Lung cancer risk prediction models based on pulmonary nodules: A systematic review.

ABSTRACT:

Background

Screening with low-dose computed tomography (LDCT) is an efficient way to detect lung cancer at an earlier stage, but has a high false-positive rate. Several pulmonary nodules risk prediction models were developed to solve the problem. This systematic review aimed to compare the quality and accuracy of these models.

Methods

The keywords "lung cancer," "lung neoplasms," "lung tumor," "risk," "lung carcinoma" "risk," "predict," "assessment," and "nodule" were used to identify relevant articles published before February 2021. All studies with multivariate risk models developed and validated on human LDCT data were included. Informal publications or studies with incomplete procedures were excluded. Information was extracted from each publication and assessed.

Resul

SUBMITTER: Wu Z 

PROVIDER: S-EPMC8888150 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature