让科学研究为女性服务

大家好，欢迎收听《柳叶刀之声》。现在是2025年9月，我是主持人加文·克利弗。科学研究的历史对女性而言是失败的。这听起来像是个大胆的论断，但数据——或者说数据的缺失——佐证了这一点。科研史就是将男性视为默认人体的历史，这意味着现有研究成果建立的系统和治疗方案往往不适用于女性。

Hello, and welcome to The Lancet Voice. It's September 2025, and I'm your host, Gavin Cleaver. The history of scientific research has failed women. It feels like a bold statement, but the data or rather the lack of data backs it up. The history of scientific research is one of treating men as the default body, meaning research has been used to create systems and treatments which aren't suited for women.

这导致女性健康结果更差，也意味着大量研究未能覆盖全体人群。我们将要提到的'性与性别平等研究指南'（简称SAGER指南），正是为了确保每项相关科学研究都能更好地考量性与性别因素。作为《柳叶刀之声》的制作人兼主持人，我同时担任柳叶刀性别与多样性工作组的联席主席。今天与我连线的嘉宾是来自里约热内卢的联席主席、《柳叶刀区域健康-美洲》主编泰莎·维拉，以及爱思唯尔集团SAGER指南推广人、性别与多样性工作组督导、《柳叶刀血液病学》主编兰兰·史密斯。我们将共同探讨研究数据中的性别议题与SAGER指南。希望您喜欢本期对话。

This leads to poorer health outcomes and means that a lot of research just isn't covering everyone. The sex and gender equity and research guidelines, which we'll refer to as the SAGER guidelines, are an attempt to make sure every relevant scientific study better accounts for sex and gender. As well as being your producer and host here at The Lancet Voice, I'm also the cochair of The Lancet's gender and diversity task force. I'm joined to discuss sex and gender in research and data and the SAGER guidelines on the line from Rio De Janeiro by my fellow cochair and editor in chief of The Lancet Regional Health Americas, Taissa Vila, and by the supervisor of the gender and diversity task force advocate of the SAGER guidelines across Elsevier and the editor in chief of The Lancet Hematology, Lan Lan Smith. We hope you enjoy the conversation.

泰莎、兰兰，非常感谢二位做客《柳叶刀之声》。我们不妨从最根本的问题开始——为什么需要这些指南？过去的科研设计如何辜负了女性？在科学研究中拥有充分细分的数据为何如此重要？

Taser, Lan Lan, thank you both so much for joining me on The Lancet Voice. Probably it's best to kick off at the beginning. Why do these guidelines exist? Like, how has scientific study design failed women in the past? What's the importance of having properly disaggregated data in in scientific research?

好的，我先来回答吧。我是兰兰，同时也参与爱思唯尔基于性与性别分析的工作流程。这是我长期致力的领域，因为我认为这项工作至关重要。

Yeah. I'm happy to kick that off if you want. So this is Lan Lan, and I'm also involved in the Elsevier sex and gender based analysis work stream. This has been something I've been working on for quite a while. And I'm working on it because it's I find it so important.

这确实是我热衷的话题。你问是否重要？传统上女性总被排除在科研之外。经典的汽车碰撞测试假人案例就是明证。

It's really a topic that I'm passionate about. And you say, is it important? Traditionally, women have been excluded from scientific research. We've all know the classic crash test dummy example. Right?

当汽车制造商开始增加安全功能时，碰撞测试假人的默认设计就是男性体型。因此遭遇车祸的女性或其他非标准男性体型者会面临更高伤害风险。心脏病学领域也是如此，女性心脏病发作时的症状表现与男性不同，却得不到同等关注。这些只是研发设计中将男性视为默认、女性作为事后补充的两个常见案例。如今我们越来越理解生物与社会因素对健康结果的不同影响。

Crash test dummies, when they started manufacturing cars with more safety features, the default design was the male body. And therefore, women who get in car accidents or others people who do not conform to the average male are at more risk from greater injuries. And the whole cardiology, women present in different ways when having a heart attack from men, and therefore are underserved. And these are just two really common examples of areas in research and development and design, where the male is considered the default and women are tacked on as a as an afterthought. And I think we're understanding more now how different biological and societal impacts have on health outcomes.

