Keloids are chronic fibroproliferative skin disorders with high recurrence rates and limited treatment options, yet reliable diagnostic biomarkers are lacking. Current classification systems rely heavily on clinical observation, underscoring the need for objective, noninvasive tools. In this exploratory study, serum-based 1H nuclear magnetic resonance (NMR) measurement combined with short-time Fourier transform (STFT) for time-frequency analysis was performed, followed by principal component analysis (PCA), to investigate potential patient subgroups. Serum samples from 29 patients were analysed and PC1 scores suggested two potential patient subgroups. Retrospective analysis showed that these subgroups differed primarily in keloid aetiology: one group predominantly included cases arising from unclear or minimal causes (e.g., acne, folliculitis), whereas the other comprised cases following clear traumatic events (e.g., surgery). Although most clinical variables showed no significant differences, significant differences in aetiology and Japan Scar Workshop Scar Scale (JSS) scores support the biological relevance of this separation of subgroups. These findings suggest that the time-frequency features of NMR signals from serum samples capture systemic characteristics associated with keloid pathophysiology. If validated in larger cohorts, this approach may serve as a noninvasive adjunct to clinical assessment and lay the foundation for objective patient stratification and precision-guided treatment strategies.
Xia et al. (Sun,) studied this question.