5分钟精读-抑郁症的解药

Do antidepressants work?抗抑郁药有效吗？

Depression is a very complex disorder and we simply have no good evidence that antidepressants help sufferers to improve.

抑郁症是一种十分复杂的疾病， 没有足够证据表明抗抑郁药可以帮助患者改善病情。

Your grief and guilt overwhelm you. You are so tired you cannot think straight. Your simple joys are lost in an invisible agony. You have pain in your head and back and stomach, real pain. The swamp of your soul suffocates you with despair. All this is your fault, you are worthless, and you might as well die. This is how depression can feel, though people’s experiences of it, including the severity of symptoms, can vary widely. This terrible disease affects about one person in 10 at some point in life and, to treat it, many millions of people have taken antidepressants. Unfortunately, we now have good reasons to think that antidepressants are not effective.

你的悲伤感和内疚感淹没了你；你的困倦使思考都无能为力；你简单的快乐消失在无形的痛苦之中；你的头、背、胃都在疼痛，实打实的疼痛；你的灵魂就像一片沼泽，使你因绝望而窒息——这些都是你的错，你一文不值，生不如死。以上这些就是抑郁症施加给人的感觉，不过具体体验和症状的严重程度因人而异。大约十分之一的人都会在人生的某一节点经历这种可怕的疾病，而为了治愈它，数百万的人都服用过抗抑郁药物。不幸的是，我们现在有充分的理由认为抗抑郁药物是无效的。

To know if antidepressants work we must, of course, pay close attention to the best evidence about these drugs. There have been many empirical trials of antidepressants, and in the past 10 years or so there have been some good meta-analyses of these trials (a meta-analysis pools data from multiple trials into a single analysis). However, there is a problem: experts disagree about the merits and problems of these empirical studies, and about what we should conclude based on them. Philosophy can help.

当然，想要知道抗抑郁药物是否有效，我们必须密切关注能证明这些药物效用的最佳证据。针对这些药物曾有过许多实证研究，并且在过去大约十年中，关于这些研究也曾有过一些很好的荟萃分析（荟萃分析指将多个实验的数据汇集到一个分析中）。然而，这里存在一个问题：专家们对这些实证研究的优点、问题以及我们应该在此基础之上得出什么结论意见不一。也许哲学可以帮助解决这一问题。

Philosophy of science is the discipline that studies the concepts and methods of science, and offers a lens through which we can understand what scientific evidence shows us about the world. After witnessing the darkness of depression and the struggle by some of my dearest friends and family to treat this disease with drugs, I began to use my training as a philosopher to understand the evidence about antidepressants. Diving into the details of how antidepressant data are generated, analysed and reported tells us that these drugs are barely effective, if at all.

科学哲学是一门研究科学的概念与方法的学科，它为我们理解科学证据所展现给我们的世界提供了一个视角。见证了抑郁症的黑暗之处以及我最亲近的家人和朋友为其经历的挣扎之后，我开始用我作为哲学家所受过的训练来理解抗抑郁药的相关证据。而我在钻研抗抑郁药研究数据生成中的细节时发现，研究和报告表明这些药品几乎没用。

Depression affects many of us. To the extent that you find the arguments in this essay convincing, the message here could be disappointing. If you are already taking antidepressants, you might decide to stop, but I urge caution. We have little reliable evidence about coming off antidepressants, though there is evidence that people can suffer from withdrawal. Moreover, we have little reliable evidence about alternative modes of intervention, such as talk therapy or lifestyle changes. So, patients should be extra cautious when considering changes to their medications, or foregoing them for other kinds of treatments. A quick essay on a difficult subject must sacrifice depth; for a fuller presentation of the arguments that follow, please see my book Medical Nihilism (2018). If you are depressed, your physician or psychiatrist has clinical experience and insight into your condition – despite the fact that most physicians overestimate the benefits and underestimate the harms of antidepressants, you should continue to consult with them, perhaps with this essay in hand.