正因如此，在报告中纳入性与性别考量才如此重要。这并非新概念——加文提到的SAGER指南最初起草于2016年，而相关讨论显然更早。相信后续我们会谈及更多典型案例。

And this is why it's really important to be able to take into account sex and gender reporting. And this is not a new concept. The SAGRI guidelines that you're talking about, Gavin, these were initially written up in 2016, and, obviously, there's a lot more discussion before that about this. And I'm sure we'll come across it. We'll talk about a few more interesting examples as we get on, I'm sure.

我本来想说那感觉还是相对近期的事，对吧？2016年，考虑到这类

Was I gonna say that still feels relatively recent. Right? The 2016, given the kind of

是啊。

Yeah.

我们讨论的是科学研究的时间跨度。

The span of scientific research is what we're talking about.

确实如此。如果你想追溯得更早一点，1993年对我来说也不算太久远，我仍觉得《侏罗纪公园》昨天才上映。但当时美国国立卫生研究院通过了一项振兴法案，规定所有NIH资助的临床研究试验必须纳入女性，并设计分析变量是否对女性产生不同影响。所以我们确实有更早的追溯依据。不过是的，我同意你的看法。

That is true. You can say if you back in if you wanna go back a little bit further in 1993, which is not that long ago for me, but I still think Jurassic Park just came out yesterday. But the US National Institutes of Health had a revitalization act where it said that women had to be included in any NIH funded clinical research trials and designed to be analyzed if the variables affect women differently. So we do have a bit more going back. But yeah, I agree.

如果追溯到科学研究的萌芽期，这确实是个相对新兴的领域。

If you're going back to the very earliest days of scientific research, then this is a relatively new area.

我是泰莎。关于科学如何辜负女性这个话题，除了兰兰提到的例子，另一个例证是临床试验因激素水平或育龄问题将女性排除在外。直到90年代，FDA才允许有生育潜力的女性参与药物试验。可以想象这些排除导致我们定义的剂量、疗效、症状、风险等所有参数，都排除了可能呈现完全不同反应的人群——这些标准完全基于社会对'标准人体'的男性定义。

Yeah. Taissa here. So to your point about how science has failed women and another example that, to add to Landland's example, is exclusion of women from clinical trials because of hormone levels or childbearing age women excluding from trials as well. So it's only in the 90s that women from titer bearing potential could be included in drug trials at the FDA and you can imagine how much these exclusions had led to us defining doses, outcomes or symptoms, risks, everything excluding people that could be presenting completely different from what we call a DIFO and it's totally defined by a societal perspective of what the DFO is, which is male.

泰莎你提出了非常犀利的观点，值得重点强调：药物在男女体内的作用机制存在显著差异。但正如兰兰所说，研究长期以男性为默认模型，这种缺失对女性健康结果造成巨大损失。如果所有药物剂量标准都基于男性设定，女性每次用药都像在赌命。

I think you made a really interesting point there, Taser, which is well worth highlighting, which is that drugs, pharmaceuticals interact with male and female bodies in quite different ways. But, the research hadn't really covered this, which is a huge loss in kind of health care outcomes for women having to, as you mentioned, Lan Lan, the kind of default model of a male in these trials. If every single piece of pharmaceutical dosing is set up to treat men, the women are rolling the dice every single time.

是的。不仅仅是药物研究的主要结果，还包括不良反应特征。不同药物对人产生的副作用也可能大不相同。这让我们绕回到SAGER报告指南，它要求必须按性别和生理性别分类数据，否则就无法全面了解情况。

Yeah. And not just the primary outcomes for drug studies either, the adverse effects profile. So the side effects that people can have from different drugs can be very different as well. And that kind of brings us round to the SAGER reporting guidelines, which is saying you've got to disaggregate your data by sex and gender because otherwise, you're not looking at the whole picture.

在提交给贵期刊的试验中，你们多久能见到一次像样的性别比例分配？比如数据中男女各占50%的情况。

How often do you get a decent gender split in trials that are submitted to your journals? Like, a fifty fifty gender split, for example, in the data.

