ReviewNature reviews. Clinical oncology2019
The beginning of the end for conventional RECIST - novel therapies require novel imaging approaches.
Review in Nature reviews. Clinical oncology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 63 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
63 citing papers in PubMed, 1 synthesis or guideline pooled it, 130 citations in OpenAlex.
- Integrated imaging and molecular analysis to decipher tumor microenvironment in the era of immunotherapy.Seminars in cancer biology · 2022Pooled it
- RECIST and iRECIST criteria for the evaluation of nivolumab plus ipilimumab in patients with microsatellite instability-high/mismatch repair-deficient metastatic colorectal cancer: the GERCOR NIPICOL phase II study.Journal for immunotherapy of cancer · 2020Trial
- Trabectedin plus CD13-targeted tissue factor tTF-NGR against advanced relapsed or refractory soft tissue sarcoma: translational data, clinical safety and efficacy.Scientific reports · 2026Article
- Progress and challenges of artificial intelligence in lung cancer clinical translation.NPJ precision oncology · 2025Review
- Imaging NRF2 activation in non-small cell lung cancer with positron emission tomography.Nature communications · 2024Article
- Innovative optical imaging strategies for monitoring immunotherapy in the tumor microenvironments.Cancer medicine · 2024Review
- Dendritic cell vaccination combined with irreversible electroporation for treating pancreatic cancer-a narrative review.Annals of translational medicine · 2024Review
- Multiparametric MRI for characterization of the tumour microenvironment.Nature reviews. Clinical oncology · 2024Review
- Radiomics-Based Prediction Model for Outcome of Radioembolization in Metastatic Colorectal Cancer.Cardiovascular and interventional radiology · 2024Article
- MRI radiomics to monitor therapeutic outcome of sorafenib plus IHA transcatheter NK cell combination therapy in hepatocellular carcinoma.Journal of translational medicine · 2024Article
- Biomarker-driven molecular imaging probes in radiotherapy.Theranostics · 2024Review
- The role of clinical imaging in oncology drug development: progress and new challenges.The British journal of radiology · 2023Review
- Assessment of the sensitivity ofNMR in biomedicine · 2023Article
- Multiparametric chemical exchange saturation transfer MRI detects metabolic changes in breast cancer following immunotherapy.Journal of translational medicine · 2023Article
- First-in-human CLDN18.2 functional diagnostic pet imaging of digestive system neoplasms enables whole-body target mapping and lesion detection.European journal of nuclear medicine and molecular imaging · 2023Article
- Vascular response patterns to targeted therapies in murine breast cancer models with divergent degrees of malignancy.Breast cancer research : BCR · 2023Article
- Review
- Profiling specific cell populations within the inflammatory tumor microenvironment by oscillating-gradient diffusion-weighted MRI.Journal for immunotherapy of cancer · 2023Article
- Radiomics-guided checkpoint inhibitor immunotherapy for precision medicine in cancer: A review for clinicians.Frontiers in immunology · 2023Review
- Immuno-PET Monitoring of Lymphocytes Using the CD8-Specific Antibody REGN5054.Cancer immunology research · 2022Article
3 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Owing to improvements in our understanding of the biological principles of tumour initiation and progression, a wide variety of novel targeted therapies have been developed. Developments in biomedical imaging, however, have not kept pace with these improvements and are still mainly designed to determine lesion size alone, which is reflected in the Response Evaluation Criteria in Solid Tumors (RECIST). Imaging approaches currently used for the evaluation of treatment responses in patients with solid tumours, therefore, often fail to detect successful responses to novel targeted agents and might even falsely suggest disease progression, a scenario known as pseudoprogression. The ability to differentiate between responders and nonresponders early in the course of treatment is essential to allowing the early adjustment of treatment regimens. Various imaging approaches targeting a single dedicated tumour feature, as described in the hallmarks of cancer, have been successful in preclinical investigations, and some have been evaluated in pilot clinical trials. However, these approaches have largely not been implemented in clinical practice. In this Review, we describe current biomedical imaging approaches used to monitor responses to treatment in patients receiving novel targeted therapies, including a summary of the most promising future approaches and how these might improve clinical practice.
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What OpenQuestion holds
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.