AI Article Synopsis

  • * This study aims to create a prognostic model to predict how well urticaria patients respond to antihistamines through a bidirectional cohort study.
  • * The model development involves five steps, including variable selection, data quality evaluation, statistical management, model selection strategies, and performance assessment to ensure accurate predictions.

Article Abstract

Chronic urticaria causes a significant limitation to quality of life. In the literature, various studies can be found that have reviewed several clinical and laboratory markers, but none of these variables alone is sufficient to predict the patient's prognosis. In this study, we present a protocol to develop a prognostic model that can predict the clinical response of urticaria patients to antihistamines. This is a protocol for a bidirectional cohort study. Urticaria data will be routinely collected from a population of patients over 18 years old. A full multivariable logistic regression model will be fitted, following five steps: 1) Selection of predictive variables for the model; 2) Evaluation of the quality of the collected data and control of lost data; 3) Data statistical management; 4) Strategies to select the variables to include at the end of the model; 5) Evaluation of the performance of the different possible models (predictive accuracy) and selection of the best model. The performance and internal validation of the model will be assessed. Some clinical and paraclinical variables will be measured for further exploration.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7537877PMC
http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0239962PLOS

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