NCT04287712

Detection of Lung Cancer by Plasma Lipids

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

• Status: Completed
• Phase: —
• Study type: Observational
• Enrollment: 558 (actual)
• Sponsor: Peking University People's Hospital · Academic / Other
• Sex: All
• Age: 18 Years
• Healthy volunteers: Accepted

Summary

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 .

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.

Conditions

• Early-Stage Lung Cancer

Interventions

Type	Name	Description
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.

Timeline

• Start date: 2018-12-13
• Primary completion: 2019-10-31
• Completion: 2020-05-20
• First posted: 2020-02-27
• Last updated: 2020-06-04

Locations

1 site across 1 country: China