对我来说，这确实取决于疾病类型。显然，像血友病这样的疾病会严重偏向男性患者。但女性和女孩也会出血。这是血友病领域另一个可能服务不足的群体。对于血液肿瘤学领域，不同疾病存在略微不同的性别倾向。

For me, it really it depends on the disease. Obviously, for a disease like hemophilia, it's gonna massively skewed towards males. But women and girls bleed too. That's another area where they can be a bit under served in the hemophilia world. For the more hematology oncology ones, there are different diseases that have slightly different sex skews.

因此我认为对我们来说，最重要的是获得所有这些数据的报告。对于像CAR-T细胞疗法这样的临床试验，我读过很多相关论文，我们实际上能看到哪些人被排除在外——并非因为无法生产治疗产品。是否存在性别偏见之类的问题？只有确保数据报告完整，才能开始挖掘这些有趣的层面。

So I think the important thing for us is that we get all that data reported. And for trials, where you have something manufactured like a clinical, like for CAR T cell therapy, I see a lot of CAR T cell papers, we actually see who were the people who weren't, it wasn't where it wasn't possible to manufacture the product. Is there a sex bias or something like that? So when you make sure you report on the data, then you can start to tease out some interesting facets.

是的，我想这也与具体疾病和研究领域高度相关。因为不仅是SAGER指南，特定资助机构和研究机构也提出了不同的审查要求。某些领域的数据分类已经比其他领域先进得多。作为涵盖多领域的综合医学期刊，我们能明显看到这种差异——例如在某些特定领域看到分类数据远比其它领域常见，而在那些领域仍需大力推动这类数据的收集与报告工作。

Yeah, I guess it's very disease and field oriented as well, because the guidelines, not only the SAGER, but specific founders and institutions have applied different scrutinising or requests. In some areas disaggregation of data is way more advanced than in others. So for us as a general medicine journal going across multiple areas, can see the difference that for example, it's much more common to see disaggregated data for specific fields compared to others where much more needs to be done on the importance of collecting and reporting those data still.

所以这更像是需要像你们讨论不同学科领域时那样，建立一个合理的理论基础。这也正是SAGER指南的部分意义所在，对吧？至少应该标注出这些分类数据可能因某项研究的特定原因而出现某种不平衡。

So it's more about having a kind of good rationale for it as you talk about with different subject areas. And that's partially what the SAGER guidelines are about. Right? It's just at least flagging that these these disaggregated data might be imbalanced in one way or another for this particular reason related to this particular study.

没错。有意思的是SAGER其实处于流程末端——它只是报告指南。而我认为当今真正重要的是所有人都应该把这些因素直接纳入研究设计。据我所知，很多资助方已经在提出这类要求了。

Yeah. I guess it's interesting to think about it that SAGER's kind of at the end of the line. It's the reporting guidelines. Whereas I think what's really important these days is that everyone actually bakes this stuff right into their study design. And I know a lot funders are already asking for it.

所以按理说，当这些内容到达我们出版人和编辑手中时，本应已经在研究中有所体现。但遗憾的是，实际情况并非总是如此。

So it should be you know, so by the time it comes to us as publishers and editors, we should be seeing this that was already supposed to be happening in the studies already. But unfortunately, it's not always the case.

我想在讨论这个问题之前，我们最好先明确SAGRI指南的具体内容。

So I guess before we we get into talking about that, it's probably best for us to outline what the SAGRI guidelines actually say.

我认为在此之前，或许更有益的是先简单聊聊性与性别之间的区别，因为我觉得这正是人们容易混淆的地方。他们会困惑哪些内容相关、哪些该讨论？虽然对不同研究而言，我们完全可以论证性与性别对所有领域都相关。但就我个人在临床期刊工作的视角来看，当我处理大量临床试验数据时，可能'性'比'性别'对我的期刊更为相关。不过人们确实经常混用这两个术语，而它们并不完全相同。

I think before we get into that, what might be even better is to actually just have a little chat about sex versus gender, because I think that's where people get confused a little bit. And they think what is relevant and what should we talk about? Because for different studies, we can make definitely make an argument that sex and gender are relevant for everything. But when from my perspective, working on a clinical journal where I see a lot of clinical trial data, then probably sex is going to be more relevant than gender for my journal. But people do use the terms interchangeably, and they're not quite the same.

