Combined Genomic, Clinical Data Better Predict Outcomes for Pediatric ALL

Compared with clinical data alone, incorporating genomic markers with clinical parameters increased the accuracy of predicting treatment response and survival for pediatric patients with acute lymphoblastic leukemia (ALL), according to a study presented at the Society of Hematologic Oncology 2024 Annual Meeting in Houston, Texas.

The study, presented by Saanie Sulley, PhD, of Boston University, aimed to “identify significant predictors of treatment response and survival and develop a predictive model with high accuracy and generalizability for clinical use in pediatric ALL.”

The retrospective analysis utilized genomic and clinical data from 2,000 patient samples from three cohorts. Age at diagnosis, white cell count, and overall survival were used as clinical parameters, whereas mutation counts, cytogenetic abnormalities, and gene expression profiles were used as genomic data. Specific mutations and gene expression patterns were associated with treatment outcomes in a preliminary analysis.

Predictive modeling to assess patient outcomes revealed an area under the receiver operating characteristic curve (AUC-ROC) of 0.85 for treatment response and a concordance index of 0.80 for survival prediction.

“This study highlights the potential of precision medicine in enhancing prognostic models and personalized treatment strategies,” Dr. Sulley wrote. “Future studies should focus on validating these findings in prospective cohorts and exploring the mechanistic foundations of identified genomic markers.”

Reference

Sulley S. Integrating genomic and clinical parameters to predict outcomes in pediatric patients with acute lymphoblastic leukemia. Abstract #ALL-012. Presented at the Society of Hematologic Oncology 2024 Annual Meeting; September 4-7, 2024; Houston, Texas.