Time-Series Clustering Captures Patterns of Early Immune Effector Cell-Associated Hematotoxicity That Are Predictable Using Tree-Based Models.

ABSTRACT:

Purpose

Immune effector cell-associated hematotoxicity (ICAHT) is a major cause of nonrelapse mortality after chimeric antigen receptor (CAR) T-cell therapy. We hypothesized that unsupervised time-series clustering could better identify archetypal patterns of early hematotoxicity compared to the early ICAHT (eICAHT) grading system.

Methods

We applied unsupervised k-means time-series clustering based on Euclidean distances to longitudinal absolute neutrophil count (ANC) data from days +0 through +30 post-CAR T-cell infusion in 691 patients treated at our center (training set: n = 483, 70%; test set: n = 208, 30%).

Results

Within our training set, we identified an optimal cluster solution based on four ANC recovery clusters, which were labeled as very good, good, poor,

SUBMITTER: Liang EC 

PROVIDER: S-EPMC12810859 | biostudies-literature | 2026 Jan

REPOSITORIES: biostudies-literature