Trial reportBMC medical research methodology2022
Evaluating the impact of calibration of patient-reported outcomes measures on results from randomized clinical trials: a simulation study based on Rasch measurement theory.
Trial report in BMC medical research methodology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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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
3 citing papers in PubMed.
- Comparative performance of PROMIS Sleep Disturbance computerized adaptive testing algorithms and static short form in postmenopausal women.Journal of patient-reported outcomes · 2025Article
- Identification of sources of DIF using covariates in patient-reported outcome measures: a simulation study comparing two approaches based on Rasch family models.Frontiers in psychology · 2023Article
- Application of the Rasch measurement model in rehabilitation research and practice: early developments, current practice, and future challenges.Frontiers in rehabilitation sciences · 2023Article
Corrections and comments
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundMeaningfully interpreting patient-reported outcomes (PRO) results from randomized clinical trials requires that the PRO scores obtained in the trial have the same meaning across patients and previous applications of the PRO instrument. Calibration of PRO instruments warrants this property. In the Rasch measurement theory (RMT) framework, calibration is performed by fixing the item parameter estimates when measuring the targeted concept for each individual of the trial. The item parameter estimates used for this purpose are typically obtained from a previous "calibration" study. But imposing this constraint on item parameters, instead of freely estimating them directly in the specific sample of the trial, may hamper the ability to detect a treatment effect. The objective of this simulation study was to explore the potential negative impact of calibration of PRO instruments that were developed using RMT on the comparison of results between treatment groups, using different analysis methods.
methodsPRO results were simulated following a polytomous Rasch model, for a calibration and a trial sample. Scenarios included varying sample sizes, with instrument of varying number of items and modalities, and varying item parameters distributions. Different treatment effect sizes and distributions of the two patient samples were also explored. Cross-sectional comparison of treatment groups was performed using different methods based on a random effect Rasch model. Calibrated and non-calibrated approaches were compared based on type-I error, power, bias, and variance of the estimates for the difference between groups.
resultsThere was no impact of the calibration approach on type-I error, power, bias, and dispersion of the estimates. Among other findings, mistargeting between the PRO instrument and patients from the trial sample (regarding the level of measured concept) resulted in a lower power and higher position bias than appropriate targeting.
conclusionsCalibration does not compromise the ability to accurately assess a treatment effect using a PRO instrument developed within the RMT paradigm in randomized clinical trials. Thus, given its essential role in producing interpretable results, calibration should always be performed when using a PRO instrument developed using RMT as an endpoint in a randomized clinical trial.
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