ArticleCells2023
A Mathematical Model for Predicting Patient Responses to Combined Radiotherapy with CTLA-4 Immune Checkpoint Inhibitors.
Article in Cells, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT01008358 (Phase II Trial of Anti-CTLA-4 Human Monoclonal Antibody CP-675,206 in Patients With Advanced Hepatocellular Carcinoma), which is not on this map. Cited by 8 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.
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.
Phase II Trial of Anti-CTLA-4 Human Monoclonal Antibody CP-675,206 in Patients With Advanced Hepatocellular Carcinoma
Who cites it
8 citing papers in PubMed, 13 citations in OpenAlex.
- Timing matters: how mechanism-guided sequencing shapes the efficacy of radiotherapy-immunotherapy combinations : A systematic review.Strahlentherapie und Onkologie : Organ der Deutschen Rontgengesellschaft ... [et al] · 2026Review
- Model-Based Patient Selection and Dosing Strategies for HRAS and PIK3CA Dysregulated HNSCC: A QSP Model for Alpelisib and Tipifarnib Combination.Clinical pharmacology and therapeutics · 2026Article
- Review
- Mathematical modeling in radiotherapy for cancer: a comprehensive narrative review.Radiation oncology (London, England) · 2025Review
- Breakthroughs in immune checkpoint therapy: overcoming NSCLC immune checkpoint therapy resistance with novel techniques.Frontiers in immunology · 2025Review
- Mechanistic in silico explorations of the immunogenic and synergistic effects of radiotherapy and immunotherapy: a critical review.Physical and engineering sciences in medicine · 2024Review
- Optimized patient-specific immune checkpoint inhibitor therapies for cancer treatment based on tumor immune microenvironment modeling.Briefings in bioinformatics · 2024Article
- Radiobiological Modeling with Monte Carlo Tools - Simulating Cellular Responses to Ionizing Radiation.Technology in cancer research & treatmentReview
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The purpose of this study was to develop a cell-cell interaction model that could predict a tumor's response to radiotherapy (RT) combined with CTLA-4 immune checkpoint inhibition (ICI) in patients with hepatocellular carcinoma (HCC). The previously developed model was extended by adding a new term representing tremelimumab, an inhibitor of CTLA-4. The distribution of the new immune activation term was derived from the results of a clinical trial for tremelimumab monotherapy (NCT01008358). The proposed model successfully reproduced longitudinal tumor diameter changes in HCC patients treated with tremelimumab (complete response = 0%, partial response = 17.6%, stable disease = 58.8%, and progressive disease = 23.6%). For the non-irradiated tumor control group, adding ICI to RT increased the clinical benefit rate from 8% to 32%. The simulation predicts that it is beneficial to start CTLA-4 blockade before RT in terms of treatment sequences. We developed a mathematical model that can predict the response of patients to the combined CTLA-4 blockade with radiation therapy. We anticipate that the developed model will be helpful for designing clinical trials with the ultimate aim of maximizing the efficacy of ICI-RT combination therapy.
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Registered trials
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.