ArticleNature cancer2024
LORIS robustly predicts patient outcomes with immune checkpoint blockade therapy using common clinical, pathologic and genomic features.
Article in Nature cancer, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 82 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
82 citing papers in PubMed.
- Artificial intelligence in immune checkpoint inhibitor research: A bibliometric analysis of the landscape.Human vaccines & immunotherapeutics · 2026Article
- Serum albumin is associated with immune-related hypothyroidism and treatment continuity in non-small cell lung cancer.International journal of clinical oncology · 2026Article
- Article
- Utilizing Machine Learning to Identify Multimodal Signatures for Patients Who Would Benefit from the Addition of Tremelimumab to Durvalumab and Chemotherapy (TRIDENT).Clinical cancer research : an official journal of the American Association for Cancer Research · 2026Observational
- A multimodal murmuration for immunotherapy.Nature medicine · 2026Article
- Clinical usability of an explainable AI decision support tool and evaluation of multimodal models in NSCLC.Nature medicine · 2026Observational
- Integrating Immunotherapy Into Head and Neck Surgery: Bridging Tumor Biology to Perioperative Decision-Making, a Review.Head & neck · 2026Review
- Clinical attribute-based risk matrix for prognostication in immunotherapy-treated non-small cell lung cancer.Nature communications · 2026Article
- Interpretable deep learning model of circulating genomics for quantitative survival prediction in advanced non-small cell lung cancer.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2026Article
- Generalizable AI predicts immunotherapy outcomes across cancers and treatments.Nature medicine · 2026Article
- Closing the Translational Gap: Closed-Loop AI Discovery Frameworks for Experimental Validation and Clinical Implementation in Cancer Therapeutics.Cancer medicine · 2026Review
- IDH1-R132H enhances oncolytic HSV-1 therapy by facilitating viral entry and immune activation in glioma.Nature communications · 2026Article
- Leveraging Artificial Intelligence and Large Language Models for Cancer Immunotherapy.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Artificial intelligence and transforming cancer care.Discover oncology · 2026Review
- CLEC2B-KLRB1 axis acts as an immune checkpoint, governing the exhaustion of CD8Journal for immunotherapy of cancer · 2026Article
- Understanding immune checkpoint inhibitor efficacy through spatial decoding of the lung cancer tumor immune microenvironment.The Journal of clinical investigation · 2026Article
- Immune Checkpoint Inhibitors and Immunomodulators for Cancer Immunotherapy: Insights Into Resistance and Therapeutic Strategies.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2026Review
- Predictors of sensitivity to immune therapies in classic Hodgkin lymphoma.Blood neoplasia · 2026Review
- Development and external validation of a machine learning model for predicting chronic critical illness in ICU patients with acute pancreatitis.BMC medical informatics and decision making · 2026Article
- Clinician-deployable deep hypergraph model integrating clinical and CT radiomics predicts immunotherapy outcomes in NSCLC.PLOS digital health · 2026Article
22 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
10 authors.
Funding
Abstract
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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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.