抑郁症影响着我们之中的许多人。如果你觉得本文中的论点令人信服，那么这里的结论可能会令人失望。如果你已经在服用抗抑郁药，你可能会决定停用，但我强烈建议你保持谨慎。我们几乎没有可靠的证据表明停用抗抑郁药物的后果，尽管有证据显示，人们可能会因为戒断而遭受痛苦。此外，对于其他干预方式，如谈话疗法或者改变生活方式，我们也没有可靠的证据表明其效用。所以，当患者打算调整他们的药物治疗或放弃药物治疗而采取其他的治疗方法时，需要格外小心。一篇探讨复杂问题的短文势必会牺牲其深度；想要更全面地理解这一观点的阐述，请参阅我的书《医学虚无主义》（Medical Nihilism, 2018）。如果你患有抑郁症，而且你的医生或心理治疗师具有临床经验并且洞悉你的病情（尽管事实上大多医生高估了抗抑郁药的好处而低估了其坏处），你仍应该继续咨询他们——也许带着这篇文章。

​The best evidence about the effectiveness of antidepressants comes from randomised trials and meta-analyses of these trials. The vast majority of these studies are funded and controlled by the manufacturers of antidepressants, which isan obvious conflict of interest. These trials often last only weeks – far less than the duration that most people are on antidepressants. The subjects in these trials are selected carefully, typically excluding patients who are elderly, who have other diseases, or who are on several other drugs – in other words, the very kinds of people who are often prescribed antidepressants – which means that extrapolating the evidence from these trials to real patients is unreliable. 

证明抗抑郁药效用的最佳证据来自于一些随机试验和对这些试验的荟萃分析。这些研究中的绝大部分被这些药物的制造商资助和控制着，而这显然存在着一种利益冲突。这些研究一般只持续几周——远比大多人服用抗抑郁药的时间短。这些受试者被精心挑选过，通常不包括老人、同时患有其他疾病的人和同时服用几种不同药物的患者——换句话说，就是那些经常开抗抑郁药的人。这意味着从这些试验中推断出的结论在真正的患者身上并不可靠。

The trials that generate evidence seeming to support antidepressants get published, while trials that generate evidence suggesting that antidepressants are ineffective often remain unpublished (this widespread phenomenon is called “publication bias”). To give one prominent example, in 2012 the UK pharmaceutical company GlaxoSmithKline pleaded guilty to criminal charges for promoting the use of its antidepressant Paxil in children (there was no evidence that it was effective in children), and for misreporting trial data.

支持抗抑郁药的试验结果被发表了，而那些表明抗抑郁药无效的试验结果往往不被发表。（这一常见现象被称为“发表偏见（publication bias）”。）举一个突出的例子，2012年，英国制药公司葛兰素史克（GlaxoSmithKline）承认了一项刑事指控，罪名是在儿童中推广使用其抗抑郁药物帕罗西汀（Paxil）（目前没有证据表明它对儿童有效），并谎报了试验数据。

Every trial on antidepressants uses a scale to measure the severity of depression of subjects before and after the trial. These scales are deeply flawed, and they bias the research toward overestimating the effectiveness of antidepressants. A typical scale that is often used is called the Hamilton Rating Scale for Depression. This scale has 17 questions, each of which has several possible answers. Each answer receives a particular score, and then the scores for all the questions are added together to give an overall measure of depression severity, for a maximum score of 52 points. The hope when testing a new antidepressant in a trial is that the depression-severity score of subjects in the drug group will decrease more than the depression-severity score of subjects in the placebo group. The scale was invented in 1960 by the psychiatrist Max Hamilton in the UK, and has been in use ever since (from here on, when I mention depression-severity scores, I am talking about this scale).

每次抗抑郁药物的试验都会使用一个量表来衡量试验前后受试者的抑郁程度，但这些量表存在着严重的缺陷，它们使研究结果倾向于高估抗抑郁药的有效性。其中常使用的一个典型的量表为汉密尔顿抑郁量表，它包含着17个问题，其中每个问题都有几个可能的答案，而每个答案都有一个特定的分数，最后得到的所有答案的分数之和就是对于抑郁严重程度的总体评估，最高分为52分。当对一种新的抗抑郁药进行试验时，希望的结果就是药物组受试者在试验后的抑郁严重程度得分会比安慰剂组受试者的得分下降更多。该量表由英国精神病学家马克斯•汉密尔顿（Max Hamilton）于1960年发明，自那以后一直在使用（下文我提到的抑郁严重程度分数就是指这个量表的得分）。

The problem with this scale is that large changes in a subject’s score can occur as a result of trivial changes in a subject’s real depression. For example, there are three questions about the quality of a subject’s sleep, with a total of six possible points, and there is a question about how much a subject is fidgeting, with up to four points. So a drug that simply made people sleep better and fidget less could lower one’s depression score by 10 points. To put this in context, recent clinical guidelines in the UK have required drugs to lower depression scores on this scale by an average of only three points. When a measurement scale measures what we want it to measure, we say the scale has ‘construct validity’.The general problem with depression-severity scales is that they lack construct validity, and this contributes to overestimating the effectiveness of antidepressants.

