MONDAY, June 10, 2024 (HealthDay News) -- For patients with cancer, a novel clinical score using a six-feature regression model can predict immune checkpoint blockade (ICB) response probability and patient survival, according to a study published online June 3 in Nature Cancer.
Tian-Gen Chang, Ph.D., from the National Institutes of Health in Bethesda, Maryland, and colleagues analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types. A clinical logistic regression-based immunotherapy-response score (LORIS) was developed using a six-feature logistic regression model.
The researchers found that LORIS outperformed previous signatures for predicting ICB response and identifying responsive patients, including those with low tumor mutational burden and with programmed cell death 1 ligand 1 expression. Patient objective response and short- and long-term survival were consistently predicted by LORIS across most cancer types. A near-monotonic relationship with ICB response probability and patient survival was seen with LORIS, enabling precise patient stratification.
"As our understanding of tumor immunology and the availability of comprehensive data in larger cohorts continue to improve, we expect to see the development of even more accurate models for personalized precision therapy, ultimately reducing cancer mortality," the authors write.
One author disclosed ties to MedAware, Metabomed, and Pangea Biomed.
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