Identification and validation of functional gastrointestinal disorder subtypes using latent class analysis: a
Alan R Zinsmeister1, Linda M Herrick2, Yuri A Saito Loftus2
1a Division of Biomedical Statistics and Informatics , Mayo Clinic , Rochester , MN , USA.
Scandinavian Journal of Gastroenterology
|November 7, 2017
Summary
Latent class analysis identified four distinct gastrointestinal symptom groups in a large community sample. This approach differentiated patients by anatomical region, offering a new way to classify functional gastrointestinal disorders.
Area of Science:
- Gastroenterology
- Biostatistics
- Epidemiology
Background:
- Functional gastrointestinal disorders (FGIDs) are challenging to categorize due to overlapping symptoms.
- Current classification systems may not fully capture distinct patient subgroups.
Purpose of the Study:
- To apply latent class analysis (LCA) to identify mutually exclusive subgroups within a population-based sample based on gastrointestinal symptoms.
- To explore an alternative method for classifying FGIDs beyond symptom overlap.
Main Methods:
- A population-based sample completed validated bowel and somatic symptom questionnaires.
- Latent class analysis (LCA) was employed to analyze symptom data, dichotomized using Rome IV criteria.
- Model fit was assessed using Akaike's Information Criterion to determine the optimal number of latent classes.
Main Results:
- Analysis of 3425 complete responses identified four distinct latent classes.
- These subgroups were characterized as 'asymptomatic,' 'upper' abdominal symptoms, 'lower' abdominal symptoms, and 'mixed' (upper and lower abdomen).
Conclusions:
- Latent class analysis successfully identified four symptom-based subgroups.
- This method provides anatomical region-based differentiation, offering a novel approach to FGID classification compared to Rome IV criteria.
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