Lancet子刊:机器学习为临床研究阴性结果“平反”(Look AHEAD研究)

2017-07-23 MedSci MedSci原创

2012年,著名的Look AHEAD(糖尿病健康行动)临床试验因为阴性结果而被提前终止,这个结果曾经令业内人士大跌眼镜。不过根据最近发表在 The Lancet Diabetes & Endocrinology(《柳叶刀糖尿病和内分泌学》)的研究成果,通过采用机器学习方法进行分析后,当年被提前终止的阴性结果Look AHEAD可以“平反”了。西奈山伊坎医学院全球卫生研究所的数据科学研究人

2012年,著名的Look AHEAD(糖尿病健康行动)临床试验因为阴性结果而被提前终止,这个结果曾经令业内人士大跌眼镜。不过根据最近发表在 The Lancet Diabetes & Endocrinology(《柳叶刀糖尿病和内分泌学》)的研究成果,通过采用机器学习方法进行分析后,当年被提前终止的阴性结果Look AHEAD可以“平反”了。

先前MedSci报道:NEJM:强化生活方式干预不能减少2型糖尿病患者的心血管风险ADA 2013:2型糖尿病患者强化生活方式干预无心血管获益(Look AHEAD研究)

西奈山伊坎医学院全球卫生研究所的数据科学研究人员团队应用新的机器学习方法,对2012年由于结果缺乏统计学意义而停止的试验中所收集到的数据得出了新的结论。

由研究所首席技术官James H.Faghmous博士领导的Arnhold研究所团队重新分析了被称为Look AHEAD的试验数据。 他们发现,尽管试验总体结果无效,但85%的研究样本确实发现减重能够降低心血管死亡率和发病率。


上图显示,对Look AHEA研究区分亚组后,在85%的患者样本中显示,对照组的心血管风险高于干预组。这85%的患者在研究开始时的特征为:糖尿病控制中等或较差;或糖尿病控制良好,同时自我报告的健康状况也良好。

Look AHEAD随机对照试验中4901例患者分为2450例模型建立组和2451例测试组。基线的HbA1c和自我报告的一般健康状况区分从干预获益不同。采用COX回归模型分析主要结局,结果发现除HbA1c<6.8%且SF-36大于等于48时,干预与非干预是不能获益的,其余情况干预均有明显获益。

“我们的分析表明,机器学习因果推论(causal forest modelling)的最新进展可以增加临床相关研究的数量,作为研究人员和数据科学家,我们总是担心整体研究结果可能掩盖不同类型的患者的重大差异,然而机器研究能够识别个人,为患者提供个性化的护理。

“除了临床发现,这项工作显示了先进的机器学习方法对精准医学遗传学的积极作用。此次研究分析了5000多名超重和肥胖的糖尿病患者,随访13年。其目的是要确定,通过生活方式的适度减肥降低了死亡率和严重的心脏病以及中风风险。早期试验并没有发现两者之间的关系。

“在此次研究中,我们以数据科学和精准医学作为基本工具,数据分析结果显示,85%的2型糖尿病患者受益于体重适度减少,有效降低了心脏病等并发症的发病率,除此之外,也有15%的患者无法受益于减重。我们的研究结果虽然不适用于所有的糖尿病患者,但是,对于大多数糖尿病患者而言,通过健康的生活方式减轻体重还是大有益处的。”

Arnhold全球卫生研究所主任经济学博士,西奈山伊坎医学院卫生系统设计和全球卫生系助理教授和研究的主要作者亚伦•鲍姆(Aaron Baum)说:“机器学习技术在因果推论方面的最新进展可以使大规模临床试验的临床相关结果数量得到增加,作为研究人员和数据科学家,我们总是担心研究本来已经发现了不同类型患者在获益和风险方面的重要差异,却可能被整体研究结果所掩盖。能够识别出从干预措施获益的个体,这对患者诊疗来说具有重要意义。”

