Predicting keratinocyte carcinoma in patients with actinic keratosis: development and internal validation of a multivariable risk‐prediction model

BACKGROUND: Patients with actinic keratosis (AK) are at increased risk for developing keratinocyte carcinoma (KC) but predictive factors and their risk rates are unknown. OBJECTIVES: To develop and internally validate a prediction model to calculate the absolute risk of a first KC in patients with AK. METHODS: The risk‐prediction model was based on the prospective population‐based Rotterdam Study cohort. We hereto analysed the data of participants with at least one AK lesion at cohort baseline using a multivariable Cox proportional hazards model and included 13 a priori defined candidate predictor variables considering phenotypic, genetic and lifestyle risk factors. KCs were identified by linkage of the data with the Dutch Pathology Registry. RESULTS: Of the 1169 AK participants at baseline, 176 (15·1%) developed a KC after a median follow‐up of 1·8 years. The final model with significant predictors was obtained after backward stepwise selection and comprised the presence of four to nine AKs [hazard ratio (HR) 1·68, 95% confidence interval (CI) 1·17–2·42], 10 or more AKs (HR 2·44, 95% CI 1·65–3·61), AK localization on the upper extremities (HR 0·75, 95% CI 0·52–1·08) or elsewhere except the head (HR 1·40, 95% CI 0·98–2·01) and coffee consumption (HR 0·92, 95% CI 0·84–1·01). Evaluation of the discriminative ability of the model showed a bootstrap validated concordance index (c‐index) of 0·60. CONCLUSIONS: We showed that the risk of KC in patients with AK can be calculated with the use of four easily assessable predictor variables. Given the c‐index, extension of the model with additional, currently unknown predictor variables is desirable. Linked Comment: Kim et al. Br J Dermatol 2020; 183:415–416.