TED日本語 - ベン・ゴールドエイカー: 医者も知らない薬の秘密


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TED日本語 - ベン・ゴールドエイカー: 医者も知らない薬の秘密

TED Talks

What doctors don't know about the drugs they prescribe
Ben Goldacre




Hi. So, this chap here, he thinks he can tell you the future. His name is Nostradamus, although here the Sun have made him look a little bit like Sean Connery. (Laughter)

And like most of you, I suspect, I don't really believe that people can see into the future. I don't believe in precognition, and every now and then, you hear that somebody has been able to predict something that happened in the future, and that's probably because it was a fluke, and we only hear about the flukes and about the freaks. We don't hear about all the times that people got stuff wrong. Now we expect that to happen with silly stories about precognition, but the problem is, we have exactly the same problem in academia and in medicine, and in this environment, it costs lives.

So firstly, thinking just about precognition, as it turns out, just last year a researcher called Daryl Bem conducted a piece of research where he found evidence of precognitive powers in undergraduate students, and this was published in a peer-reviewed academic journal and most of the people who read this just said, "Okay, well, fair enough, but I think that's a fluke, that's a freak, because I know that if I did a study where I found no evidence that undergraduate students had precognitive powers, it probably wouldn't get published in a journal. And in fact, we know that that's true, because several different groups of research scientists tried to replicate the findings of this precognition study, and when they submitted it to the exact same journal, the journal said, "No, we're not interested in publishing replication. We're not interested in your negative data." So this is already evidence of how, in the academic literature, we will see a biased sample of the true picture of all of the scientific studies that have been conducted.

But it doesn't just happen in the dry academic field of psychology. It also happens in, for example, cancer research. So in March,2012, just one month ago, some researchers reported in the journal Nature how they had tried to replicate 53 different basic science studies looking at potential treatment targets in cancer, and out of those 53 studies, they were only able to successfully replicate six. Forty-seven out of those 53 were unreplicable. And they say in their discussion that this is very likely because freaks get published. People will do lots and lots and lots of different studies, and the occasions when it works they will publish, and the ones where it doesn't work they won't. And their first recommendation of how to fix this problem, because it is a problem, because it sends us all down blind alleys, their first recommendation of how to fix this problem is to make it easier to publish negative results in science, and to change the incentives so that scientists are encouraged to post more of their negative results in public.

But it doesn't just happen in the very dry world of preclinical basic science cancer research. It also happens in the very real, flesh and blood of academic medicine. So in 1980, some researchers did a study on a drug called lorcainide, and this was an anti-arrhythmic drug, a drug that suppresses abnormal heart rhythms, and the idea was, after people have had a heart attack, they're quite likely to have abnormal heart rhythms, so if we give them a drug that suppresses abnormal heart rhythms, this will increase the chances of them surviving. Early on its development, they did a very small trial, just under a hundred patients. Fifty patients got lorcainide, and of those patients,10 died. Another 50 patients got a dummy placebo sugar pill with no active ingredient, and only one of them died. So they rightly regarded this drug as a failure, and its commercial development was stopped, and because its commercial development was stopped, this trial was never published.

Unfortunately, over the course of the next five,10 years, other companies had the same idea about drugs that would prevent arrhythmias in people who have had heart attacks. These drugs were brought to market. They were prescribed very widely because heart attacks are a very common thing, and it took so long for us to find out that these drugs also caused an increased rate of death that before we detected that safety signal, over 100,000 people died unnecessarily in America from the prescription of anti-arrhythmic drugs.

Now actually, in 1993, the researchers who did that 1980 study, that early study, published a mea culpa, an apology to the scientific community, in which they said, "When we carried out our study in 1980, we thought that the increased death rate that occurred in the lorcainide group was an effect of chance." The development of lorcainide was abandoned for commercial reasons, and this study was never published; it's now a good example of publication bias. That's the technical term for the phenomenon where unflattering data gets lost, gets unpublished, is left missing in action, and they say the results described here "might have provided an early warning of trouble ahead."

