ReviewAnnals of oncology : official journal of the European Society for Medical Oncology2023
Treatment of evolving cancers will require dynamic decision support.
Review in Annals of oncology : official journal of the European Society for Medical Oncology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 53 papers.
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
53 citing papers in PubMed.
- Evolutionary Antifragile Therapy Is a Treatment Strategy to Suppress Drug Resistance by Exploiting Dose-Response Convexity.Cancer research · 2026Article
- Mathematical Biomarkers of Adaptive Therapy Outcomes in Prostate Cancer.JAMA oncology · 2026Article
- Cancer drug response and resistance: molecular mechanisms and combating strategies.Signal transduction and targeted therapy · 2026Review
- A novel combination therapy for ER+ breast cancer suppresses drug resistance via an evolutionary double-bind.Molecular systems biology · 2026Article
- Article
- A computational framework for optimizing radioiodine therapy protocols in metastatic thyroid cancer.Scientific reports · 2026Article
- Adaptive and sequential cancer therapies emerge from treatment schedule optimization.Research square · 2026Article
- Artificial intelligence and transforming cancer care.Discover oncology · 2026Review
- Pharyngeal Dysphagia in Cancer: Characterizing Functional and Physiological Swallow Targets Across 12 Cancer Types.Dysphagia · 2026Article
- Article
- Metastatic Odyssey: Decoding the Genomic Journey from Primary Colorectal Cancer to Disseminated Disease.Cancers · 2026Review
- Stochastic Evolutionary Control in Heterogeneous Populations.bioRxiv : the preprint server for biology · 2026Article
- Collaborative large language models (LLMs) are all you need for screening in systematic reviews.medRxiv : the preprint server for health sciences · 2026Article
- Can evolutionary therapy be applied in non-small cell lung cancer?Scientific reports · 2026Article
- "Excluded phenotypes" restrict genetic paths toward adaptation in declining populations.Proceedings of the National Academy of Sciences of the United States of America · 2026Article
- Targeting tumor transition windows.Exploration of targeted anti-tumor therapy · 2026Review
- Dynamic Metabolic States in TNBC: Orchestrating Spatiotemporal Adaptation and Therapy.Oncology research · 2026Review
- Cell State Transitions Drive the Evolution of Disease Progression in B-Lymphoblastic Leukemia.Cancer research communications · 2026Article
- Liquid biopsy in breast cancer: current biomarker platforms and clinical applications.Exploration of targeted anti-tumor therapy · 2026Review
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
Abstract
Cancer research has traditionally focused on developing new agents, but an underexplored question is that of the dose and frequency of existing drugs. Based on the modus operandi established in the early days of chemotherapies, most drugs are administered according to predetermined schedules that seek to deliver the maximum tolerated dose and are only adjusted for toxicity. However, we believe that the complex, evolving nature of cancer requires a more dynamic and personalized approach. Chronicling the milestones of the field, we show that the impact of schedule choice crucially depends on processes driving treatment response and failure. As such, cancer heterogeneity and evolution dictate that a one-size-fits-all solution is unlikely-instead, each patient should be mapped to the strategy that best matches their current disease characteristics and treatment objectives (i.e. their 'tumorscape'). To achieve this level of personalization, we need mathematical modeling. In this perspective, we propose a five-step 'Adaptive Dosing Adjusted for Personalized Tumorscapes (ADAPT)' paradigm to integrate data and understanding across scales and derive dynamic and personalized schedules. We conclude with promising examples of model-guided schedule personalization and a call to action to address key outstanding challenges surrounding data collection, model development, and integration.
Indexed as
Identifiers
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.