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Multi-dimensional Signatures for Precisely Predicting the Response and Prognosis of Lung Cancer Patients (Pred-lung)

H

Huazhong University of Science and Technology

Status

Enrolling

Conditions

Prognosis
Response

Treatments

Other: real world treatment by doctors

Study type

Observational

Funder types

Other

Identifiers

NCT04980352
2019-1-12 V1.1

Details and patient eligibility

About

This study aims to determine the clinical effectiveness of multi-dimensional signatures in predicting response and prognosis of lung cancer patients. The study is a multi-center perspective research of treatment planning for patients with lung cancer. To characterize clinical effectiveness, the progression-free survival (PFS) and overall survival (OS) impacts of multi-dimensional signatures will be estimated.

Full description

Multi-dimensional signatures, including NGS-based genotyping, and other essential detections such as immunohistochemistry (IHC), provides an opportunity to improve outcomes for patients by tailoring treatments to each individual's genomic profile. This is a multi-center single arm research study integrating multi-dimensional signatures into clinical decision-making for patients with lung cancer. The clinical effectiveness of multi-dimensional signatures is unknown in the real-world of clinics. To identify a counterfactual for Pred-lung approach, matching methods combined with administrative healthcare data will be used. The survival impacts of Pred-lung approach compared to usual care in matched controls will then be estimated.

Enrollment

200 estimated patients

Sex

All

Ages

18+ years old

Volunteers

No Healthy Volunteers

Inclusion criteria

  • Patients with locally-advanced or metastasis lung cancer
  • Life expectancy > 3 months

Exclusion criteria

  • Age at diagnosis <18
  • refuse to enroll

Trial contacts and locations

1

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Central trial contact

Yuan Li, Dr.

Data sourced from clinicaltrials.gov

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