因此，'性'通常指代与生理特征相关的一系列生物属性，包括染色体、基因型、激素水平、内外生殖器等。它不仅仅涉及X和Y染色体，还包含更多与之相关的生物过程。而'性别'则属于社会建构的范畴。

So sex generally refers to a set of biological attributes that are associated with physical and physiological features such as chromosome, genotype, hormonal levels, internal and external anatomy. So it's not even just x and y chromosomes. There's a lot more. It's all the biological processes involved with that. Whereas gender refers to a social construct.

性别是一种社会建构，涉及角色、行为和身份认同，这些因素无疑也会影响健康。例如女性往往承担更多照料责任，因此可能无暇顾及自身健康——这显然会造成健康影响。这就是性别如何影响健康结果的典型案例之一。

Gender is a social construct. It has to do with roles, behaviors, identities, which can definitely have an impact on health as well. For example, women are more associated with caring responsibilities and therefore may have less time for them to care for themselves. And that definitely has a health impact. And that's one kind of example for how gender can influence outcomes as well.

从我的角度来看，我们期刊确实收录了许多医学与社会科学交叉领域的论文。对我们而言，性别数据的细分在多个层面都至关重要，因为这能帮助识别医疗可及性差异，以及那些影响健康获取和结果的偏见与污名。比如在许多国家，男性更不愿就医或坚持治疗——这对慢性病管理尤为关键；而正如Lenlan所说，女性则面临着与性别身份相关的污名化及照料负担。因此两者与社会角色的交叉影响非常值得关注。

From my perspective, I do see a lot of papers with the intersection of medicine and social science in our journal. And for us, the desegregation of gender specifically is very important in many levels because it also helps us identify disparities in access to care and other levels of bias and stigma that define access to health and health outcomes on a conception like in consequence of that. So many countries for example, men are less likely to seek care or adhere to treatment. For chronic diseases this is very relevant and on the other face as you mentioned, Lenlan, women have stigmas and caregiving burdens associated with identifying as a woman and the gender level as well. So there is the intersections of both of them and with the wider society roles that they play are very important.

我认为在指南层面，我们能做的尝试之一是改变对研究设计的看法，重新界定哪些数据值得报告和收集。随着我们对健康结果更宏观理解的深入，终将发现许多未被收集的数据其实亟需分类统计。

And I think one of the things at the guideline level that we can is to try to change how we look at the design and what is important or not important to report and collect as data as well. As we advance more and more to understand what a health outcome means in the broader picture of it, we'll identify that a lot of the data that we're not collecting are actually very important to be segregated in the end.

你刚才提到这一点，泰莎，但它确实反映了健康结果中交叉性的本质，对吧？我事先查阅过资料，有一项关于面部识别的经典研究，很好地展示了数据与健康领域中交叉性如何运作。在一项著名研究中，某面部识别系统对人脸识别的错误率显示：深色皮肤女性为35%，深色皮肤男性为12%，浅色皮肤女性为7%，而浅色皮肤男性则低于1%。这充分说明了歧视的不同维度——正如人们常说的——会如何影响个人结果，甚至系统也会与之产生交互作用。是的。

You mentioned it there, Taissa, but it speaks to the intersectional nature of health outcomes, doesn't it? I was reading up before this and there was that classic study on facial recognition that was a really good example of how intersectionality works across data and health. And there's a facial recognition system in a famous study that found that the error rates on recognizing people's faces were thirty five percent for darker skinned women, twelve percent for darker skinned men, seven percent for lighter skinned women, and less than one percent for lighter skinned men. So it shows how those different aspects of the kind of axes of discrimination as people refer to them can interact on people's outcomes and how systems even interact with them as well. Yeah.

大家必须牢记，从科学角度而言，生理性别与社会性别是人的两个不同维度，但它们会以不同方式共同影响个人的健康结果。对吧？

It's really important for people to bear in mind that sex and gender are two, scientifically two distinct aspects of a person, but they can both interact in different ways on a person's health outcomes. Right?

