ReviewNature reviews. Clinical oncology2014
Biomarker enrichment strategies: matching trial design to biomarker credentials.
Review in Nature reviews. Clinical oncology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 83 papers, 2 of them syntheses 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
83 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Association of maternal blood metabolomics and gestational diabetes mellitus risk: a systematic review and meta-analysis.Reviews in endocrine & metabolic disorders · 2025Pooled it
- Systematic review of combinations of targeted or immunotherapy in advanced solid tumors.Journal for immunotherapy of cancer · 2021Pooled it
- Mortality Benefit of Recombinant Human Interleukin-1 Receptor Antagonist for Sepsis Varies by Initial Interleukin-1 Receptor Antagonist Plasma Concentration.Critical care medicine · 2018Trial
- Molecular profiling and targeted therapy for advanced thoracic malignancies: a biomarker-derived, multiarm, multihistology phase II basket trial.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2015Trial
- Operationalizing Precision Medicine in Drug Development: Predictive Biomarkers, Companion Diagnostics, and Regulatory Pathways.Clinical pharmacology and therapeutics · 2026Review
- Protein Quantification Platforms For Use In Critical Care Precision Medicine Trials: A Scoping Review.Critical care explorations · 2026Article
- Multi-omics-driven precision medicine.iMeta · 2026Review
- Abundances but not concentrations of circulating unsaturated fatty acids are associated with incident psoriatic diseases: Evidence from cohort and Mendelian randomization studies.JID innovations : skin science from molecules to population health · 2026Article
- Review
- Moving Toward Objective Diagnosis in Fibromyalgia: Emerging Biomarkers and Digital Phenotyping Tools.Biomedicines · 2026Review
- Evidence-based personalised medicine in critical care: a framework for quantifying and applying individualised treatment effects in patients who are critically ill.The Lancet. Respiratory medicine · 2025Review
- Interpreting results from biomarker-guided clinical trials: avoiding "negative" or "failed" terminology.BMC medicine · 2025Article
- Artificial intelligence in oncology: ensuring safe and effective integration of language models in clinical practice.The Lancet regional health. Europe · 2024Review
- Exploring the clinical implications and applications of exosomal miRNAs in gliomas: a comprehensive study.Cancer cell international · 2024Review
- From ICU Syndromes to ICU Subphenotypes: Consensus Report and Recommendations for Developing Precision Medicine in the ICU.American journal of respiratory and critical care medicine · 2024Review
- Isotonic design for single-arm biomarker stratified trials.Statistical methods in medical research · 2024Article
- Tumor-neutrophil cross talk orchestrates the tumor microenvironment to determine the bladder cancer progression.Proceedings of the National Academy of Sciences of the United States of America · 2024Article
- Efficiency of Biomarker-Driven Clinical Trial Designs.Journal of clinical oncology : official journal of the American Society of Clinical Oncology · 2024Article
- Efficient testing of the biomarker positive and negative subgroups in a biomarker-stratified trial.Biometrics · 2024Article
- The potential of miRNA-based approaches in glioblastoma: An update in current advances and future perspectives.Current research in pharmacology and drug discovery · 2024Review
23 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
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The use of biomarkers to identify patients who can benefit from treatment with a specific anticancer agent has the potential to both improve patient care and accelerate drug development. The development of targeted agents and their accompanying biomarkers frequently occurs contemporaneously, and confidence in a putative biomarker's performance might, therefore, be insufficient to restrict the definitive testing of a new agent to the subgroup of biomarker-positive patients. This Review considers which clinical trial designs and analysis strategies are appropriate for use in phase III, biomarker-driven, randomized clinical trials, on the basis of pre-existing evidence that the biomarker can successfully identify patients who will respond to the treatment in question. The types of interim monitoring that are appropriate for these trials are also discussed. In addition, enrichment strategies based on the use of prognostic biomarkers to separate a population into subgroups with better and worse outcomes, regardless of treatment, are described. Finally, the possibility of formally using a biomarker during phase II drug development, to select what type of biomarker-driven strategy should be used in the phase III trial, is discussed.
Indexed as
Identifiers
24281059What 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.