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审核状态: Project audit state: |
通过审核 Successful |
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注册号: Registration number: |
ChiCTR2000036584 |
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最近更新日期: Date of Last Refreshed on: |
2020-09-14 08:11:10 |
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注册时间: Date of Registration: |
2020-08-24 00:00:00 |
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注册号状态: |
预注册 |
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Registration Status: |
Prospective registration |
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注册题目: |
人工智能模型强化患者画像预测甲状腺相关眼病激素疗效的前瞻性队列研究 |
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Public title: |
A prospective cohort study of artificial intelligence model enhanced patient portraits in predicting hormone response in thyroid associated ophthalmopathy |
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注册题目简写: |
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English Acronym: |
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研究课题的正式科学名称: |
人工智能模型强化患者画像预测甲状腺相关眼病激素疗效的前瞻性队列研究 |
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Scientific title: |
A prospective cohort study of artificial intelligence model enhanced patient portraits in predicting hormone response in thyroid associated ophthalmopathy |
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研究课题代号(代码): Study subject ID: |
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在二级注册机构或其它机构的注册号: The registration number of the Partner Registry or other register: |
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申请注册联系人: |
宋雪霏 |
研究负责人: |
宋雪霏 |
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Applicant: |
Xuefei Song |
Study leader: |
Xuefei Song |
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申请注册联系人电话: Applicant telephone: |
+86 18516329785 |
研究负责人电话: Study leader's telephone: |
+86 18516329785 |
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申请注册联系人传真 : Applicant Fax: |
研究负责人传真: Study leader's fax: |
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申请注册联系人电子邮件: Applicant E-mail: |
songxuefei@shsmu.edu.cn |
研究负责人电子邮件: Study leader's E-mail: |
songxuefei@shsmu.edu.cn |
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申请单位网址(自愿提供): Applicant website(voluntary supply): |
研究负责人网址(自愿提供): Study leader's website(voluntary supply): |
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申请注册联系人通讯地址: |
中国上海市黄浦区制造局路639号 |
研究负责人通讯地址: |
中国上海市黄浦区制造局路639号 |
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Applicant address: |
639 Zhizaoju Road, Huangpu Distinct, Shanghai, China |
Study leader's address: |
639 Zhizaoju Road, Huangpu Distinct, Shanghai, China |
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申请注册联系人邮政编码: Applicant postcode: |
研究负责人邮政编码: Study leader's postcode: |
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申请人所在单位: |
上海交通大学医学院附属第九人民医院 |
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Applicant's institution: |
The Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine |
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研究负责人所在单位: |
上海交通大学医学院附属第九人民医院 |
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Affiliation of the Leader: |
The Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine |
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是否获伦理委员会批准: |
是/Yes |
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Approved by ethic committee: |
Yes |
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伦理委员会批件文号: Approved No. of ethic committee: |
SH9H-2020-T211-1 |
伦理委员会批件附件: Approved file of Ethical Committee: |
查看附件View |
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批准本研究的伦理委员会名称: |
上海交通大学医学院附属第九人民医院伦理委员会 |
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Name of the ethic committee: |
Ethic Committee of Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine |
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伦理委员会批准日期: Date of approved by ethic committee: |
2020-08-20 00:00:00 |
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伦理委员会联系人: |
甄红 |
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Contact Name of the ethic committee: |
Hong Zhen |
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伦理委员会联系地址: |
中国上海市黄浦区制造局路639号 |
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Contact Address of the ethic committee: |
639 Zhizaoju Road, Huangpu Distinct, Shanghai, China |
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伦理委员会联系人电话: Contact phone of the ethic committee: |
伦理委员会联系人邮箱: Contact email of the ethic committee: |
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研究实施负责(组长)单位: |
上海交通大学医学院附属第九人民医院 |
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Primary sponsor: |
The Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine |
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研究实施负责(组长)单位地址: |
中国上海市黄浦区制造局路639号 |
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Primary sponsor's address: |
639 Zhizaoju Road, Huangpu Distinct, Shanghai, China |
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试验主办单位(项目批准或申办者): Secondary sponsor: |
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经费或物资来源: |
上海申康医院发展中心 |
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Source(s) of funding: |
Shanghai Hospital Development Center |
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Target disease: |
thyroid associated ophthalmopathy |
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Target disease code: |
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研究类型: |
诊断试验 |
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Study type: |
