Detection of Lung Cancer by Plasma Lipids (ELAID)

June 2, 2020 updated by: Jun Wang, Peking University People's Hospital

Detection of Early-stage Lung Cancer Using Machine Learning and Plasma Metabolomics

There are no reliable blood-based tests currently available for early-stage lung cancer diagnosis. We try to establish a highly accurate method for detecting early-stage lung cancer by combining machine learning with untargeted and targeted metabolomics .

Study Overview

Status

Completed

Conditions

Intervention / Treatment

Detailed Description

All plasma lipids were first detected by untargeted metabolomics methods and 9 feature lipids of early-stage lung cancer were selected by support vector machine algorithm. Then, a targeted metabolomics method was developed to detect the 9 lipids quantitatively based on multiple reaction monitoring mode. Finally, a detection model was established based on the 9 lipids.

Study Type

Observational

Enrollment (Actual)

558

Contacts and Locations

This section provides the contact details for those conducting the study, and information on where this study is being conducted.

Study Locations

  • China
    • Beijing
      • Beijing, Beijing, China, 100044
        • Peking University People's Hospital

Participation Criteria

Researchers look for people who fit a certain description, called eligibility criteria. Some examples of these criteria are a person's general health condition or prior treatments.

Eligibility Criteria

Ages Eligible for Study

18 years and older (ADULT, OLDER_ADULT)

Accepts Healthy Volunteers

Yes

Genders Eligible for Study

All

Sampling Method

Non-Probability Sample

Study Population

Patients who with pulmonary nodules or opacity and underwent surgery at the Department of Thoracic Surgery of Peaking University People's Hospital, Jiangsu Cancer Hospital, and Beijing Haidian Hospital were enrolled

Description

Inclusion Criteria:

  1. pulmonary nodules or opacity
  2. plan to receive surgery

Exclusion Criteria:

  1. history of other malignancies
  2. received anti-cancer treatment (chemotherapy, radiotherapy, targeted therapy, etc.) before surgery

Study Plan

This section provides details of the study plan, including how the study is designed and what the study is measuring.

How is the study designed?

Design Details

Cohorts and Interventions

Group / Cohort
Intervention / Treatment
Participants received surgery
Patients who underwent surgery at the Department of Thoracic Surgery of Peaking University People's Hospital, Jiangsu Cancer Hospital, and Beijing Haidian Hospital were enrolled with the following criteria: 1) pathologically confirmed lung cancer; 2) no history of other malignancies; 3) no anti-cancer treatment (chemotherapy, radiotherapy, targeted therapy, etc.) before surgery. Plasma samples were collected before surgery and plasma lipids were detected by mass spectrometry. Pathological diagnosis and clinical characteristics of enrolled participants were retrieved.
Diagnostic test: Plasma lipids
Plasma lipids were detected by an Ultimate 3000 ultra-high-performance liquid chromatography (UHPLC) system coupled with Q-Exactive MS (Thermo Scientific) . Then a detection model was built based on plasma lipids using machine learning algorithm.

What is the study measuring?

Primary Outcome Measures

Outcome Measure
Measure Description
Time Frame
Plasma Lipids
Time Frame: All samples were detected together after participants recruitment and sample collection. All samples were detected within 18 months from sample collection.
A detection model based on 9 lipids were developed, including 3 lysophosphatidylcholines, 5 phosphatidylcholines, and a triglyceride. The 9 lipids were detected by targeted metabolomics by mass spectrometry.
All samples were detected together after participants recruitment and sample collection. All samples were detected within 18 months from sample collection.

Collaborators and Investigators

This is where you will find people and organizations involved with this study.

Sponsor

Peking University People's Hospital

Collaborators

Jiangsu Cancer Institute & Hospital
Peking University Health Science Center
Beijing Haidian Hospital

Study record dates

These dates track the progress of study record and summary results submissions to ClinicalTrials.gov. Study records and reported results are reviewed by the National Library of Medicine (NLM) to make sure they meet specific quality control standards before being posted on the public website.

Study Major Dates

Study Start (ACTUAL)

December 13, 2018

Primary Completion (ACTUAL)

October 31, 2019

Study Completion (ACTUAL)

May 20, 2020

Study Registration Dates

First Submitted

February 13, 2020

First Submitted That Met QC Criteria

February 25, 2020

First Posted (ACTUAL)

February 27, 2020

Study Record Updates

Last Update Posted (ACTUAL)

June 4, 2020

Last Update Submitted That Met QC Criteria

June 2, 2020

Last Verified

June 1, 2020

More Information

Terms related to this study

Keywords

Additional Relevant MeSH Terms

Other Study ID Numbers

  • 2018PHB233-01

Drug and device information, study documents

Studies a U.S. FDA-regulated drug product

No

Studies a U.S. FDA-regulated device product

No

This information was retrieved directly from the website clinicaltrials.gov without any changes. If you have any requests to change, remove or update your study details, please contact register@clinicaltrials.gov. As soon as a change is implemented on clinicaltrials.gov, this will be updated automatically on our website as well.

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