ArticleJournal of pharmacokinetics and pharmacodynamics2016
Improvement in latent variable indirect response joint modeling of a continuous and a categorical clinical endpoint in rheumatoid arthritis.
Article in Journal of pharmacokinetics and pharmacodynamics, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 13 papers.
What it found
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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.
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Who cites it
13 citing papers in PubMed.
- Application of Beta-Distribution and Combined Uniform and Binomial Methods in Longitudinal Modeling of Bounded Outcome Score Data.The AAPS journal · 2020Trial
- Joint longitudinal model development: application to exposure-response modeling of ACR and DAS scores in rheumatoid arthritis patients treated with sirukumab.Journal of pharmacokinetics and pharmacodynamics · 2018Trial
- Improvement in latent variable indirect response modeling of multiple categorical clinical endpoints: application to modeling of guselkumab treatment effects in psoriatic patients.Journal of pharmacokinetics and pharmacodynamics · 2017Trial
- A framework for precision "dosing" of mental healthcare services: algorithm development and clinical pilot.International journal of mental health systems · 2023Article
- Latent variable indirect response modeling of clinical efficacy endpoints with combination therapy: application to guselkumab and golimumab in patients with ulcerative colitis.Journal of pharmacokinetics and pharmacodynamics · 2023Article
- Improving categorical endpoint longitudinal exposure-response modeling through the joint modeling with a related endpoint.Journal of pharmacokinetics and pharmacodynamics · 2022Article
- Exposure-Response Modeling to Support Dosing Selection for Phase IIb Development of Kukoamine B in Sepsis Patients.Frontiers in pharmacology · 2021Article
- Facilitating Longitudinal Exposure-Response Modeling of a Composite Endpoint Using the Joint Modeling of Sparsely and Frequently Collected Subcomponents.The AAPS journal · 2020Article
- Applying Beta Distribution in Analyzing Bounded Outcome Score Data.The AAPS journal · 2020Article
- Modeling near-continuous clinical endpoint as categorical: application to longitudinal exposure-response modeling of Mayo scores for golimumab in patients with ulcerative colitis.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- A comprehensive evaluation of exposure-response relationships in clinical trials: application to support guselkumab dose selection for patients with psoriasis.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Challenges in longitudinal exposure-response modeling of data from complex study designs: a case study of modeling CDAI score for ustekinumab in patients with Crohn's disease.Journal of pharmacokinetics and pharmacodynamics · 2017Article
- Landmark and longitudinal exposure-response analyses in drug development.Journal of pharmacokinetics and pharmacodynamics · 2017Article
Corrections and comments
- Erratum issued
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Improving the quality of exposure-response modeling is important in clinical drug development. The general joint modeling of multiple endpoints is made possible in part by recent progress on the latent variable indirect response (IDR) modeling for ordered categorical endpoints. This manuscript aims to investigate, when modeling a continuous and a categorical clinical endpoint, the level of improvement achievable by joint modeling in the latent variable IDR modeling framework through the sharing of model parameters for the individual endpoints, guided by the appropriate representation of drug and placebo mechanism. This was illustrated with data from two phase III clinical trials of intravenously administered mAb X for the treatment of rheumatoid arthritis, with the 28-joint disease activity score (DAS28) and 20, 50, and 70% improvement in the American College of Rheumatology (ACR20, ACR50, and ACR70) disease severity criteria were used as efficacy endpoints. The joint modeling framework led to a parsimonious final model with reasonable performance, evaluated by visual predictive check. The results showed that, compared with the more common approach of separately modeling the endpoints, it is possible for the joint model to be more parsimonious and yet better describe the individual endpoints. In particular, the joint model may better describe one endpoint through subject-specific random effects that would not have been estimable from data of this endpoint alone.
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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.