] PRICE, CONTROLS THE UNIVERSE!

greenyoda• 13 years ago

Here's a statistician's take on this story:

http://wmbriggs.com/blog/?p=9308

sanskritabelt2• 13 years ago

Everybody reading this and saying 'oh! a statistician!' should remember that Briggs is also, among other things, a global warming denier.

newnewnew• 13 years ago

A lot of statisticians tend to be so.

nkurz3• 13 years ago

Thanks for pointing that out. Yes, it's hard to believe that someone with so much education (degrees in Statistics, Atmospheric Science, Meteorology, and Math) and so much professional experience (University Professor, Wall Street Quant, National Weather Service, US Air Force) would get that completely wrong. What do you figure the chances of that are? ;)

http://wmbriggs.com/blog/?page_id=1085

yarou• 13 years ago

This is very interesting. In most papers I read during uni, the p-value was always set to 0.10. But I suppose it makes sense to have a more rigorous null hypothesis testing when you are talking about saving lives. I'm curious to see, on the whole, if all researchers in pharma try to move the goalposts like this guy did.

fiatmoney• 13 years ago

Thank God R.A. Fisher still had all his toes when he invented the concept, or we could have been stuck with a P-value threshold of 0.052631579...

downandout• 13 years ago

This case, like so many others, appears to be the product of an overzealous prosecutor looking to add to his resume before he begins applying to work at much higher paying private law firms. The concept of moral hazard does not exist for prosecutors - they can take all the shots they want at other people with no consequences. Until there are consequences, we will continue seeing blatant abuses of our justice system for the personal gain of those that work within it. Though it will never happen, private law firms should simply refuse to hire former prosecutors - many of these nonsensical prosecutions would vanish overnight.

The press-release conviction of a biotech CEO and its impact on research

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