Post-imaging pulmonary nodule mathematical prediction models: are they clinically relevant?

ABSTRACT:

Objectives

Post-imaging mathematical prediction models (MPMs) provide guidance for the management of solid pulmonary nodules by providing a lung cancer risk score from demographic and radiologists-indicated imaging characteristics. We hypothesized calibrating the MPM risk score threshold to a local study cohort would result in improved performance over the original recommended MPM thresholds. We compared the pre- and post-calibration performance of four MPM models and determined if improvement in MPM prediction occurs as nodules are imaged longitudinally.

Materials and methods

A common cohort of 317 individuals with computed tomography-detected, solid nodules (80 malignant, 237 benign) were used to evaluate the MPM performance. We created a web-based application for this stu

SUBMITTER: Uthoff J 

PROVIDER: S-EPMC6717521 | biostudies-literature | 2019 Oct

REPOSITORIES: biostudies-literature