Now these are stories from basic science. These are stories from 20,30 years ago. The academic publishing environment is very different now. There are academic journals like "Trials," the open access journal, which will publish any trial conducted in humans regardless of whether it has a positive or a negative result. But this problem of negative results that go missing in action is still very prevalent. In fact it's so prevalent that it cuts to the core of evidence-based medicine. So this is a drug called reboxetine, and this is a drug that I myself have prescribed. It's an antidepressant. And I'm a very nerdy doctor, so I read all of the studies that I could on this drug. I read the one study that was published that showed that reboxetine was better than placebo, and I read the other three studies that were published that showed that reboxetine was just as good as any other antidepressant, and because this patient hadn't done well on those other antidepressants, I thought, well, reboxetine is just as good. It's one to try. But it turned out that I was misled. In fact,seven trials were conducted comparing reboxetine against a dummy placebo sugar pill. One of them was positive and that was published, but six of them were negative and they were left unpublished. Three trials were published comparing reboxetine against other antidepressants in which reboxetine was just as good, and they were published, but three times as many patients' worth of data was collected which showed that reboxetine was worse than those other treatments, and those trials were not published. I felt misled.

Now you might say, well, that's an extremely unusual example, and I wouldn't want to be guilty of the same kind of cherry-picking and selective referencing that I'm accusing other people of. But it turns out that this phenomenon of publication bias has actually been very, very well studied. So here is one example of how you approach it. The classic model is, you get a bunch of studies where you know that they've been conducted and completed, and then you go and see if they've been published anywhere in the academic literature. So this took all of the trials that had ever been conducted on antidepressants that were approved over a 15-year period by the FDA. They took all of the trials which were submitted to the FDA as part of the approval package. So that's not all of the trials that were ever conducted on these drugs, because we can never know if we have those, but it is the ones that were conducted in order to get the marketing authorization. And then they went to see if these trials had been published in the peer-reviewed academic literature. And this is what they found. It was pretty much a 50-50 split. Half of these trials were positive, half of them were negative, in reality. But when they went to look for these trials in the peer-reviewed academic literature, what they found was a very different picture. Only three of the negative trials were published, but all but one of the positive trials were published. Now if we just flick back and forth between those two, you can see what a staggering difference there was between reality and what doctors, patients, commissioners of health services, and academics were able to see in the peer-reviewed academic literature. We were misled, and this is a systematic flaw in the core of medicine.

In fact, there have been so many studies conducted on publication bias now, over a hundred, that they've been collected in a systematic review, published in 2010, that took every single study on publication bias that they could find. Publication bias affects every field of medicine. About half of all trials, on average, go missing in action, and we know that positive findings are around twice as likely to be published as negative findings.

This is a cancer at the core of evidence-based medicine. If I flipped a coin 100 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. (Laughter) But this is exactly what we blindly tolerate in the whole of evidence-based medicine. And to me, this is research misconduct. If I conducted one study and I withheld half of the data points from that one study, you would rightly accuse me, essentially, of research fraud. And yet, for some reason, if somebody conducts 10 studies but only publishes the five that give the result that they want, we don't consider that to be research misconduct. And when that responsibility is diffused between a whole network of researchers, academics, industry sponsors, journal editors, for some reason we find it more acceptable, but the effect on patients is damning.

And this is happening right now, today. This is a drug called Tamiflu. Tamiflu is a drug which governments around the world have spent billions and billions of dollars on stockpiling, and we've stockpiled Tamiflu in panic, in the belief that it will reduce the rate of complications of influenza. Complications is a medical euphemism for pneumonia and death. (Laughter) Now when the Cochrane systematic reviewers were trying to collect together all of the data from all of the trials that had ever been conducted on whether Tamiflu actually did this or not, they found that several of those trials were unpublished. The results were unavailable to them. And when they started obtaining the writeups of those trials through various different means, through Freedom of Information Act requests, through harassing various different organizations, what they found was inconsistent. And when they tried to get a hold of the clinical study reports, the 10, 000-page long documents that have the best possible rendition of the information, they were told they weren't allowed to have them. And if you want to read the full correspondence and the excuses and the explanations given by the drug company, you can see that written up in this week's edition of PLOS Medicine.

And the most staggering thing of all of this, to me, is that not only is this a problem, not only do we recognize that this is a problem, but we've had to suffer fake fixes. We've had people pretend that this is a problem that's been fixed. First of all, we had trials registers, and everybody said, oh, it's okay. We'll get everyone to register their trials, they'll post the protocol, they'll say what they're going to do before they do it, and then afterwards we'll be able to check and see if all the trials which have been conducted and completed have been published. But people didn't bother to use those registers. And so then the International Committee of Medical Journal Editors came along, and they said, oh, well, we will hold the line. We won't publish any journals, we won't publish any trials, unless they've been registered before they began. But they didn't hold the line. In 2008, a study was conducted which showed that half of all of trials published by journals edited by members of the ICMJE weren't properly registered, and a quarter of them weren't registered at all. And then finally, the FDA Amendment Act was passed a couple of years ago saying that everybody who conducts a trial must post the results of that trial within one year. And in the BMJ, in the first edition of January,2012, you can see a study which looks to see if people kept to that ruling, and it turns out that only one in five have done so.

This is a disaster. We can not know the true effects of the medicines that we prescribe if we do not have access to all of the information.

And this is not a difficult problem to fix. We need to force people to publish all trials conducted in humans, including the older trials, because the FDA Amendment Act only asks that you publish the trials conducted after 2008, and I don't know what world it is in which we're only practicing medicine on the basis of trials that completed in the past two years. We need to publish all trials in humans, including the older trials, for all drugs in current use, and you need to tell everyone you know that this is a problem and that it has not been fixed. Thank you very much. (Applause) (Applause)

さてこの男は 自分には 未来のことがわかると考えていました ノストラダムスです サン紙では ショーン・コネリーのように見えますね (笑)

大半の人と同じく 私も未来のことがわかるとは思いません 予知は信じません ときおり 誰かが 未来を予知していたという話もありますが それはまぐれ当たりでしょう まぐれとか極端な話だけが話題になり 失敗した場合については話題にならないのです 予言のようなどうでもいい話は そんなものでしょうしかし困ったことに 全く同じ問題が学術や医学の世界にも はびこっており 時として命にも関わる問題になっているのです

最初に 予言の話だけを考えてみます つい昨年 ダリル・ベンという研究者が 学生達に予知能力があると証明する研究をまとめ 査読付きの学術論文として掲載されたことがわかりました 読者の大半の反応です 「なるほど でもまぐれか例外だろう 学生達に予知能力があるという 証拠が得られなかったという研究だったら 論文誌に載らないことは明らかなんだから」 そして まさにそのとおりだと判っています 別の複数のグループが この予知の実験結果を再現しようと試みて 同じ学術誌に投稿したときに その雑誌からは「反復実験に興味はありません ネガティブデータに興味はございません」と言われたのです この例は 学術誌において 我々が目にする姿と実際に行われた科学的研究の全体像とが ずれていることの証拠です

心理学という生死に関わらない学術分野だけの問題ではありません 例えば癌の研究でも同じ問題が起きます ほんの一ヶ月前の2012年3月に ネイチャー誌に出た報告です 癌の治療ターゲット候補に関する53件の基礎研究の 再現を試みた研究ですが 53件のうち 再現できたのは わずか6件でした 53件中47件は再現できなかったのです おそらく 特異的な結果が論文にされるので こうなるのだろうと論じられています よってたかってたくさんの研究をして うまくいった研究は公表され 失敗すると公表されません この問題に対処するため こんな提案がされています これは問題であり行き止まりの袋小路に至る問題だからです この問題を回避するために 科学的に失敗した結果の公表を簡単にすることに加え 科学者にネガティブデータの公表を奨励するような インセンティブを与えるべきだと提案されています

