A consensus-based practical and daily guide for the treatment of acne patients.

BACKGROUND: Many current guidelines provide detailed evidence-based recommendations for acne treatment. OBJECTIVE: To create consensus-based, simple, easy-to-use algorithms for clinical acne treatment in daily office-based practice and to provide checklists to assist in determining why a patient may not have responded to treatment and what action to take. METHODS: Existing treatment guidelines and consensus papers were reviewed. The information in them was extracted and simplified according to daily clinical practice needs using a consensus-based approach and based on the authors' clinical expertise. RESULTS: As outcomes, separate simple algorithms are presented for the treatment of predominant comedonal, predominant papulopustular and nodular/conglobate acne. Patients with predominant comedonal acne should initially be treated with a topical retinoid, azelaic acid or salicylic acid. Fixed combination topicals are recommended for patients with predominant papulopustular acne with treatment tailored according to the severity of disease. Treatment recommendations for nodular/conglobate acne include oral isotretinoin or fixed combinations plus oral antibiotics in men, and these options may be supplemented with oral anti-androgenic hormonal therapy in women. Further decisions regarding treatment responses should be evaluated 8 weeks after treatment initiation in patients with predominant comedonal or papulopustular acne and 12 weeks after in those with nodular/conglobate acne. Maintenance therapy with a topical retinoid or azelaic acid should be commenced once a patient is clear or almost clear of their acne to prevent the disease from recurring. The principal explanations for lack of treatment response fall into 5 main categories: disease progression, non-drug-related reasons, drug-related reasons, poor adherence, and adverse events. CONCLUSION: This practical guide provides dermatologists with treatment algorithms adapted to different clinical features of acne which are simple and easy to use in daily clinical practice. The checklists to establish the causes for a lack of treatment response and subsequent action to take will facilitate successful acne management.

The effectiveness of intermittent isotretinoin treatment in mild or moderate acne.

BACKGROUND: Isotretinoin is the only drug that affects almost all factors in acne pathogenesis. Recently, its use for the treatment of chronic mild or moderate acne unresponsive to long-term antibiotic therapy, and with a tendency to cause scarring and leading to negative psychological effects, has became popular. The aim of the study was to investigate the effectiveness of intermittent isotretinoin treatment in mild or moderate acne. METHODS: Sixty patients with mild or moderate acne localized to the face were enrolled in the study. The treatment regimen consisted of isotretinoin, 0.5-0.75 mg/kg per day, applied for 1 week every 4 weeks for a total period of 6 months, according to the degree of acne and number of inflammatory lesions. RESULTS: Forty-one (68.3%) of the 60 patients completed the 6-month therapy. At the end of the treatment complete improvement was observed in 34 patients (82.9%) out of 41. All adverse effects were mild and discontinuation of the treatment was not necessary. CONCLUSION: Intermittent isotretinoin treatment was found to be a safe and effective choice for patients with mild or moderate acne.

Learning differential diagnosis of erythemato-squamous diseases using voting feature intervals.

A new classification algorithm, called VFI5 (for Voting Feature Intervals), is developed and applied to problem of differential diagnosis of erythemato-squamous diseases. The domain contains records of patients with known diagnosis. Given a training set of such records, the VFI5 classifier learns how to differentiate a new case in the domain. VFI5 represents a concept in the form of feature intervals on each feature dimension separately. classification in the VFI5 algorithm is based on a real-valued voting. Each feature equally participates in the voting process and the class that receives the maximum amount of votes is declared to be the predicted class. The performance of the VFI5 classifier is evaluated empirically in terms of classification accuracy and running time.