ArticleNature medicine2025
Prediction of checkpoint inhibitor immunotherapy efficacy for cancer using routine blood tests and clinical data.
Article in Nature medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT07265661 (Surgical Timing After Preoperative Hypofractionated Radiotherapy for Patients With Primary Localized Soft Tissue Sarcoma of the Extremity and Trunk), which is not on this map. Cited by 100 papers, 1 of them a synthesis that pooled it.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Surgical Timing After Preoperative Hypofractionated Radiotherapy for Patients With Primary Localized Soft Tissue Sarcoma of the Extremity and Trunk: a Randomized Phase 2 Clinical Trial
Who cites it
100 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Precision Medicine and Artificial Intelligence in Next-Generation Cancer Surgery: A Comprehensive Analysis of Clinical Applications, Therapeutic Outcomes, and Implementation Strategies.Asian Pacific journal of cancer prevention : APJCP · 2025Pooled it
- Efficacy and safety of fruquintinib combined with albumin-bound paclitaxel as second-line therapy for advanced gastric cancer following failure of PD-1 inhibitor-containing treatment (TACTIC GC-01): A phase II single-arm study.International journal of cancer · 2026Trial
- Predicting PD-L1 + CD8 - status in non-small cell lung cancer tissue from clinical indicators using machine learning.Chinese medical journal · 2026Article
- 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
- The immunology of human breast cancer.Nature reviews. Immunology · 2026Review
- Exploratory Comparison of Meld, Meld-Na, and Meld 3.0 Scores for Prognostic Assessment at Diagnosis in Hepatocellular Carcinoma Using Machine Learning Approaches.Digestive diseases and sciences · 2026Article
- Clinical Applications and Evidence Landscape of Thymosin Alpha 1 as an Immunomodulatory Adjunct in Cancer Care: A Scoping Review.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Population-Scale Precision Safety in Oncology Reveals Clinical and Genetic Determinants of Systemic Therapy Toxicity.medRxiv : the preprint server for health sciences · 2026Article
- Clinical usability of an explainable AI decision support tool and evaluation of multimodal models in NSCLC.Nature medicine · 2026Observational
- A multimodal murmuration for immunotherapy.Nature medicine · 2026Article
- A Multidisciplinary Team-Based Large Language Model Framework for Predicting Postoperative Neurological Complications in Acute Type A Aortic Dissection: Model Development and Validation Study.Journal of medical Internet research · 2026Article
- Generalizable AI predicts immunotherapy outcomes across cancers and treatments.Nature medicine · 2026Article
- Disparate privacy risks from medical AI.Nature · 2026Article
- tRNA-derived small RNAs in tumor microenvironment remodeling: From mechanistic insights to therapeutic perspectives.Oncogene · 2026Review
- Development and validation of a machine learning model for predicting objective response to PD-1 inhibitors in lung cancer patients.Translational lung cancer research · 2026Article
- Hypoxia shapes both therapeutic response and resistance in metastatic clear cell renal cell carcinoma.Cancer cell · 2026Article
- Pan-cancer prioritization of CCDC69 reveals an immune-enriched and therapeutically sensitive breast cancer phenotype.Discover oncology · 2026Article
- Multimodal blood based proteomic profiling reveals insights into mechanisms of immunotherapy resistance.Nature communications · 2026Article
- Blood-based kinase activity profiling to predict response to immune checkpoint inhibitors in patients with advanced stage NSCLC: the prospective IOpener study.Journal for immunotherapy of cancer · 2026Article
- Peripheral blood IFN-γ-producing T-cell subsets and soluble IL-2 receptor as independent prognostic biomarkers in NSCLC treated with immune checkpoint inhibitor-based therapy.Discover oncology · 2026Article
40 more citing papers are in PubMed but not listed here.
Corrections and comments
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Authors and funding
37 authors.
Funding
Abstract
Predicting whether a patient with cancer will benefit from immune checkpoint inhibitors (ICIs) without resorting to advanced genomic or immunologic assays is an important clinical need. To address this, we developed and evaluated SCORPIO, a machine learning system that utilizes routine blood tests (complete blood count and comprehensive metabolic profile) alongside clinical characteristics from 9,745 ICI-treated patients across 21 cancer types. SCORPIO was trained on data from 1,628 patients across 17 cancer types from Memorial Sloan Kettering Cancer Center. In two internal test sets comprising 2,511 patients across 19 cancer types, SCORPIO achieved median time-dependent area under the receiver operating characteristic curve (AUC(t)) values of 0.763 and 0.759 for predicting overall survival at 6, 12, 18, 24 and 30 months, outperforming tumor mutational burden (TMB), which showed median AUC(t) values of 0.503 and 0.543. Additionally, SCORPIO demonstrated superior predictive performance for predicting clinical benefit (tumor response or prolonged stability), with AUC values of 0.714 and 0.641, compared to TMB (AUC = 0.546 and 0.573). External validation was performed using 10 global phase 3 trials (4,447 patients across 6 cancer types) and a real-world cohort from the Mount Sinai Health System (1,159 patients across 18 cancer types). In these external cohorts, SCORPIO maintained robust performance in predicting ICI outcomes, surpassing programmed death-ligand 1 immunostaining. These findings underscore SCORPIO's reliability and adaptability, highlighting its potential to predict patient outcomes with ICI therapy across diverse cancer types and healthcare settings.
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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.