ArticleCPT: pharmacometrics & systems pharmacology2022
Tumor growth inhibition modeling to support the starting dose for dacomitinib.
Article in CPT: pharmacometrics & systems pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
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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.
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Who cites it
9 citing papers in PubMed, 9 citations in OpenAlex.
- Bridging tumor growth dynamics and survival in preclinical oncology drug development - a Tumor Growth Inhibition and Time-to-Event (TGI-TTE) modeling framework.Cancer chemotherapy and pharmacology · 2026Article
- Bridging Tumor Growth Dynamics and Survival in Preclinical Oncology Drug Development - A Translational Tumor Growth Inhibition and Time to Event (TGI-TTE) Modeling Framework.Research square · 2026Article
- Novel Drug-Disease Modeling Framework for Oncology Benefit-Risk Evaluation: Application to Tusamitamab Ravtansine.CPT: pharmacometrics & systems pharmacology · 2026Article
- Application of Machine Learning for Predicting Progression-Free and Overall Survival in Patients With Renal Cell Carcinoma.Clinical and translational science · 2025Article
- A sample size analysis of a mathematical model of longitudinal tumor volume and progression-free survival for Bayesian individual dynamic predictions in recurrent high-grade glioma.CPT: pharmacometrics & systems pharmacology · 2025Article
- A novel Bayesian generative approach for estimating tumor dynamics from published studies.CPT: pharmacometrics & systems pharmacology · 2024Article
- Building an adaptive dose simulation framework to aid dose and schedule selection.CPT: pharmacometrics & systems pharmacology · 2023Article
- Model-based prediction of progression-free survival for combination therapies in oncology.CPT: pharmacometrics & systems pharmacology · 2023Article
- Tumor growth inhibition modeling to support the starting dose for dacomitinib.CPT: pharmacometrics & systems pharmacology · 2022Article
Corrections and comments
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Authors and funding
4 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Dacomitinib is a second-generation, irreversible EGFR tyrosine kinase inhibitor for first-line treatment of patients with metastatic non-small cell lung cancer and EGFR-activating mutations. A high rate of dose reductions in the pivotal trial led to an observed inverse exposure-response (ER) relationship with the primary end points. Three ER models were developed to determine if the starting dose from the pivotal trial, 45 mg once daily (q.d.) dose, is appropriate: a longitudinal logistic regression model for adverse event-related dose changes, a Claret tumor growth inhibition (TGI) model, and a Cox model for progression-free survival (PFS) based on the TGI model predictions. This analysis included 266 patients taking dacomitinib with a starting dose of 45 mg (N = 250) or 30 mg (N = 16) q.d. The ER relationships with the time-varying exposure metrics, most recent maximum plasma concentration (C
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