该研究的资深作者和机器学习与医疗专家James H. Faghmous博士说:“除了临床研究结果,这项工作显示了先进的机器学习方法对精密医学遗传学的积极作用。

The Look AHEAD研究招募了超过5,000名超重和肥胖的糖尿病患者,计划的随访期长达13年。 其目的是要确定,通过生活方式的改变来适度减肥能否降低死亡率和患有严重的心脏病以及卒中风险。然而,美国国立卫生研究院(NIH)早期试验中并没有发现两者之间的关系,遂于2012年提前终止了Look AHEAD研究。

“这项研究加强了数据科学和精准医学的作用,使其成为一种改变医疗保健方式的重要工具,”西奈山伊坎医学院Arnhold全球卫生研究所主任、卫生系统设计与全球卫生系主任Prabhjot Singh博士说 “对于执业临床医师来说,确认哪些患者可通过干预获益是至关重要的,而忽视获益的亚组可能导致减重计划得不到报销,这就会使易感人群被忽略。”

该小组的研究结果表明,由于减肥干预,15%的受试者显著增加心血管疾病的风险,如心肌梗死或卒中。 这可能是对通常被认为是常识和无害干预所引起的不良反应的第一个提示性证据。 该亚组在基线时同时具备两个特征:轻度或治疗良好的糖尿病(HbA1c小于6.8%)和对自身健康状况感觉不甚良好的糖尿病(SF-36一般健康评分小于48)。后者与抑郁症密切相关。

2012年我国著名糖尿病专家,北京大学人民医院纪立农、阜外医院李光伟教授等在分析Look AHEAD研究失败原因时曾指出:“目前标准治疗的应用较普及,在对照组许多患者根据指南建议接受降压治疗、应用他汀类药物或阿司匹林,这些治疗的普遍应用导致减重在改善心血管病变方面并不能显示出过多优势。”“入选人群年龄偏大(45~75岁),患者入组时已有动脉粥样硬化的可能性较大,此时生活方式干预已不可能逆转其动脉粥样硬化的进展。然而,干预组与对照组主要转归的累计风险曲线几乎是平行的,干预组一直没有超过对照组。从这一趋势看,强化生活方式干预有效,但强度和时间都还不够,增加干预强度和延长随访时间有希望达到主要终点,对待这些研究应有耐心。”

从最新发表于《柳叶刀糖尿病和内分泌学》的这项研究看,中国专家当时的观点现在一定程度上得到了机器学习技术对研究数据再分析的客观证实。

这15%的患者还具有以下特点:

对干预的运动部分依从性较差,这同时也说明了:在推荐行为干预时,评估患者对于改变的意愿,是非常重要的;

在一些中期健康结果方面的改善较少,包括血糖、心理健康和血压。

研究共同作者、西奈山临床糖尿病研究所医学总监罗纳德•塔姆勒(Ronald Tamler)说:“这种分析恢复了我对基本常识的信念。 ”对于绝大多数糖尿病患者,减轻体重的健康生活方式具有重大益处,但这并不适合所有人,由于这项工作,临床医生可以推断哪些患者将从这种生活方式干预中获益最多。”

参考文献

Aaron Baum, et al. Targeting weight loss interventions to reduce cardiovascular complications of type 2 diabetes: a machine learning-based post-hoc analysis of heterogeneous treatment effects in the Look AHEAD trial. The Lancet Diabetes & Endocrinology, 2017

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    2017-08-10 nymo
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    2017-09-14 为啥子

    这个很厉害

    0

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    2017-08-20 189****7206

    学习了谢谢分享

    0

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    2018-02-23 howi
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    2017-07-29 jet747

