ArticleCPT: pharmacometrics & systems pharmacology2018
Comparison of Power, Prognosis, and Extrapolation Properties of Four Population Pharmacodynamic Models of HbA1c for Type 2 Diabetes.
Article in CPT: pharmacometrics & systems pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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
5 citing papers in PubMed.
- Model-Informed Approaches for Pediatric Type 2 Diabetes Evidence Generation: Insights from a Model-Based Longitudinal HbA1c Meta-Analysis from EMA Marketing Authorization Applications.Clinical pharmacology and therapeutics · 2026Article
- A Review of Semi-Mechanistic HbA1c Models in People with Type 2 Diabetes: Strengths, Limitations, and Applications.Journal of clinical pharmacology · 2026Review
- Evaluation of Four Semi-Mechanistic Models for Predicting Glycemic Control With a Glucagon Receptor Antagonist in People With Type 2 Diabetes.CPT: pharmacometrics & systems pharmacology · 2025Article
- Optimization of trial duration to predict long-term HbA1c change with therapy: A pharmacometrics simulation-based evaluation.CPT: pharmacometrics & systems pharmacology · 2022Article
- Research Progress of Population Pharmacokinetic of Metformin.BioMed research international · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Reusing published models saves time; time to be used for informing decisions in drug development. In antihyperglycemic drug development, several published HbA1c models are available but selecting the appropriate model for a particular purpose is challenging. This study aims at helping selection by investigating four HbA1c models, specifically the ability to identify drug effects (shape, site of action, and power) and simulation properties. All models could identify glucose effect nonlinearities, although for detecting the site of action, a mechanistic glucose model was needed. Power was highest for models using mean plasma glucose to drive HbA1c formation. Insulin contribution to power varied greatly depending on the drug target; it was beneficial only if the drug target was insulin secretion. All investigated models showed good simulation properties. However, extrapolation with the mechanistic model beyond 12 weeks resulted in drug effect overprediction. This investigation aids drug development in decisions regarding model choice if reusing published HbA1c models.
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Registered trials
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