CLIN CHEM:通过液相色谱-串联质谱法测定总睾酮浓度对女性产生雄激素的肿瘤或病理性雄激素过多症的诊断阈值

2018-11-05 MedSci MedSci原创

用于筛查产生雄激素的肿瘤(APT)先前定义的总睾酮(TT)浓度阈值已在RIA使用,但其在女性中可能不太准确。本研究目的是使用通过液相色谱-串联质谱(LC-MS / MS)测量的TT浓度来确定诊断阈值以用于APT或绝经后病理性雄激素过多症的筛查。 在2004年至2014年间在明尼苏达州罗切斯特的梅奥诊所,研究人员对所有TT≥3.5nmol/ L的女性和所有绝经后女性进行了一项回顾性队列研究。

用于筛查产生雄激素的肿瘤(APT)先前定义的总睾酮(TT)浓度阈值已在RIA使用,但其在女性中可能不太准确。本研究目的是使用通过液相色谱-串联质谱(LC-MS / MS)测量的TT浓度来确定诊断阈值以用于APT或绝经后病理性雄激素过多症的筛查。

2004年至2014年间在明尼苏达州罗切斯特的梅奥诊所,研究人员对所有TT3.5nmol/ L的女性和所有绝经后女性进行了一项回顾性队列研究。

结果显示,在369TT3.5nmol/ L的女性中,总共有89人被纳入临床诊断,分为3组,2124%)例为APT16例(18%)为绝经后病理性雄激素过多症;52例(58%)为多囊卵巢综合征APT的来源更多是卵巢(81%,n = 17),而非肾上腺(19%,n = 4)。使用ROC分析TT确定严重生化性高雄激素血症女性APT的诊断阈值≥5.1nmol/ L(敏感性,90;特异性,81%)。在一组仅出现雄激素过多症状或体征的绝经后妇女的第二次分析中,绝经后病理性雄激素过多组(APT和卵巢高血压组)与特发性高雄激素血症组的中位TT升高显著相关(4.9 vs 0.8 nmol / L; P<0.01)。在绝经后妇女中,病理性雄激素过多症的诊断阈值为TT2.2nmol/ L(敏感性,100;特异性,86%)。

研究表明,通过LC-MS / MS测定生化严重高雄激素血症女性的APT诊断阈值为TT5.1nmol/ L. 在绝经后妇女中,病理性雄激素过多症的诊断阈值较低(TT2.2nmol/ L)。

原始出处:

Anu Sharma, Ekta Kapoor, C Diagnostic Thresholds for Androgen-Producing Tumors or Pathologic Hyperandrogenism in Women by Use of Total Testosterone Concentrations Measured by Liquid Chromatography-Tandem Mass Spectrometry

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    2018-11-07 jeanqiuqiu
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    2018-11-07 qjddjq
  6. [GetPortalCommentsPageByObjectIdResponse(id=1818976, encodeId=f95518189e643, content=<a href='/topic/show?id=ab0c98e0061' target=_blank style='color:#2F92EE;'>#雄激素过多#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=29, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=98700, encryptionId=ab0c98e0061, topicName=雄激素过多)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=bb0b97, createdName=zhangxingru, createdTime=Wed Feb 27 21:26:00 CST 2019, time=2019-02-27, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1662276, encodeId=07b916622e686, content=<a href='/topic/show?id=6a426545472' target=_blank style='color:#2F92EE;'>#测定#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=25, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=65454, encryptionId=6a426545472, topicName=测定)], attachment=null, authenticateStatus=null, createdAvatar=, createdBy=395f25, createdName=爆笑小医, createdTime=Sun Mar 10 04:26:00 CST 2019, time=2019-03-10, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1544557, encodeId=4048154455e21, content=<a href='/topic/show?id=ac3d6549e75' target=_blank style='color:#2F92EE;'>#浓度#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=36, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=65497, encryptionId=ac3d6549e75, topicName=浓度)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=16b213663040, createdName=12498974m55暂无昵称, createdTime=Wed Nov 07 13:26:00 CST 2018, time=2018-11-07, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1553346, encodeId=0b7315533462b, content=<a href='/topic/show?id=81bd923e559' target=_blank style='color:#2F92EE;'>#质谱#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=27, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=92375, encryptionId=81bd923e559, topicName=质谱)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=96fd14366106, createdName=jeanqiuqiu, createdTime=Wed Nov 07 13:26:00 CST 2018, time=2018-11-07, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=1553605, encodeId=9981155360532, content=<a href='/topic/show?id=839e9e33475' target=_blank style='color:#2F92EE;'>#阈值#</a>, beContent=null, objectType=article, channel=null, level=null, likeNumber=0, replyNumber=0, topicName=null, topicId=null, topicList=[TopicDto(id=97334, encryptionId=839e9e33475, topicName=阈值)], attachment=null, authenticateStatus=null, createdAvatar=null, createdBy=2f4f14387940, createdName=qjddjq, createdTime=Wed Nov 07 13:26:00 CST 2018, time=2018-11-07, status=1, ipAttribution=), GetPortalCommentsPageByObjectIdResponse(id=351668, encodeId=f633351668a3, content=学习了,长知识, beContent=null, objectType=article, channel=null, level=null, likeNumber=49, replyNumber=0, topicName=null, topicId=null, topicList=[], attachment=null, authenticateStatus=null, createdAvatar=https://img.medsci.cn/20220115/46bcf39c32de4aa6b45c5f9d66c8ee77/6cb4a20c55bb4b7691122f47747bfca2.jpg, createdBy=9dad1662329, createdName=1ddf0692m34(暂无匿称), createdTime=Mon Nov 05 22:29:26 CST 2018, time=2018-11-05, status=1, ipAttribution=)]
    2018-11-05 1ddf0692m34(暂无匿称)

    学习了,长知识

    0