ReviewBritish journal of clinical pharmacology2020
Imatinib, sunitinib and pazopanib: From flat-fixed dosing towards a pharmacokinetically guided personalized dose.
Review in British journal of clinical pharmacology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed, 1 synthesis or guideline pooled it, 78 citations in OpenAlex.
- Predictive performance of population pharmacokinetic models of imatinib in chronic myeloid leukemia patients.Cancer chemotherapy and pharmacology · 2024Pooled it
- Model-Informed Precision Dosing of Protein Kinase Inhibitors: Evaluation of Model-Averaging and Flattened Priors Methods.Clinical pharmacokinetics · 2026Trial
- Time-Dependent Bias and Prognostic Confounding in Exposure-Response Analysis of Targeted Therapies: Lessons from Sunitinib in Metastatic Renal Cancer.Clinical pharmacology and therapeutics · 2026Article
- Pharmacological Targeting of Angiogenesis in Head and Neck Cancer: Molecular Mechanisms and Emerging Therapeutic Strategies.Pharmaceuticals (Basel, Switzerland) · 2026Review
- Optimized UPLC-MS/MS Method for the Simultaneous Quantification of Pazopanib and GSK-1268997 and Its Application to Drug-Drug Interaction Studies.Drug design, development and therapy · 2026Article
- Molecular Mechanisms and Clinical Implications ofCurrent issues in molecular biology · 2025Review
- Tyrosine Kinase Inhibitors for Gastrointestinal Stromal Tumor After Imatinib Resistance.Pharmaceutics · 2025Review
- Model-Informed Dose Optimization of Pazopanib in Real-World Patients with Cancer.Clinical pharmacokinetics · 2025Article
- Exposure-Response Relationships for Toceranib in Dogs with Solid Tumors: A Pilot Study.Animals : an open access journal from MDPI · 2025Article
- Exploring the contribution of genetic variants to high sunitinib exposure in patients with cancer.British journal of clinical pharmacology · 2025Article
- Evaluating the Clinical Impact and Feasibility of Therapeutic Drug Monitoring of Pazopanib in a Real-World Soft-Tissue Sarcoma Cohort.Clinical pharmacokinetics · 2024Article
- Phenotype versus genotype to optimize cancer dosing in the clinical setting-focus on 5-fluorouracil and tyrosine kinase inhibitors.Pharmacology research & perspectives · 2024Review
- Patient perspectives on treatment-related toxicities and therapeutic drug monitoring with tyrosine kinase inhibitors for the treatment of non-small-cell lung cancer.Therapeutic advances in medical oncology · 2024Article
- Therapeutic drug monitoring to personalize dosing of imatinib, sunitinib, and pazopanib: A mixed methods study on barriers and facilitators.Cancer medicine · 2023Article
- Novel Approaches to Characterize Individual Drug Metabolism and Advance Precision Medicine.Drug metabolism and disposition: the biological fate of chemicals · 2023Review
- Therapeutic Drug Monitoring of Kinase Inhibitors in Oncology.Clinical pharmacokinetics · 2023Review
- Application of physiologically based pharmacokinetic modeling to understand real-world outcomes in patients receiving imatinib for chronic myeloid leukemia.Pharmacology research & perspectives · 2023Observational
- Framework for Implementing Individualised Dosing of Anti-Cancer Drugs in Routine Care: Overcoming the Logistical Challenges.Cancers · 2023Article
- Article
- A strategy for low-cost portable monitoring of plasma drug concentrations using a sustainable boron-doped-diamond chip.Heliyon · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Tyrosine kinase inhibitors (TKIs) are anti-cancer drugs that target tyrosine kinases, enzymes that are involved in multiple cellular processes. Currently, multiple oral TKIs have been introduced in the treatment of solid tumours, all administered in a fixed dose, although large interpatient pharmacokinetic (PK) variability is described. For imatinib, sunitinib and pazopanib exposure-treatment outcome (efficacy and toxicity) relationships have been established and therapeutic windows have been defined, therefore dose optimization based on the measured blood concentration, called therapeutic drug monitoring (TDM), can be valuable in increasing efficacy and reducing the toxicity of these drugs. In this review, an overview of the current knowledge on TDM guided individualized dosing of imatinib, sunitinib and pazopanib for the treatment of solid tumours is presented. We summarize preclinical and clinical data that have defined thresholds for efficacy and toxicity. Furthermore, PK models and factors that influence the PK of these drugs which partly explain the interpatient PK variability are summarized. Finally, pharmacological interventions that have been performed to optimize plasma concentrations are described. Based on current literature, we advise which methods should be used to optimize exposure to imatinib, sunitinib and pazopanib.
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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.