没错。完全正确。我认为如果要问SAGER指南的目标——虽然不确定利兰是否会同意我的观点——那就是改变社会对需要报告内容及其原因的认知。虽然我们现在是在结果端采取行动，但核心理念是终有一天我们不再需要特别提出要求，因为这将成为我们进行科研与报告的新标准。这是

Yes. Perfectly. Exactly where I think if you ask for what's the aim of the SAGER guideline, I don't know if Leland's gonna agree with me, but it's to change the societal perception of what needs to be reported and why. So while we are acting at the end, the whole idea is that at some point we don't need to actually ask for this because this is the new default of how we do science and report it. It's a

为这套国际指南奠定了重要基础，它鼓励在众多学科领域采用系统性方法报告生理性别与社会性别。研究者、作者和编辑可以将其作为全面工具，确保我们捕捉到这一至关重要的指标。

great groundwork for this international set of guidelines that encourage really systematic approach to reporting sex and gender across a lot of disciplines. And then you can apply it as a comprehensive tool for researchers, authors, editors to make sure that we capture this really important metric.

这最终会让我们发表更优质的研究成果。对吧？研究知识库会更精确，能为女性带来更好的健康结果、更公平的待遇，甚至包括我们之前讨论过的药物有效性等问题。所有这些都依赖于我们正在探讨的精准报告机制。

It just results in us publishing better research. Right? The research is a more accurate knowledge base. The outcomes are better health for women, better better equity, even the things that we've talked about before, the usefulness of pharmaceuticals. All of this stuff depends on kind of this accurate reporting that we're talking about.

是的。即使研究设计最初并未考虑按生理性别或社会性别进行数据分列——我常遇到类似推诿：'我们没设计这项试验''要达到统计功效需要双倍样本量'——但你仍然可以在事后进行这类分析，将其发表在附录中。这样未来人们就能利用这些数据进行更大规模的元分析，这同样能产生巨大价值。

Yeah. And even if people's designs haven't been designed to disaggregate by sex or gender. I often get a lot of pushback like, we didn't design the trial. We would have to recruit twice as many people to get the power calculations. But you can still do that analysis post hoc, publish it in the appendix, and then that data will be available for people to do larger meta analyses in the future, which can be really beneficial as well.

所以不必追求完美。

So it doesn't need to be perfect.

我认为在现阶段，我们对数据分组的认识已经达到了一定水平，这是与研究人员交流时最重要的信息。当你告诉他们，在进行数据分组时不必急于得出结论，而是为未来的元分析保留可能性时，他们会豁然开朗。这一点仍然非常重要。如果条件允许，请务必这样做。我认为在当前阶段，传达这一信息至关重要。

I I would say that at this stage that we are now of knowledge about disaggregation, I think this is the most important message when I talk to researchers as well. And that something clicks for them when you say it's okay if when you disaggregate you have to make sure that you don't have the power for any conclusions because that puts it in the pool of possibilities for future meta analysis. So it's still very important. If you can, please do it. And I think this is at this stage that we are, this is a really important message to send out.

对于已经招募完成的研究人员来说，这仍然是你们可以做的事情。

As for the researchers that are already recruited and done, that's still something that you can do.

Lennlan，你刚才提到了试验设计。对于可能不太了解试验设计概念的听众来说，围绕捕获这类数据设计试验与事后分析有什么区别？

And, Lennlan, you mentioned there about trial design. For our listeners who might not be all over the concept of trial design, what's the difference between designing your trial around capturing this sort of data and then versus running a post hoc analysis?

很大程度上这取决于功效计算，以及从一开始就考虑如何应用生理性别和社会性别。例如在精神病学研究中，可能需要记录受试者自我认同的性别信息，同时结合其他生物变量（如某种激素水平），并认真思考如何整合这些数据。我们该如何收集这些数据？如何让个体自我声明其性别认同？

Well, a lot of it will probably come down to power calculations and having a little bit of thought at the beginning about how to apply sex and gender. For example, a psychiatry study. Maybe they need to have a person's self identified gender to be captured, that information, along with different biological variables, such as maybe they're measuring a certain hormone level, and really thinking about how that needs to be incorporated. How are we gonna collect that data? How is it gonna be an individual will self identify as a certain gender?

