Mycophenolate mofetil and lichen planopilaris: systematic review and meta-analysis.
Niyaz MostafaKevin PhanSaxon D SmithPublished in: The Journal of dermatological treatment (2020)
Background: For severe cases of lichen planopilaris (LPP), unresponsive to first line therapy, systemic or potent agents may be required for disease control. There have been several reports of the off-label use of mycophenolate mofetil (MMF) in patients with LPP or have developed adverse effects to initial agents.Methods: A systematic review and meta-analysis was performed according to recommended Preferred Reporting Items for Systematic Reviews and Meta-Analyses guidelines. Studies with ≥5 cases reporting the outcomes of MMF in LPP were pooled and a meta-analysis of proportion was performed. Case reports were excluded from analysis.Results: A total of six studies were identified and included for meta-analysis, comprising 94 LPP patients. The pooled proportion of any good response (partial or complete) was 69.2% (95% confidence interval (CI): 47.8-77). The pooled proportion of complete response was 20% (95% CI: 10.1-36.3). The pooled proportion of partial responses was 49.2% (95% CI: 30.5-63.7). Side effects occurred in 16.9% (95% CI: 17.6-33.2). of cases, which included elevated LFTs, edema, hyperlipidemia, anemia, herpes zoster infection, photosensitivity, and urinary tract infection.Conclusion: The current evidence for MMF remains limited. However, it appears to be a potential treatment option for patients with severe or recalcitrant LPP who have failed hydroxychloroquine and other immunosuppressants.
Keyphrases
- meta analyses
- systematic review
- urinary tract infection
- case control
- end stage renal disease
- adverse drug
- randomized controlled trial
- chronic kidney disease
- ejection fraction
- phase iii
- newly diagnosed
- early onset
- prognostic factors
- stem cells
- high fat diet
- clinical trial
- adipose tissue
- risk assessment
- anti inflammatory
- skeletal muscle
- emergency department
- weight loss
- study protocol
- double blind
- data analysis