这一量表的问题在于，受试者实际抑郁情况的细微变化，能造成得分的巨大变化。比如，这一量表中有三个问题是关于受试者睡眠质量的，共包含六个分值，有一个问题是关于受试者的烦躁情况的，包含四个分值。这意味着一种能简单地改善睡眠、减少烦躁的药物就能让一个人的抑郁严重程度得分降低多达十分。与此相对应的背景是，英国最近的临床指南只要求药物能在这张量表上平均降低三分。当一个测量量表能够有效测量我们想要测量的东西时，我们说这个量表有“建构效度（construct validity）”。抑郁严重程度量表的普遍问题是缺乏建构效度，这导致了对抗抑郁药物有效性的过高估计。

The placebo effect is when patients improve merely as a result of the medical care they have received rather than as a result of the biochemical properties of their drug. The idea is that the mere expectation that you will get better after receiving medical care can itself contribute to you getting better. Some diseases are more responsive to placebo than others, and depression is one of the most placebo-responsive of all diseases. Since much clinical research aims at discovering the true biochemical effects of drugs, trials include a control group that receives a placebo (sometimes control groups receive competitor drugs), and the allocation of subjects to the drug group or the placebo group is concealed from subjects (this is sometimes called ‘blinding’). To estimate the active biochemical effects of the drug, the measured outcomes in the drug group are compared with the measured outcomes in the placebo group.

安慰剂效应指一位病人的病情好转仅仅是由于它们所受到的医疗护理，而不是得益于药物的生化特性，这意味着单是你对治疗后好转的期望本身，就能够使你的病情好转。有些疾病相比于其它疾病对安慰剂的反应更为强烈，而抑郁症正是反应最为强烈的疾病之一。由于许多临床试验旨在找到药物真正有效的生化特性，所以试验通常会设计一个使用安慰剂的对照组（有时对照组会使用竞争药物），而药物组和安慰剂组的分配对受试者是保密的（这种做法有时被称为“盲试验（blinding）”）。为了评估药物有效的生化特性，药物组的测量结果将会与安慰剂组的测量结果进行对比。

Blind-breaking is when subjects accurately guess which group of a trial they are in. This can occur because of the presence or absence of side- effects – for example, two common side-effects of antidepressants are weight gain and problems with sexual functioning, and so if a subject in a trial on a new antidepressant gained weight and developed difficulty achieving orgasms, she might accurately guess that she was in the drug group. This accurate guess could then lead to an expectation that her symptoms of depression will improve, and then her symptoms could in fact improve, by the placebo effect alone. There is not much empirical evidence on the frequency of blind-breaking in trials of antidepressants, though some experts believe that it is very high. (A simple improvement to trials would be to ask subjects to guess their group at the end of the trial, which would give researchers some indication of the extent of the placebo effect in the trial – this is sometimes but not often done, yet could easily be done in all trials.)

当药物的副作用出现或缺失时，可能会出现受试者准确地推测出他们属于哪一个测试组的情况，这种情况被称作“盲试解除（blind-breaking）”。比如，抗抑郁药的两种常见的副作用是体重增长和性功能障碍，所以当一位抗抑郁新药试验的受试者发现自己体重增长并且难以达到高潮时，她可能会准确地猜测她属于药物组。这种准确的推测可能会导致她产生抑郁症将会改善的预期，之后她的症状也就可能仅因为这种安慰剂效应得到改善。在抗抑郁药物的实验中并没有太多经验证据表明这种“盲试解除”现象的普遍存在，不过许多专家认为这个数字非常高。（一个简单的改进试验则要求受试者在试验尾声猜测他们的组别归属，这将为研究人员提供一些关于这次试验中安慰剂效应的线索——尽管这种改进试验很容易实现，但只是偶尔被用到。）

Because blind-breaking is occurring in trials on antidepressants, and because depression itself is so placebo-responsive, some prominent researchers (such as Irving Kirsch at Harvard Medical School and Peter Gøtzsche, formerly of the Nordic Cochrane Centre in Denmark) argue that whatever small positive effect is observed in such trials could be due entirely to the placebo effect.

