This repository contains the code developed for the article by Duverdier et al. (2024), "Evaluation of measurement errors in the Patient-Oriented Eczema Measure (POEM) outcome", published in Clinical & Experimental Allergy.
The Patient-Oriented Eczema Measure (POEM) is the recommended the core outcome measure of eczema symptoms perceived by patients in clinical trials and practice. POEM is reported by recalling the presence/absence of symptoms that occurred in the last seven days. The FDA has highlighted the importance of considering the recall period of patient-reported outcome measures. This project investigated measurement errors in the Patient-Oriented Eczema Measure (POEM) score due to the imperfect recall of symptoms.
The code is written in the R language for statistical computing (version 4.2.0) and the probabilistic programming language Stan for the models.
Package dependencies can be found in renv.lock.
Files for the analysis conducted in this project are:
01_missing_values_imputation.R: Impute missing daily symptom presence/absence using a Markov chain model implemented in the EczemaPred R package.02_recall_error.R: Compare d-POEM (derived from daily diaries) and r-POEM (recalled) scores, and calculate recall bias and recall noise in the POEM score.03a_recall_model_check.R: Prior predictive check for the recalled days model.03b_recall_model_fit.R: Fit the recalled days model on the data and plot the results of the model.
Common functions used throughout the project can be found in functions.R.
The code for the Stan recalled days model developed in this project can be found in Model/recalled_days_model.stan.
The open source version of this project is licensed under the GPLv3 license, which can be seen in the LICENSE file.