ArticleThe AAPS journal2020
Item Response Theory Modeling of the International Prostate Symptom Score in Patients with Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia.
Article in The AAPS journal, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT06820606 (A Randomized Controlled Trial Comparing Efficacy and Cost Effectiveness of Water Vapour Thermal Therapy), which is not on this map. Cited by 8 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.
A Randomized Controlled Trial Comparing Efficacy and Cost Effectiveness of Water Vapour Thermal Therapy (Rezum) and Prostatic Urethral Lift (UroLift) in Men With Benign Prostatic Hyperplasia
Who cites it
8 citing papers in PubMed, 9 citations in OpenAlex.
- Integrated Modeling of Digital-Motor and Clinician-Reported Outcomes Using Item Response Theory: Towards Powerful Trials for Rare Neurological Diseases.CPT: pharmacometrics & systems pharmacology · 2025Observational
- Differential impact of digital therapy on storage and voiding LUTS: A post-hoc IPSS analysis from the BEST randomized controlled trial.BJUI compass · 2025Article
- Quantitative Comparisons of Progressive Supranuclear Palsy Rating Scale Versions Using Item Response Theory.Movement disorders : official journal of the Movement Disorder Society · 2024Article
- Item performance of the scale for the assessment and rating of ataxia in rare and ultra-rare genetic ataxias.CPT: pharmacometrics & systems pharmacology · 2024Article
- Comparison of Two Methods for Determining Item Characteristic Functions and Latent Variable Time-Course for Pharmacometric Item Response Models.The AAPS journal · 2024Article
- A disease model predicting placebo response and remission status of patients with ulcerative colitis using modified Mayo score.Clinical and translational science · 2023Article
- Bounded Integer Modeling of Symptom Scales Specific to Lower Urinary Tract Symptoms Secondary to Benign Prostatic Hyperplasia.The AAPS journal · 2021Article
- Integrated Item Response Theory Modeling of Multiple Patient-Reported Outcomes Assessing Lower Urinary Tract Symptoms Associated with Benign Prostatic Hyperplasia.The AAPS journal · 2020Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Item response theory (IRT) was used to characterize the time course of lower urinary tract symptoms due to benign prostatic hyperplasia (BPH-LUTS) measured by item-level International Prostate Symptom Scores (IPSS). The Fisher information content of IPSS items was determined and the power to detect a drug effect using the IRT approach was examined. Data from 403 patients with moderate-to-severe BPH-LUTS in a placebo-controlled phase II trial studying the effect of degarelix over 6 months were used for modeling. Three pharmacometric models were developed: a model for total IPSS, a unidimensional IRT model, and a bidimensional IRT model, the latter separating voiding and storage items. The population-level time course of BPH-LUTS in all models was described by initial improvement followed by worsening. In the unidimensional IRT model, the combined information content of IPSS voiding items represented 72% of the total information content, indicating that the voiding subscore may be more sensitive to changes in BPH-LUTS compared with the storage subscore. The pharmacometric models showed considerably higher power to detect a drug effect compared with a cross-sectional and while-on-treatment analysis of covariance, respectively. Compared with the sample size required to detect a drug effect at 80% power with the total IPSS model, a reduction of 5.9% and 11.7% was obtained with the unidimensional and bidimensional IPSS IRT model, respectively. Pharmacometric IRT analysis of the IPSS within BPH-LUTS may increase the precision and efficiency of treatment effect assessment, albeit to a more limited extent compared with applications in other therapeutic areas.
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