由于“盲试解除”在抗抑郁药试验中如此常见，而抑郁症本身又如此易受安慰剂效应的影响，一些知名研究人员（如哈佛医学院的欧文·克什（Irving Kirsch）和曾在丹麦北欧科克伦中心的皮特·戈奇(Peter Gøtzsche)）认为，在这种试验中无论结论得出了何种微小的积极影响，都可能完全是由于安慰剂效应。

Once researchers have actual measurements from a trial on antidepressants, they must analyse the data in a way that turns the numbers into meaningful evidence about the effectiveness of the drug. The best way to do this is to measure the decrease of depression severity in the drug group and in the placebo group, and then compare the difference between the two. The result is called an “effect size”.

一旦研究人员从抗抑郁药物的试验中得到了测量数据，他们就必须采取一种能将这些数据转化为关于药物效用的有效证据的方式来分析数据，而最好的方法就是分别测量药物组和安慰剂组抑郁症严重程度的下降，然后比较两者之间的差异。其结果被称为“效果值(effect size)”。

 It gives you – as a real, average patient – a rough indication of how much you could expect your symptoms of depression to improve thanks to the drug. In a moment I will tell you the result when this is done as carefully as possible with all of the data we have on antidepressants. First, though, a cautionary reminder that statistics can be weapons of deception.

作为一个真实的普通病人，它会粗略地告诉你，通过药物你的抑郁症症状会有多大程度的改善。之后我将会告诉你们一个结果，它是由我们尽可能仔细地分析所有关于抗抑郁药的数据得出的。不过，首先要警惕的是，统计数据可能是欺骗的武器。

There are many ways that researchers can analyse data from trials that render the evidence meaningless and unreliable. Here is one example. In 2018, a meta-analysis about antidepressants was published in The Lancet (one of the world’s most important medical journals). This article, by the psychiatrist Andrea Cipriani at the University of Oxford and colleagues, included many sophisticated analyses. But one simple statistic was widely discussed. This was the “odds ratio” of benefiting from antidepressants. 

研究人员可以使用许多方法去分析试验数据，从而其变得毫无意义且不可靠。比如，2018年，一篇抗抑郁药的荟萃分析发表在《柳叶刀》杂志上（世界上最重要的医学期刊之一），这篇由牛津大学精神病学家安德里亚·西普利亚尼（Andrea Cipriani）及其同事所撰写的文章包含了许多复杂的分析，但其中有一项简单的统计数据被广泛讨论——抗抑郁药有益的“优势比”。

In such studies ‘benefit’ is often defined as occurring when depression severity goes down by more than half. The odds ratio is the odds of subjects in the drug group benefiting divided by the odds of subjects in the placebo group benefiting. The result of their analysis was an odds ratio of about 1.5. On the face of it, this is an extremely modest result. But, in fact, it tells us very little.

在这些研究中，当抑郁的严重程度降低超过一半时，我们认为其“有效”。该优势比是指，药物组中有所受益者的所占比率，除以安慰剂组中受益者所占比率。他们的分析结果表显示优势比是1.5。从表面上看，这个结果很合理。但事实上，我们能从中获得的信息非常少。

To see this, consider an analogy. Imagine we are testing a drug for weight loss. For every 100 subjects in the drug group, three subjects lose one kilogramme and 97 subjects gain five kilos. For every 100 subjects in the placebo group, two lose four kilos and 98 subjects do not gain or lose any weight. How effective is the drug for weight loss? The odds ratio of weight loss is 1.5, and yet this number tells us nothing about how much weight people on average gain or lose – indeed, the number entirely conceals the real effects of the drug. Though this is an extreme analogy, it shows how cautious we must be when interpreting this celebrated meta-analysis. Unfortunately, however, in response to this work, many leading psychiatrists celebrated, and news headlines misleadingly claimed ‘The drugs do work.’ On the winding route from the hard work of these researchers to the news reports where you were most likely to hear about that study, a simple number became a lie.

