06: ML Identification of Key Features for 90-Day Readmission & LOS in CAR T-Cell Therapy for R/R LBCL

Music City Center 

Chimeric antigen receptor (CAR) T-cell therapy efficacy is limited by toxicities and high cost (median $350k) in relapsed/refractory large B-cell lymphoma (R/R LBCL). This study explores patient features predicting 90-day readmission and hospital length of stay (LOS). A retrospective review of 66 patients with R/R LBCL treated at UC San Diego (2016–2022) included 46 clinical variables (e.g., clinical/visits/readmission parameters & adverse events). The targets were 90-day readmission (29%) and related LOS (mean 18.3 days [SD 19.5]). Data were pre-processed for lasso logistic/linear regression (L1-LG/LR), random forest (RF), extreme gradient boosting (XGB), and support vector machine (SVM) with a 75/25 train/test split, 100 randomly created test sets, GridSearchCV tuning, and 5-fold cross-validation. For 90-day readmission, top predictor was Day-60 Readmission LOS (22%-35% from RF to XGB; L1-LG coefficient 2.5), and highly weighted for predicting the associated LOS (35%-70% across models; L1-LR coefficient 2.9). Large variations (Min F1s: 0.33-0.75) and low R2 (about 0.55) were observed. This study highlights key predictors; larger datasets are needed for clinical generalization.

chimeric antigen receptor (CAR) T-cell

90-day readmission

machine learning

important features 

Section on Statistical Consulting