Serum-Based Assessment of Alopecia Areata Response to Treatment Using ATR-FTIR Spectroscopy

The study explores the use of ATR-FTIR spectroscopy combined with machine learning to monitor treatment response in alopecia areata patients. Serum samples from 42 patients and 41 healthy donors were analyzed, revealing significant spectral variations in biochemical regions, particularly proteins, lipids, and nucleic acids. The logistic regression model achieved an AUC of 0.85 for distinguishing patients from controls and 0.86 for predicting treatment response, indicating its potential as a non-invasive diagnostic tool. The study found that shifts in the Amide I band correlated with treatment response, with right shifts often indicating clinical improvement. Despite promising results, the study's small sample size and confounding factors suggest the need for further validation in larger, multicenter trials.