Diagnostic test |
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研究所处阶段: |
其它 | ||||||||||||||||||||||
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Study phase: |
N/A |
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研究设计: |
队列研究 |
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Study design: |
Cohort study |
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研究目的: |
评价人工智能(AI)模型强化患者画像对TAO激素疗效的预测价值,建立智能助手协助医生在治疗前预测患者的激素疗效从而优化治疗方案的选择,改善预后。 |
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Objectives of Study: |
To evaluate the predictive value of artificial intelligence (AI) model in strengthening patient portraits in predicting the efficacy of Tao hormone therapy, and to establish an intelligent assistant to help doctors predict the hormone efficacy of patients before treatment, so as to optimize the choice of treatment options and improve the prognosis. |
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药物成份或治疗方案详述: |
本研究设计为前瞻性队列研究,纳入拟接受激素冲击治疗的中重度活动期TAO患者。基于40%激素有效率,考虑纳入10个变量的模型稳定性,根据EPV原则预期纳入278例患者。治疗前采用人工智能AI模型(本课题组原创建立,专利授权)进行影像学、容貌和面部结构改变等4个维度进行判别,以丰富患者画像维度,同时结合传统临床指标一并纳入预测模型以实现更高水平的预测模型建立。随访观察并评价TAO激素治疗疗效,采用多因素Logistic回归分析建立激素疗效预测模型,实现治疗前筛选治疗无效患者。通过纳入新病人实施以所建预测模型敏感度、特异度为目标的诊断试验,验证模型是否能在治疗前筛选出治疗无效的患者。 |
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Description for medicine or protocol of treatment in detail: |
This study was designed as a prospective cohort study involving moderate to severe active TAO patients who were scheduled to receive hormone therapy. Based on the 40% hormone response rate, considering the stability of the model with 10 variables, 278 patients were expected to be included according to the EPV principle. Before treatment, the artificial intelligence AI model (originally established by our research group and authorized by patent) was used to distinguish the four dimensions of imaging, appearance and facial structure changes, so as to enrich the dimensions of patients' portraits. At the same time, the traditional clinical indicators were incorporated into the prediction model to achieve a higher level of prediction model establishment. The curative effect of Tao hormone therapy was observed and evaluated. Multivariate logistic regression analysis was used to establish the prediction model of hormone efficacy, so as to screen the ineffective patients before treatment. Through the inclusion of new patients, the diagnostic test aimed at the sensitivity and specificity of the established prediction model was carried out to verify whether the model can screen out patients who are ineffective before treatment. |
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纳入标准: |
(1)18-60岁,男女不限; |
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Inclusion criteria |
(1) 18-60 years old, male or female; |
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排除标准: |
(1)严重心、肝、肾功能不全;糖尿病,高血压未控制、精神类疾病患者;SLE、RA等自身免疫性疾病;结核、HIV感染或AIDS患者;糖皮质激素过敏者;孕妇或处于哺乳期者;入组前1个月内接种肝炎疫苗者; |
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Exclusion criteria: |
(1) Severe heart, liver and kidney dysfunction; diabetes, uncontrolled hypertension, mental illness; SLE, RA and other autoimmune diseases; tuberculosis, HIV infection or AIDS patients; glucocorticoid allergy; pregnant women or breast-feeding; hepatitis vaccination within one month before enrollment; |
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研究实施时间: Study execute time: |
从 From 2020-10-01 00:00:00至 To 2022-09-30 00:00:00 |
征募观察对象时间: Recruiting time: |
从From 2020-10-01 00:00:00 至 To 2022-03-31 00:00:00 |
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诊断试验: Diagnostic Tests: |
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研究实施地点: Countries of recruitment and research settings: |
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测量指标: Outcomes: |
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采集人体标本:
Collecting sample(s)
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征募研究对象情况: Recruiting status: |
尚未开始 Not yet recruiting |
年龄范围: Participant age: |
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性别: |
男女均可 |
Gender: |
Both |
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随机方法(请说明由何人用什么方法产生随机序列): |
无 |
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Randomization Procedure (please state who generates the random number sequence and by what method): |
NA |
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是否公开试验完成后的统计结果: Calculated Results after the Study Completed public access: |
公开/Public |
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盲法: |
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Blinding: |
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试验完成后的统计结果(上传文件): |
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Calculated Results after
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是否共享原始数据: IPD sharing |
Yes |
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共享原始数据的方式(说明:请填入公开原始数据日期和方式,如采用网络平台,需填该网络平台名称和网址): |
以学术论文方式公开 |
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The way of sharing IPD”(include metadata and protocol, If use web-based public database, please provide the url): |
Share in the form of academic papers |
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数据采集和管理(说明:数据采集和管理由两部分组成,一为病例记录表(Case Record Form, CRF),二为电子采集和管理系统(Electronic Data Capture, EDC),如ResMan即为一种基于互联网的EDC: |
EDC |
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Data collection and Management (A standard data collection and management system include a CRF and an electronic data capture: |
EDC |
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数据与安全监察委员会: Data and Safety Monitoring Committee: |
有/Yes |