Predictive Model for Differential Diagnosis of Inflammatory Papular Dermatoses of the Face.

BACKGROUND

The clinical features of inflammatory papular dermatoses of the face are very similar. Their clinical manifestations have been described on the basis of a small number of case reports and are not specific.

OBJECTIVE

This study aimed to use computer-aided image analysis (CAIA) to compare the clinical features and parameters of inflammatory papular dermatoses of the face and to develop a formalized diagnostic algorithm based on the significant findings.

METHODS

The study included clinicopathologically confirmed inflammatory papular dermatoses of the face: 8 cases of eosinophilic pustular folliculitis (EPF), 13 of granulomatous periorificial dermatitis-lupus miliaris disseminatus faciei (GPD-LMDF) complex, 41 of granulomatous rosacea-papulopustular rosacea complex (GR-PPR) complex, and 4 of folliculitis. Clinical features were evaluated, and area density of papular lesions was quantitatively measured with CAIA. Based on these variables, we developed a predictive model for differential diagnosis using classification and regression tree analysis.

RESULTS

The EPF group showed lesion asymmetry and annular clusters of papules in all cases. The GPD-LMDF complex group had significantly higher periocular density. The GR-PPR complex group showed a higher area density of unilateral cheek papules and the highest total area density. According to the predictive model, 3 variables were used for differential diagnosis of the 4 disease groups, and each group was diagnosed with a predicted probability of 67%~100%.

CONCLUSION

We statistically confirmed the distinct clinical features of inflammatory papular dermatoses of the face and proposed a diagnostic algorithm for clinical diagnosis.