Latent Class Analysis to Classify Patients with Transthyretin Amyloidosis by Signs and Symptoms

The aim of this study was to develop an empirical approach to classifying patients with transthyretin amyloidosis (ATTR) based on clinical signs and symptoms.

Data from 971 symptomatic subjects enrolled in the Transthyretin Amyloidosis Outcomes Survey were analyzed using a latent class analysis approach. Differences in health status measures for the latent classes were examined.

A four-class latent class solution was the best fit for the data. The latent classes were characterized by the predominant symptoms as severe neuropathy/severe autonomic, moderate to severe neuropathy/low to moderate autonomic involvement, severe cardiac, and moderate to severe neuropathy. Incorporating disease duration improved the model fit. It was found that measures of health status varied by latent class in interpretable patterns.

This latent class analysis approach offered promise in categorizing patients with ATTR across the spectrum of disease. The four-class latent class solution included disease duration and enabled better detection of heterogeneity within and across genotypes than previous approaches, which have tended to classify patients a priori into neuropathic, cardiac, and mixed groups. Although this study utilized a cross-sectional approach to disease duration, future work could include the application of longitudinal latent class analyses.

Pfizer Inc., New York, NY, USA.