Alopecia Areata: Multivariate Analysis for Predicting Its Clinical Course

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    TLDR Certain factors like patchy hair loss at the back of the head, being female, and younger age at diagnosis can lead to a worse outcome for alopecia areata.
    The study titled "Alopecia areata: Multivariate analysis for predicting its clinical course" aimed to identify predictive factors influencing the long-term clinical course of alopecia areata (AA). The retrospective clinical cohort consisted of 137 AA patients (35.0% men) with a mean age of 31.2 years at the time of diagnosis, observed between 1990 and 2011. The study found that patchy, occipital hair loss, being female, and a younger age at diagnosis were associated with a poorer prognosis. In contrast, a positive family history of AA, personal past history of atopy, autoimmune diseases, psychiatric disorders, smoking, and alcohol consumption did not significantly affect the clinical course of AA. The predictive model developed, which included scalp location of AA, sex, age at diagnosis, and AA type, had a C-index of 0.76, indicating moderate utility in predicting the clinical course of AA.
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