或者我们是否需要通过特定的生物变量来定义生理性别，并在研究初期就考虑如何整合这些因素。然后明确如果我们想要进行正确的分组数据分析，就需要生物统计学家进行适当的功效计算，以便能基于这些维度得出结论。

Or will we be looking at specific biological variables to define the sex and really considering at the beginning how these will be incorporated. And then saying if we want to do a proper disaggregated data, getting the biostatisticians to make the proper power calculations so that they can draw conclusions based on these areas.

鉴于以上讨论，现在似乎是介绍SAGI指南的合适时机。

So this feels like a good time then, given all of that, to get to what the SAGI guidelines are.

当然，我可以简要概述一下。该指南是一套关于如何在研究设计、数据分析、结果呈现、结果解释和研究发现中报告生理性别与社会性别信息的建议。它指导作者更好地报告他们已经收集的数据。正如Lenin所说，在这个阶段，你们已经拥有这些数据。如果收集的数据足够充分，你们完全可以回头进行事后分析。

Sure, I can give a brief outline. So the guideline is a set of recommendations of how to report sex and gender information in the study design, in the data analysis, in the results, in the interpretation and in your findings. So it guides the author through how to do a better reporting of the data that they already collected. So as Lenin was saying, at this stage, you already have that. You can go back and be analysed post hoc if you have enough data collected to do it.

我们希望通过此举改变整体的报告思维方式。该指南特别强调正确使用‘生理性别’和‘社会性别’术语，正如我们全程提及研究参与者、方法及要求时那样——需要考虑如何收集数据、采用何种方法确定每个变量，并报告具体操作流程。正如所述，它主张分开报告，同时讨论这些变量与研究结果的关联性影响。因此不仅关乎数据收集，更需要批判性思考它们如何影响数据与研究发现。若未考虑这些因素，则需讨论这会如何限制最终的数据解读能力。

And what we're trying to achieve with that is change the overall mentality of how we report it. And the guideline specifically encourages the correct use of the term sex and gender as we just referred to all the way through our study participants and the methods and requests that you think about how you're going to collect that data, what methods are you going to use to determine each variable that's there and report how you did that. It advocates for separate reporting, as we mentioned, and also for discussion of the influence on the association of those variables with your findings. So it's not only about collecting, but if you can critically think about how they impact your data and your findings. And if you did not have them, then discuss how this limits your capacity to interpret your data in the end.

因此也呼吁运用性别视角和方法对研究发现进行全面反思。指南提供了核查清单（这非常重要），可确保您遵循所有要点。我认为最重要的目标是提高出版透明度、可重复性和公平性。这算是个操作指南吧。

So it also calls out for a full reflection on your findings using sex and gender interfaces and approaches as well. It provides you with a checklist, so this is really important. You can use the checklist to make sure that you're following everything. And importantly, I think the biggest aim is to improve transparency, reproducibility and equity in publishing. I guess this is a walkthrough.

我认为这是个非常全面的概述。最让我印象深刻的是，现阶段若不做这项工作会被视为局限，而且必须讨论这类缺失——不仅是我们谈到的数据报告问题，从研究设计之初就未纳入安全准则，现在已被科学界普遍视为重大缺陷。

I think it's all that's it's a really great overview of it. I think what really sticks with me is how not doing this by this point is seen as a limitation and how it's important to to discuss the lack of this sort of not even the data reporting we've been talking about, the lack of baking the safety guidelines in from the start of a study design is very much now recognized as a limitation in the scientific community.

确实非常重要。希望《柳叶刀》、细胞出版社等大型期刊集团要求提供这类信息时，能突显其价值与重要性，这将有助于指导未来的试验设计和研究设计。我知道很多资助机构已在提出要求，希望这个理念能持续传播。

Yeah. That's I think that's really important. And, hopefully, journal groups like The Lancet, Cell Press, other big journals asking for this information were flagging up that this is something that is of value and important and will help educate people for trial design and study design going forward. I know a lot of funding bodies are already asking for it. So hopefully, the message is getting out there.