要弄清这一点，可以思考这样一个类比。想象我们正在测试一种减肥药。在药物组的每100个个体中，有三个个体减重1kg，其他97个个体增重5kg。在安慰剂组中的每100个个体中，有2个个体减重4kg，其他98个个体体重不变。那么药物的减肥功效如何？可得减肥的优势比是1.5，但这并没有告诉我们人均体重增加或减少的重量——事实上，这个数字完全掩盖了药物的实际效果。尽管很极端，但该类比还是表明，我们在解读这一广受赞誉的荟萃分析法时，必须多加谨慎。然而不幸的是，在本文所讲的这些研究中，大家是这么反应的：许多领先的精神病学家纷纷庆祝，新闻头条则误导大众声称“药物确实起作用”。在从这些研究人员的努力工作，到你最有可能听到这项研究的新闻报道的曲折路线上，一个简单的数字变成了谎言。

When analysed properly, the best evidence indicates that antidepressants are not clinically beneficial. The meta-analyses worth considering, such as the one above, involve attempts to gather evidence from all trials on antidepressants, including those that remain unpublished. Of course it is impossible to know that a meta-analysis includes all unpublished evidence, because publication bias is characterised by deception, either inadvertent or wilful. Nevertheless, these meta-analyses are serious attempts to address publication bias by finding as much data as possible. What, then, do they show? 

如果分析得当，这将是证明抗抑郁药对临床没有益处的最佳证据。值得考虑的荟萃分析，如前文提到的一例，要从抗抑郁药的所有试验结果中收集证据，包括尚未发表的试验结果。当然，我们不可能知道一次荟萃分析是否包含了所有未发表的证据，因为发表论文的偏见问题带有欺骗性，无论是出于有意还是无意。尽管如此，通过搜尽可能多的数据，这类荟萃分析还是真的想要解决发表偏差的问题。那么，这样它们又能展现出什么呢？

In meta-analyses that include as much of the evidence as possible, the severity of depression among subjects who receive antidepressants goes down by approximately two points compared with subjects who receive a placebo. Two points. Remember, a depression score can go down by double that amount simply if a subject stops fidgeting. This result, found by both champions and critics of antidepressants, has been replicated year after year for more than a decade (see, for example, the meta-analyses led by Irving Kirsch in 2008, by J C Fournier in 2010, and by Janus Christian Jakobsen in 2017). The phenomena of blind-breaking, the placebo effect and unresolved publication bias could easily account for this trivial two-point reduction in severity scores.

在包含尽可能多证据的荟萃分析方法中，药物组个体的抑郁严重程度比安慰剂组的降低大约2分。仅仅“2分”。要知道，只要个体停止焦躁，抑郁的严重程度可以轻易降低4分。然而，这个由抗抑郁药物的拥护者和评论家发现的实验结果，已经被重复利用了十多年（比如由2008年Irving Kirsch、2010年J C Fournier、2017年Janus Christian Jakobsen做的荟萃分析）。盲目解除，安慰剂效应和尚未解决的发表偏见题，都可以轻而易举地解释这微不足道的2分。

We saw above how clinical guidelines have held that drugs must lower severity-depression scores by three points to be deemed effective. On this standard, antidepressants do not pass. Worse, some psychiatrists have argued that this standard is too low – they say that, for an antidepressant to be clinically significant, it must lower depression severity by at least seven points, compared with a placebo. No drug does this.

我们在前面提到，临床指南是如何认定药物必须将抑郁严重度的分值降低3分才被视为有效。以此衡量，抗抑郁药不过关。更糟糕的是，一些精神科医生认为这个标准太低了——他们认为，想要判定抗抑郁药是否有临床价值，与安慰剂相比，它必须将抑郁症的严重程度降低至少7分。但没有药物做到这一点。

In short, we have plenty of reasons to think that antidepressants have no clinically meaningful benefits for those suffering from depression. Conversely, we know that these drugs cause many harmful side-effects, including weight gain, sexual problems, fatigue and insomnia. Some studies have demonstrated a link between antidepressants and the risk of violence, suicide, childhood and teenage aggression, and psychotic events in women.

总之，我们有很充分的理由相信，抗抑郁药对那些饱受抑郁折磨的人没有临床价值。相反，我们知道这些药物会引起许多副作用，比如增重、性功能障碍、疲劳以及失眠。一些研究表明，抗抑郁药物与暴力行为、自杀、儿童和青少年暴力倾向及女性的精神疾病风险之间存在关联。

An early theory about depression is that it is constituted by a low concentration ofserotonin.Since the class of antidepressants known as ‘selective serotonin reuptake inhibitors’ (SSRIs) helps to increase serotonin levels, it was widely thought that there was a solid theoretical basis for treating depression with SSRIs. However, most researchers now think that this is a grossly simplistic and misleading theory of depression.