さらに この問題は癌の基礎研究という 治験前の基礎研究のみならず さらに生々しく肉と血を相手にする医療の学術分野でも 起きる問題です1980年に ロルカイニドと呼ばれる抗不整脈剤の 研究が行われました 心拍の異常を抑える薬です 心臓発作のあとに 不整脈が現われることが多いので 抗不整脈剤を投与すれば 生存率が向上するだろうという考えです 開発初期に極めて小規模の治験を行い 100人の患者を対象にしました 50人にロルカイニドを投与し 10人が死亡しました 残りの50人には薬効成分を含まない砂糖でできた 偽薬を投与し 死亡したのは一人でした 研究者たちは この薬は駄目だと直ちに判断し 新薬開発は中止されました 新薬開発は中止されたので治験の結果は公表されませんでした

不幸にして その後五年 十年のうちに 他の会社も同じように 心臓発作の後に投与する 抗不整脈剤のことを考えついたのです これらの薬は上市され 何しろ心臓発作は多いだけに たくさん処方されました これらの上市された薬もまた死亡率を高めてしまうことが 判明するまでには長い時間がかかったので その赤信号に気付くまでに アメリカでは死ななくてよかったはずの人が 10万人以上も亡くなりました 抗不整脈剤を処方されたための死者です

さて1993年になると 1980年に初期の研究をした研究チームは 科学界への告解文というべき論文でこう述べています 「1980年に我々の研究を行ったときに ロルカイニドを投与した群における 死亡率上昇は偶然のものと考えていた ロルカイニドの開発は事業判断により中止され結果は公にならなかった」 これは「公表バイアス」のわかりやすい例です この専門用語は 嬉しくないデータが失われたり 公表も 対応もされずに放置される現象を示します 論文には「後から生じた問題は 早期に警告できるはずだった」と書かれています

ここまでの話は20?30年前の 基礎科学におけるエピソードでした 今では学術出版の環境もすっかり変わりました オープンアクセスの「トライアル」のような学術誌は 結果のいかんを問わず人間を対象とした治験を 掲載しようという方針です それでも否定的な結果が失われがちという問題は やはり広く見られるものであり 「根拠に基づいた医療」の中核にかかわる問題です これはレボキセチンという薬で 私も処方したことがある抗うつ剤です オタク気味の医者なので この薬に関して 読みうる全ての論文を読みましたレボキセチンは 偽薬よりも良いと示す論文を1本 そして 別の3つの論文ではレボキセチンは 他の抗うつ剤と同等の効果を認められていました 私の患者には他の薬は効かなかったので レボキセチンが同等というなら試すべきだと考えました それは誤った判断とわかりました実際は 砂糖で作った偽薬とレボキセチンとの 治験は7つ行われそのうち1つの治験では 効果が認められ論文となりました 他の6つの治験では否定的な結果となり公開されないまま終わったのです レボキセチンと他の抗うつ剤を比較した? 3つの治験が公開され 同等の効果が 認められていますが その3倍もの患者数を調べ レボキセチンは他の抗うつ剤よりも劣るとわかったのに これらの処置や治験については論文になりませんでした 私は誤った判断に導かれたようです

極端に例外的なケースと 思われるかもしれません 今 問題にしている人たちのように都合のいいデータを 選ぶようなことを 私はしたくありません 結局 公表バイアスという現象は これまで大いに研究されてきたものです たとえばこんなふうに調べます 古典的モデルですが 実施されて 完了した治験を集めて これがどこかの学術雑誌に 出版されているかどうかを調べますさてここに示すのは この15年間に FDA が承認した 抗うつ薬の治験の全てです 承認手続きの一環としてFDAに提出された治験を集めたのです 実際にどれだけの治験が行われたかを知ることはできないので 全てが網羅されているとは限りませんが 製品を承認させるために行われた治験なのです さてこれらの治験について査読付学術誌での出版状況を 調べたところこんなことがわかりました 治験の成績は五分五分で治験の半分は成功 半分は否定的な結果というのが実状でしたが これらの治験についての査読付き論文を探してみると 違う描像が浮かび上がってきます 否定的な治験で論文公開されているのはわずか3報です 肯定的な治験は1件を除いて全て論文公開されています この2つの結果をよく見比べると 驚愕すべき違いがわかります 医師や患者や 健康保険の理事や学会の人々が 査読付き論文誌を通して知る姿と現実との間のギャップです 我々は誤った判断に導かれます これは医学の根本にあるシステム的な欠陥です