作为期刊编辑，你们觉得这方面进展如何？目前投稿研究中包含这些内容的比例高吗？近几年是否有提升？整体趋势是否向好？

As journal editors, how have you found this progressing over time? Do you find that most of your studies that are submitted to you have this contained? Do you find a higher percentage over the last few years? Is it moving in the right direction?

我们于2023年将SAGER指南纳入作者须知中，大西洋集团也是较晚才采用的。虽然2016年指南发布时我们就认为这是个好主意，但直到2023年才正式整合。需要说明的是，这不仅是《柳叶刀》集团的做法。

We implemented the SAGER guidelines into our information for authors in 2023. So we only ourselves as Atlantic Group adopted them relatively recently. Although when they were first published in 2016, we obviously said, ah, this is a great idea. But it's only been incorporated at in 2023. And I have to say it's it's not just The Lancet Group.

爱思唯尔集团在这方面做了大量工作。2023年我们将其添加到所有《柳叶刀》系列期刊、细胞出版社全部期刊（虽然还没涉及真核细胞和动物模型），但SAGER同样适用于这些领域。目前覆盖超过2300种爱思唯尔期刊，这确实是项了不起的成就。

Elsevier itself has done an amazing job across this. In 2023, we got it added to all Lancet Group titles, all of Cell Press, because we haven't even touched on eukaryotic cells and animal models yet. But, yes, SAGER can apply to those as well. And over 2,300 Elsevier titles. So that's I have to say, that was a great accomplishment.

我认为目前的情况更像是我们在进行更多的提示工作。作者们的反对意见并不多。当然，有些会说‘我们做不到，因为研究样本量不足，这样没有意义’。但总体而言，确实有不少人认同我们关于添加分类数据的建议。希望未来他们能自动做到这一点。

I think at this time, it feels very much like we're really doing more prompting. I've not had a huge amount of pushback from authors. There's obviously you get ones which say, oh, we can't because wouldn't really be meaningful because the study is not powered. But in general, we do get people who agree with our prompting to add disaggregated data. And hopefully, in the future, they'll just do it automatically.

没错。因为我觉得关键在于研究人员已经承担了太多工作压力，他们要完成所有这些研究。但我们想强调的是——我认为这绝对正确——这是产出优质研究的核心环节。

Right. Because I think the argument is that researchers already have a lot to do. They're stressed they've gotta get all these research studies out. But what we're saying, which I think is absolutely right, is that this is a central part of putting out a good study.

如果你的资助方一开始就要求这么做，那么你就应该进行相关报告

And if your funding body asked you to do it in the first place, then you should be reporting on it

确实。关于《柳叶刀》如何采纳这个问题，虽然很新，但今年早些时候我们针对这个主题在杂志内部进行了作者调查。我们开展了试点研究，了解作者对指南实施的反应。虽然是小规模的问卷调查，但总体上作者对指南的接受度相当高。

as well. Yeah. To your point about how we're receiving it as LaLancet, this is really recent, but earlier in the year we conducted an internal author survey on the topic at The Lancet. So we did a pilot study to understand how our authors were receiving the implementation of the guideline. It was a small survey based study that we did, but the overall acceptance of the authors of the guidelines is quite high.

反对意见与Leland报告的情况类似，但我们有超过50%的受访者表示支持这项倡议，很高比例的人表示在被首次投稿提示后，会在下次投稿时改变做法。这是我们收到的非常好的反馈。我们还收集了关于编辑团队如何使SAGER指南更易获取和显见的建议。因此我们即将举办的SAGER网络研讨会正是基于该调查的行动之一，旨在从编辑角度更好地服务作者，持续推动对SAGER指南的遵循。

The pushbacks are similar to what Leland reported, but we have like over 50% of people responding that they encourage the initiative, that a high percentage of people saying that after being prompted by this first submission, will change their approach in their next submission. So that is very good feedback that we received. And we also collected feedback on how we as editors could help make the SAGER guidelines more accessible and visible. So how can we serve authors from the editorial perspective and acting on that, that's one of the reasons why we are doing the webinar on SAGER in the near future. This is one of our actions prompted by that survey on things that we can do to encourage and promote the SAGER guidelines adherence more and more.

