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临床试验/NCT03967652
NCT03967652Unknown不适用

Diagnosing Cancers From Healthy From Human Exhaled Breath With Na-nose

Anhui Medical University0 个研究点目标入组 10,000 人开始时间: 2019年7月1日最近更新:
适应症

试验速览

阶段
不适用
发起方
入组人数
10,000
主要终点
Build predictive diagnosis database

研究概览

简要总结

Early diagnoses of malignant tumors are pivotal for improving their prognoses. The Exhaled Breath is made up of oxygen, carbon dioxide, nitrogen, water, inert gases and volatile organic compounds (VOCs). Theoretically, the concentration of VOCs in exhalation produced by metabolism in human body is only about nmol/L-pmol/L, which can significantly increase under certain pathological conditions. A series of studies of VOCs diagnosing solid tumors the investigators had been conducted in the past decade. It was found that VOCs in exhaled breath can not only distinguish different types of tumors, but also can make a clear distinction between different stages. Our long-term collaborator, Professor Hossam Haick (Israel Institute of Technology) has developed a nano sensor array, so called Na-nose, which can detect VOCs of the exhaled breath by binding gases to specific chemiresistors coated with gold nanomaterials. The Na-nose has the advantages of low cost, easy to use, good reproducibility and real-time detection for large scale clinical application. This study was to use large clinical samples to validate the diagnostic efficacy of the newly developed Nano-nose( Sniffphone and Breath Screener) for malignant tumors .

详细描述

Israel Institute of Technology provides two type of Na-nose. One is Breath Screener used for large-scale sampling and feature VOCs extraction to establish database. The other is called Sniff Phone aim at clinical real-time VOCs detection assisted by software. About 10,000 patients will participate in the subject of Breath Screener in batches. First, 7000 patients will have a definitive diagnosis and exhaled breath collected. Feature VOCs of specific tumors will be extracted from these samples and employed to build predictive model by using discriminant factor analysis (DFA). After the predictive model had been completed, 3000 definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model. With the assistance of Breath Screener clinical database and software services, Sniff Phone is more suitable for clinical real-time detection for its small and convenient design characteristics. At last, Breath Screener and Sniff Phone will continue enriching databases and improve diagnosis efficacy in their clinical applications.

研究设计

研究类型
Observational
观察模型
Other
时间视角
Prospective

入排标准

年龄范围
18 Years 至 75 Years(Adult, Older Adult)
性别
All
接受健康志愿者

入选标准

  • 18-75 years
  • Cancer/benign disease having been diagnosed by pathology
  • ECOG < 2

排除标准

  • Concomitant malignancies other than one malignant tumor
  • Diabetes, Fatty liver
  • Autoimmune disease
  • Ventilation and transaired function obstacle

结局指标

主要结局

Build predictive diagnosis database

时间窗: From July 01,2019 to December 31,2021

First, feature VOCs of specific tumors will be extracted from part of collected samples and employed to build predictive model. After the predictive model had been completed, number of definitively diagnosed patients will participate in validating the specificity and sensitivity of the prediction model.

次要结局

  • Associated feature exhaled breath with differentially expressed genes(From Juan 01,2022 to December 31,2022)

研究者

发起方
Anhui Medical University
申办方类型
Other
责任方
Principal Investigator
主要研究者

Hu Liu

Professor

Anhui Provincial Hospital

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Cancer Diagnoses From Exhaled Breath With Na-nose | 临床试验