    有意思的研究

    0

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  7. [GetPortalCommentsPageByObjectIdResponse(id=1779616, encodeId=9b051e7961665, content=<a href='/topic/show?id=e8ee21362e' target=_blank style='color:#2F92EE;'>#AHEAD#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=2136, encryptionId=e8ee21362e, topicName=AHEAD)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=560d188, createdName=nymo, createdTime=Thu Aug 10 02:07:00 CST 2017, time=2017-08-10, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=244031, encodeId=016e24403108, content=这个很厉害, beContent=null, objectType=article, channel=null, level=null, likeNumber=58, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/mONcle9pic3xwU6047w4GQZHmaJMe3cGxCqPS0x43a9R04dN3HrAn5diaR2N4pEwoibqiaiaA3m6ia3g3XbZXadIomlRa5WAvjSUHb/0, createdBy=93aa1715091, createdName=为啥子, createdTime=Thu Sep 14 20:38:51 CST 2017, time=2017-09-14, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=235256, encodeId=1fe523525667, content=学习了谢谢分享, beContent=null, objectType=article, channel=null, level=null, likeNumber=61, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/oLAjfB7s1ib06iaV3D9Tg5Kzuf9u71gZhPYMiajRtENwicoAABeQtfXOlic8ibhYSy6DvJZWUDVtjRvTfqBffr1XJ6JLtFB5kHicthl/0, createdBy=08bb2061153, createdName=189****7206, createdTime=Sun Aug 20 06:35:14 CST 2017, time=2017-08-20, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1829101, encodeId=5ae618291013d, content=<a href='/topic/show?id=1b6210686b2' target=_blank style='color:#2F92EE;'>#Lancet#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=21, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=10686, encryptionId=1b6210686b2, topicName=Lancet)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=3f0227, createdName=howi, createdTime=Fri Feb 23 10:07:00 CST 2018, time=2018-02-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=227522, encodeId=10e722e522b5, content=有意思的研究, beContent=null, objectType=article, channel=null, level=null, likeNumber=71, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/mStl88fu4NfNLvzZhgPxRl88IIG7mnPw9aCyiclFjtObkW7hiaPluxVnP8W0L50Zk28TB6bOUvDAyD1p9jfvTD8fLIANPtx1tK/0, createdBy=0b0779675, createdName=jet747, createdTime=Sat Jul 29 07:15:03 CST 2017, time=2017-07-29, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1583048, encodeId=622315830485d, content=<a href='/topic/show?id=f6e1611840d' target=_blank style='color:#2F92EE;'>#机器#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=31, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=61184, encryptionId=f6e1611840d, topicName=机器)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=13dc16973127, createdName=ms6279672939590805, createdTime=Tue Jul 25 05:07:00 CST 2017, time=2017-07-25, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=225473, encodeId=40762254e378, content=学习了谢谢分享, beContent=null, objectType=article, channel=null, level=null, likeNumber=80, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=00501987275, createdName=130****4638, createdTime=Sun Jul 23 15:47:47 CST 2017, time=2017-07-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=225460, encodeId=3bbc225460b6, content=好办法,学习了。, beContent=null, objectType=article, channel=null, level=null, likeNumber=57, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=60791943465, createdName=1e0f8808m18(暂无匿称), createdTime=Sun Jul 23 14:44:14 CST 2017, time=2017-07-23, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=225454, encodeId=8a2a22545486, content=学习,谢谢分享, beContent=null, objectType=article, channel=null, level=null, likeNumber=23, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://wx.qlogo.cn/mmopen/aLGWoFXAyMbIu3qymFOyhb9xDeHojCicsdRdyC3XXdGk2ib9yLypZuHN06WeW4HO8WN0GGrgEfvnTX8gsckof05GHOU5OM4Mvx/0, createdBy=9cee1982656, createdName=执着追梦, createdTime=Sun Jul 23 14:36:39 CST 2017, time=2017-07-23, status=1, ipAttribution=)]
    2017-07-23 130****4638

    学习了谢谢分享

    0

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    2017-07-23 1e0f8808m18(暂无匿称)

    好办法,学习了。

    0

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    2017-07-23 执着追梦

    学习,谢谢分享

    0

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