一项早期的抑郁症研究发现，抑郁症由低浓度的5羟色胺引起。由于被称为“选择性5-羟色胺再摄取抑制剂”（SSRIs）的抗抑郁药有助于提高血清素水平，因此人们普遍相信用SSRIs治疗抑郁症有坚实的理论基础。然而，大多数研究者如今认为，该这一抑郁症理论过于简单，会造成误导。 

One of the main reasons for the serotonin-deficiency theory was the belief that SSRIs are effective at treating depression. The thinking was as follows. Premise one: SSRIs modulate pathological serotonin levels; premise two: SSRIs treat depression; conclusion: depression is constituted by pathological serotonin levels. Notice that, even if this reasoning was persuasive, it would not provide independent grounds for thinking that SSRIs are effective, since that is a premise of the reasoning. So, one cannot respond to this essay by saying ‘but we have theoretical reasons for thinking that antidepressants are effective’. Moreover, the thesis of this essay calls into doubt the second premise.

5羟色胺不足理论站不住脚的主要原因之一是，该理论认为，SSRIs能有效治疗抑郁症。推理如下，前提一：SSRIs调节病理性5羟色胺水平；前提二：SSRIs治疗抑郁症; 结论：抑郁症是由致病的5羟色胺含量导致。请注意，SSRIs有效本来作为一个推理的结果在这里却是一个前提，就算是这种推理有说服力，这条推理也因缺乏独立性而难以支撑SSRIs有效这个结论。所以，人们不能用“但我们有理论依据证明抗抑郁药是有效的”来反驳本文。而且本文的论点质疑第二个前提是否成立。

Conversely, there is another theoretical consideration that seems to speak against antidepressants. Some critics claim that many diagnosed cases of depression are not cases of real disease, but rather involve the ‘medicalisation’ of normal life – normal grief, stress, anxiety or simply suburban sadness being brought into the jurisdiction of medicine. If a case of sadness is inappropriately medicalised, goes this thought, then treatment with pharmaceuticals is also inappropriate. However, I do not find this criticism of antidepressants compelling. Beneath its surface lurk controversial premises about the concept of disease, the nature of normality and the proper jurisdiction of medicine. We treat many normal aspects of life with external aids, such as morning drowsiness with coffee, shyness with alcohol and erectile dysfunction with drugs. So, in short, these theoretical considerations – about the pathophysiology of depression or about the medicalisation of depression – are not persuasive one way or another regarding the effectiveness of antidepressants. 

与此相反的，还有另一种理论似乎在声讨抗抑郁药。 一些批评者称，许多被诊断患有抑郁症的病例并不是真的患病，而是正常的生活被“医学化”——正常的悲伤，压力，焦虑或仅仅是“郊区悲伤”（ 指郊区生活的种种不便、生活枯燥乏味、没有盼头，久而久之带来的悲伤情感）被划入药物的管辖范围。如果一个悲伤的情况被误诊成疾病，那么接下来用药物来治疗也会不合适。但是，我发现对抗抑郁药的批评不能让人信服。在这种批评的表面下，隐藏着具有争议的问题如什么是病，什么是正常，如何妥善用药。我们常利用外部帮助来克服生活中许多正常不过的情况，例如靠咖啡驱赶清晨的倦怠，用酒精战胜内心的羞怯，用药物克服勃起功能障碍。简而言之，在看待抗抑郁症药物是否有效的问题上，无论是用病理生理学看待抑郁症，还是“医学化”抑郁症，这些考量无论怎样都没有说服力。

That said, we ought to be suspicious of theories that characterise depression as a simple disease, constituted by a deficiency of such-and-such a chemical – as most researchers recognise, depression is not like scurvy (constituted by a deficiency of vitamin C) or Type 1 diabetes (constituted by a deficiency of insulin). We can cure scurvy with vitamin C, and treatment of Type 1 diabetes with insulin is miraculous. Since depression is a complex disease, it is implausible to expect that it could be successfully treated just by nudging chemical levels, as we do with scurvy. 