是的。如果我们做完这期播客却没提三人合办的网络研讨会，MARCOMS的同事们会很不高兴。10月21日我们将举办讨论SAGER指南的网络研讨会，报名链接见节目说明。最后我想请教二位：你们认为SAGER指南之后的下步工作是什么？当然，严格来说不存在‘SAGER指南之后’这个概念，

Yes. Our MARCOMS colleagues would be quite annoyed if we got through this podcast without plugging the webinar that the three of us are doing. October 21, if you would like to join us for a webinar to discuss the SAGER guidelines, you can find the link to sign up in the show notes. I just wanted to finish up by asking you both what you think the next steps are after the SAGER guidelines. Now, obviously, there's no such thing as after the SAGER guidelines.

这永远会是编辑、作者、出版商、研究资助方等各方持续互动的过程。但就数据与报告中的交叉性而言，你们希望接下来看到哪些进展？

It's always gonna be something that is a constant back and forth between editors, authors, publishers, research funders, all that sort of thing. But, in terms of intersectionality in kind of data and reporting, what would you like to see next?

我认为你提到交叉性时一针见血，Taissa之前也谈到过这点。这非常重要。影响健康结果的因素太多了。看看我们在《柳叶刀》内部建立的杰出团队——种族平等小组，我们还在作者指南中纳入了种族与民族规范。能够综合考虑所有这些因素并引入社会经济问题，这些都是决定因素。

I think you hit the nail on the head when you said intersectionality, and Taissa touched on this earlier. That is really important. There's so many things that affect health outcomes. And just looking I we've got amazing group within The Lancet, the group for racial equity, race, and we also have a race and ethnicity guideline within our information for authors as well. So being able to consider all of these factors together and pulling in socioeconomic issues, these all have determinants.

试图纳入的因素越多，情况就越复杂，因此我认为我们应从性别议题入手。这些都是更基础的内容。但一旦大家达成共识，就能向外扩展，真正考虑其他重要因素并将其整合。说到底，这又回到了个性化医疗不是吗？需要寻找与个体相关的要素。

It gets more complicated the more factors you try to incorporate, which is why I think we're starting out with saying sex and gender. These are more and more basic things. But as once everyone's on board with that, then expanding outwards and really considering other important factors and bringing that all together. Really, I guess it's personalized medicine again, isn't it? Where you need to look at trying to get things that are relevant towards individuals.

是的，我想这就是我们的方向。如果坚持在群体层面，未来不应再查看分割的——或者说已消除隔离的数据。但只有先获得这类数据，才能观察它们如何交叉影响你所关注的结果。我希望未来能看到每个研究问题都能考量个体背景，即便是群体层面的研究。问题本身需要包含背景维度。

Yeah, I guess that's where we were going. And I think that if we want stick with the population level, the future would be not to look at separate, well desegregated data. Yes, but once you have the desegregated data, then you can look at how they intersect to influence the outcome that you're looking at. So I think if I want to see something in the future is that every single research question accounts for context of the individual, even if it's a population level research. The question needs to account for context.

而背景涵盖从生理性别到社会性别、社会经济层面、政治影响力到健康状况等所有内容。如果我们能实现这点的话。

And context involves everything from sex to gender, to socio economic aspects, to political influence and health and so on. Guess if we get there.

向着完全个性化医疗迈进吧。好的，非常感谢二位今天参与播客录制，我们一个月后的网络研讨会上再见。或许有些听众也会加入。现在先感谢二位的时间。

Onwards to fully personalized medicine. Alright. Thank you both so much for joining me on the podcast today, and I'll see you on the webinar in a month's time. Maybe some of our listeners will join us there. But for now, thank you both for your time.

谢谢，非常感谢。

Thank you. Thank you so much.

非常感谢收听本期《柳叶刀之声》。若想获取我们所有期刊的更多内容，请访问thelancet.com/podcasts查看各期刊的播客节目。下次再见，保重。

Thanks so much for listening to this episode of The Lancet Voice. If you'd like to hear more from all of our journals, you can go to thelancet.com/podcasts to see offerings from across every journal. See you again soon, and take care.