実際 公開バイアスに関してはこれまでに100件以上の 研究が行われてきましたが さらにその体系的なレビューが2010年に出版されました 公開バイアスに関してのあらゆる研究を 取扱ったものです 公開バイアスは医学のあらゆる領域に影響しています 平均すると 全ての治験のうち半分がやりっぱなしで失われ 肯定的な結果が論文になる割合は 否定的な結果の2倍となるとわかりました

これは根拠に基づく医学の根本におけるガンです 私がコインを100回投げてそれから その結果の半分を隠すことをしたら いつも表の出るコインを持っていると思わせることができますが 実際は違っています 私はペテン師で いんちきを許す皆さんがアホなのです(笑) でもこれが根拠に基づく医療において 見過ごされていることです 私見ですが 不適切な研究とも言えます 一つの研究として行った中で データの半分を 隠してしまったら 間違いなく不正な研究として非難されます しかしながら 理由はともあれ10件の研究を行い 自分の望む結果の得られた5件だけを論文にする人がいても これを不正な研究とは呼ばないのです さらに その責任は 研究者全体のネットワークや学会や 支援する企業や 学術誌の編集者までにわたって希薄に広がり 許容されがちです しかし 患者に及ぼされた影響こそが逃れようもない証拠です

影響は今まさに生じていることなのです この薬はタミフルです 世界中の政府が何十億ドルもかけて タミフルを備蓄してきました パニックに陥ったように競って備蓄してきました この薬がインフルエンザ合併症の割合を低減するだろうと信じたのです 合併症というのは医学的な婉曲表現で肺炎と 死亡のことです(笑) さてコクランの体系的レビュアーが タミフルが合併症を抑えるかどうかという 治験の全てのデータを収集しようとしたとき いくつかの治験の結果が公表されていないことがわかりました レビュアーは結果を入手できないのです 別の様々なルートを通じて詳細記録を集め始めましたが 情報公開法に基づいたり いくつもの組織に嫌がられながら集めたデータは整合しませんでした そして臨床研究の報告書を入手しようとしたとき その文書は1万ページにもわたって この研究についての最良の記述をしているのに これは渡せないと言われました このやりとりの全てと 製薬会社による弁解と説明にご興味があれば 全ては今週の PLOS メディスンに 掲載されています

この中で私を何よりも愕然とさせたのは このことが問題だったことに留まらず これが問題だとわかってなお 偽りの対策でごまかされていることです この問題は解決済みだというふりをする人がいるのです 最初に 治験を申請するときには口を揃えて 治験参加者全員に登録させ実施要綱も公開させると言います 申請時に言っていたとおりであれば 実施して完了した全ての治験が 出版されたかどうかは後から誰でも確認できますが 実際にはきちんと登録されていなかったのです ここで国際医学雑誌編集者委員会(ICMJE)が登場し 我々が方針を定めよう 開始前に登録されなかった治験や論文誌には 出版させないことにしようと言いました でもその方針は守られませんでした2008年に行われた研究によれば ICMJE 会員が編集する学術誌に掲載された 治験の半分は 登録が不適切で 4分の1はそもそも登録されていなかったことがわかりました そしてようやく FDA 改正法が成立しました 数年前のことです治験を行うものは誰でも その治験の結果を1年以内に投稿せよと規定しています BMJ の2012年1月号には この規定が守られているかどうかの調査が掲載され ルールに従っていたのは5件に1件に過ぎないことが 明らかになりました

ひどい状況です 全ての情報にアクセスできないようでは 処方する薬の効果について本当のところを 知ることができません

この問題を解決するのは難しいことではありません ヒトを対象とした全ての治験について 古いものも含めて公表させる必要があります FDA 改正法は 2008年以降の治験に対してのみ公開を求めています 医療を実践するのに 過去2年の治験のみを参照することなどありえません ヒトに対する治験全てを遡って 現在使用されている全ての薬を対象にして公開する必要があります この問題のこと それが未解決であることを どうか広く伝えて下さい ありがとうございます(拍手) (拍手)

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