也就是说，有些理论将抑郁症描述成一种简单疾病，认为抑郁症是因为某些化学物质的缺失，对此，但我们应该持怀疑态度。正如大多数研究人员所认识到的那样，抑郁症不像坏血病（由缺乏维生素C导致）或一型糖尿病（由胰岛素缺乏导致）。我们可以用维生素C治愈坏血病，用胰岛素治疗一型糖尿病的效果也很令人惊叹。但抑郁症是一种复杂的疾病，我们总不能盼着能像治疗坏血病一样，调节一下化学物指数就能治愈抑郁症。

I have been focusing on evidence from trials on antidepressants. Despite all of the problems I have noted about these trials, they are nevertheless our best source of evidence about the effectiveness of antidepressants. However, there is another source of evidence we could consider: the experience of real patients. You – or your friends and loved ones – might have taken antidepressants, and this could have convinced you that such drugs can be effective for some people.

我一直专注于收集关于抗抑郁药物试验的证据。除了我提到的这些试验中的问题外，这些试验，仍然是我们关于抗抑郁药有效性的最佳证据来源。然而，还有另一种证据值得我们考虑，那就是抑郁症患者的亲身经历。你，你的朋友，或者至亲至爱的人可能服用过抗抑郁症药物，你可能因此相信这类药物对某些人有效。

Attending to the testimony of patients is integral to good medicine. But such testimony is typically not a good guide to causal inference. First-person reports are unreliable when determining whether or not antidepressants are effective. There are at least three reasons for this. First, the severity of symptoms of depression fluctuates and improves over time, and people tend to seek treatment when their symptoms are more severe. So, after being treated, symptoms are likely to improve, not because the treatment is effective but merely because time passes, like the gradual healing of a wound.

关注病人的自述是进行有效治疗的不可或缺的一个手段。但这样的证据通常不能很好地指导因果推理。首先，在衡量抗抑郁症药物是否有效上，自述并不可靠，原因至少有三个。首先，抑郁症症状的严重程度起伏不定，并可能随时间推移有所改善，而且当症状加重时，人们会倾向于寻求治疗。因此在被诊断治疗后，症状可能有所改善，不是因为治疗方案有效，而很可能是因为时间的推移，就像伤口的自然恢复一样。

Second, depression is very placebo-responsive. For a large proportion of subjects in the placebo group of trials, depression-severity scores decrease by as much as 10 or 15 points. The placebo effect is amazing – for example, bigger placebo pills elicit greater effects than small pills. Third, confirmation bias is the tendency of people to notice evidence that confirms their expectations and ignore evidence that disconfirms their expectations. This cognitive failure affects us all. After taking an antidepressant, people tend to notice signs of their health improving more than they notice opposing signs.

其次，抑郁症对安慰剂反应强烈。就安慰剂组试验中的大部分受试者来看，抑郁严重程度评分可降低多达10或15分。安慰剂效应是很惊人的，比如更大的安慰剂药片比小药丸影响更大。其三，确认偏见现象，是指人们倾向于注意那些证实他们预期的证据，而忽视那些与他们预期相反的证据。这种认知失败影响着我们所有人。服用抗抑郁药后，相比于自己健康恶化的情况，人们往往会注意到自己健康状况改善的迹象。

So, if you hear of someone benefiting from antidepressants, this was likely due to the natural course of the disease fluctuating or improving over time, confounded by the placebo effect, and exaggerated by confirmation bias. This is not to doubt the testimony of patients. Their first-person experience is, ultimately, the most real and most important phenomenon in medicine. We must listen to it. But, away from the clinical encounter, sitting at our desks with statistics, science and sober reflection, when we listen, what do we hear? Placebo, not Prozac.

因此，如果你听闻有些人服用抗抑郁症药物后情况有所改善，这可能是因为，疾病症状浮动的正常进程（服药后正好处于低潮），或是随着时间推进的自身改善，其中还夹杂着安慰剂效应，以及因为确认偏见的存在，正面效果被夸大。这不是在质疑病人的说辞，归根结底，他们的亲身经历对于医学界来说肯定是最真实、最重要的，我们必须倾听。但当我们远离临床试验，坐在办公桌边上带着统计学、科学知识，去冷静思考，去倾听时，我们听到了什么？听到的是安慰剂，而不是百忧解。