ArticleThe AAPS journal2019
A Bounded Integer Model for Rating and Composite Scale Data.
Article in The AAPS journal, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 26 citations in OpenAlex.
- A Longitudinal Disease Progression Model Characterizing Endoscopic Response and Remission in Crohn's Disease.Journal of pharmacokinetics and pharmacodynamics · 2026Trial
- Pharmacokinetics and pharmacodynamics of intravenous and oral (S)-ketamine: Investigating metabolite contribution to subjective effects.British journal of clinical pharmacology · 2026Trial
- Early exposure-response modeling of an interferon-beta monoclonal antibody (dazukibart) in adults with dermatomyositis.Journal of pharmacokinetics and pharmacodynamics · 2026Trial
- Pharmacokinetic and Pharmacodynamic Modeling of Clonidine and Midazolam for Sedation in Pediatric Intensive Care.Paediatric anaesthesia · 2025Trial
- Exposure-response modeling of liver fat imaging endpoints in non-alcoholic fatty liver disease populations administered ervogastat alone and co-administered with clesacostat.CPT: pharmacometrics & systems pharmacology · 2025Trial
- Employing zero-inflated beta distribution in an exposure-response analysis of TYK2/JAK1 inhibitor brepocitinib in patients with plaque psoriasis.Journal of pharmacokinetics and pharmacodynamics · 2024Trial
- Tutorial on Analyzing Patient-Reported Outcome Measures in Clinical Development.Clinical and translational science · 2026Review
- A tutorial on pharmacometric Markov models.CPT: pharmacometrics & systems pharmacology · 2025Article
- Comparison of the power and type 1 error of total score models for drug effect detection in clinical trials.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Moving Beyond Boundaries: Utilization of Longitudinal Exposure-Response Model for Bounded Outcome Score to Inform Decision Making in the Accelerated Drug Development Paradigm.Clinical pharmacokinetics · 2024Article
- Modeling of Parkinson's Disease Progression and Implications for Detection of Disease Modification in Treatment Trials.Journal of Parkinson's disease · 2024Article
- A disease model predicting placebo response and remission status of patients with ulcerative colitis using modified Mayo score.Clinical and translational science · 2023Article
- Optimized infusion rates for N,N-dimethyltryptamine to achieve a target psychedelic intensity based on a modeling and simulation framework.CPT: pharmacometrics & systems pharmacology · 2023Article
- Bounded integer model-based analysis of psoriasis area and severity index in patients with moderate-to-severe plaque psoriasis receiving BI 730357.CPT: pharmacometrics & systems pharmacology · 2023Article
- Improved numerical stability for the bounded integer model.Journal of pharmacokinetics and pharmacodynamics · 2021Article
- An Item Response Theory-Informed Strategy to Model Total Score Data from Composite Scales.The AAPS journal · 2021Article
- Bounded Integer Modeling of Symptom Scales Specific to Lower Urinary Tract Symptoms Secondary to Benign Prostatic Hyperplasia.The AAPS journal · 2021Article
- Two-part models for repeatedly measured ordinal data with "don't know" category.Statistics in medicine · 2020Article
- Comparison of Precision and Accuracy of Five Methods to Analyse Total Score Data.The AAPS journal · 2020Article
- A phase I-II design based on periodic and continuous monitoring of disease status and the times to toxicity and death.Statistics in medicine · 2020Article
Corrections and comments
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Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Rating and composite scales are commonly used to assess treatment efficacy. The two main strategies for modelling such endpoints are to treat them as a continuous or an ordered categorical variable (CV or OC). Both strategies have disadvantages, including making assumptions that violate the integer nature of the data (CV) and requiring many parameters for scales with many response categories (OC). We present a method, called the bounded integer (BI) model, which utilises the probit function with fixed cut-offs to estimate the probability of a certain score through a latent variable. This method was successfully implemented to describe six data sets from four different therapeutic areas: Parkinson's disease, Alzheimer's disease, schizophrenia, and neuropathic pain. Five scales were investigated, ranging from 11 to 181 categories. The fit (likelihood) was better for the BI model than for corresponding OC or CV models (ΔAIC range 11-1555) in all cases but one (∆AIC - 63), while the number of parameters was the same or lower. Markovian elements were successfully implemented within the method. The performance in external validation, assessed through cross-validation, was also in favour of the new model (ΔOFV range 22-1694) except in one case (∆OFV - 70). A residual for diagnostic purposes is discussed. This study shows that the BI model respects the integer nature of data and is parsimonious in terms of number of estimated parameters.
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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.