One of the dilemmas in checkpoint inhibitor therapy - which can be quite toxic - is predicting who is the best candidate for a strong response.
An NCI Press release highlights a new tool, LORIS, which is an AI-based algorithm and was developed by Ruppin et al. at NCI and Morris et al. at Sloan-Kettering.
See a Linked In blog by Josie Hayes, here.
See the NCI press release here.
See the Nature Cancer article by Chang et al. (June 3) here.
See a summary algorithm online at NCI here.
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Here's the abstract from Nature Cancer (PMID 38831056):
Despite the revolutionary impact of immune checkpoint blockade (ICB) in cancer treatment, accurately predicting patient responses remains challenging. Here, we analyzed a large dataset of 2,881 ICB-treated and 841 non-ICB-treated patients across 18 solid tumor types, encompassing a wide range of clinical, pathologic and genomic features.
We developed a clinical score called LORIS (logistic regression-based immunotherapy-response score) using a six-feature logistic regression model. LORIS outperforms previous signatures in predicting ICB response and identifying responsive patients even with low tumor mutational burden or programmed cell death 1 ligand 1 expression. LORIS consistently predicts patient objective response and short-term and long-term survival across most cancer types. Moreover, LORIS showcases a near-monotonic relationship with ICB response probability and patient survival, enabling precise patient stratification.
As an accurate, interpretable method using a few readily measurable features, LORIS may help improve clinical decision-making in precision medicine to maximize patient benefit. LORIS is available as an online tool at https://loris.ccr.cancer.gov/
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See a July 11 article at JAMA FORUM, "Congress must update FDA regulations for Medical AI," by Scott Gottlieb:
https://jamanetwork.com/journals/jama-health-forum/fullarticle/2821274
July 11, 2024 Congress Must Update FDA Regulations for Medical AI - Scott Gottlieb, MD
JAMA Health Forum. 2024;5(7):e242691. doi:10.1001/jamahealthforum.2024.2691
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