Evaluating the Predictive Utility of Demographic, Lesion, and Inflammatory Parameters for Immunotherapy Success in Cutaneous Warts
The Predictive Utility for Immunotherapy Success in Cutaneous Warts
DOI:
https://doi.org/10.54393/pbmj.v9i7.1394Keywords:
Cutaneous Warts, Intralesional Immunotherapy, Human Papillomavirus, Induration Diameter, Predictors of Treatment Response, ROC Curve AnalysisAbstract
HPV is the cause of cutaneous warts; they're very common and sometimes do not respond to damaging treatments. An alternative treatment is intralesional immunotherapy, but there are no good predictors of clearance that will help in patient selection. Objectives: To assess the ability of baseline demographic, lesion, and inflammatory parameters (wart type, age, sex, wart count, lesion area, treatment duration, and induration diameter) to predict complete clearance, and whether induration diameter is a useful predictive biomarker. Methods: Retrospective analysis of 90 patients treated with intralesional immunotherapy (71 had successful treatment, and 19 failed). Categorical variables were compared using chi-square, continuous variables were compared using the Mann-Whitney U-test, and predictors were identified through multivariate logistic regression. The interaction between age and wart type was tested, and the induration diameter was assessed using ROC curve analysis (Youden index). Results: There were no differences among groups for any variable (categorical or continuous). No association was found between outcome and wart type (p=0.680) or sex (p=0.840), and the median induration diameter was the same across both groups (7.0 mm, p=0.910). Age was near significant (p=0.080). The multivariate model accounted for less than 6% of variance in the outcome (Nagelkerke R²=0.06) and did not have any discriminative power (AUC=0.51). Conclusions: The standard demographic, morphological, and inflammatory parameters, such as induration diameter, were not good predictors of the response to immunotherapy in this dataset, and other molecular or immunological parameters will likely be needed for better patient selection.
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