2023 World Conference on Lung Cancer (Posters)-EP06.01. A Circulating Tumor Cell-based Artificial Neural Network of Patients with Advanced Non-Small Cell Lung Cancer

EP06.01. A Circulating Tumor Cell-based Artificial Neural Network of Patients with Advanced Non-Small Cell Lung Cancer - PDF(Abstract)

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This study presents a predictive model for assessing the risk of non-small cell lung cancer (NSCLC) using an artificial neural network (ANN) constructed from circulating tumor cells (CTCs). The researchers utilized a microfluidic device to isolate CTCs from individuals with NSCLC and analyzed their correlation with clinical characteristics, treatment efficacy, and patient prognosis. They classified subjects into high and low CTC groups and found that individuals in the high-CTC and cluster-positive group had a poorer progression-free survival. The researchers also analyzed CTC counts collected at multiple time points and found that patients with progression had higher CTCs and CTC clusters. They constructed an ANN model using the CTC and CTC cluster counts, which showed superior discriminating power compared to the classical Cox model. The risk stratification was based on a nomogram constructed by the ANN model, which exhibited excellent predictive ability. Overall, the ANN model based on CTCs can effectively conduct risk stratification, predict tumor progression, and provide a basis for the diagnosis and tailored treatment of NSCLC.

Asset Subtitle

Xuyu Gu

Meta Tag

Speaker Xuyu Gu

Topic Pathology & Biomarkers: Artificial Intelligence in Pathology

Keywords

predictive model

non-small cell lung cancer

artificial neural network

circulating tumor cells

microfluidic device

progression-free survival

CTC counts

CTC clusters

risk stratification

tumor progression