IMPORTANCE: Response to laser treatment for café au lait macules (CALMs) is inconsistent and difficult to predict. OBJECTIVE: To test the hypothesis that irregularly bordered CALMs of the “coast of Maine” subtype respond better to treatment than those of the smooth-bordered “coast of California” subtype. DESIGN, SETTING, AND PARTICIPANTS: This retrospective case series included patients from 2 multiple-clinician US practices treated from 2005 through 2016. All patients had a clinical diagnosis of CALM and were treated with a Q-switched or picosecond laser. A total of 51 consecutive patients were eligible, 6 of whom were excluded owing to ambiguous lesion subtype. Observers were blinded to final patient groupings. EXPOSURES: Treatment with 755-nm alexandrite picosecond laser, Q-switched ruby laser, Q-switched alexandrite laser, or Q-switched 1064-nm Nd:YAG laser. MAIN OUTCOMES AND MEASURES: Main outcome was grade in a visual analog scale (VAS) consisting of 4 levels of treatment response: poor (grade 1, 0%-25% improvement), fair (grade 2, 26%-50% improvement), good (grade 3, 51%-75% improvement), and excellent (grade 4, 76%-100% improvement). RESULTS Forty-five patients were included in the series, 19 with smooth-bordered lesions and 26 with irregularly bordered lesions. Thirty-four (76%) of the participants were female; 33 (73%) were white; and the mean age at the time of laser treatment was 14.5 years (range, 0-44 years). Smooth-bordered lesions received a mean VAS score of 1.76, corresponding to a fair response on average (26%-50% pigmentary clearance). Irregularly bordered lesions received a mean VAS score of 3.67, corresponding to an excellent response on average (76%-100% clearance) (P < .001). CONCLUSIONS AND RELEVANCE: CALMs with jagged or ill-defined borders of the coast of Maine subtype tend to respond well to laser treatment, whereas those with smooth and well-defined borders of the coast of California subtype tend to have poor response. Clinicians using Q-switched or picosecond lasers to treat CALMs can use morphologic characteristics to help predict response and more effectively manage patient expectations.
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