Occurrence of metachronous basal cell carcinomas: a prognostic model. (1st October 2017)

• Record Type: Journal Article
• Authors: Smedinga, H.; Verkouteren, J.A.C.; Steyerberg, E.W.; Hofman, A.; Nijsten, T.; Vergouwe, Y.
• Is Part Of: British journal of dermatology. Volume 177:Number 4(2017)
• Page Start: 1113
• Page End: 1121
• Publication Date: 2017-10-01
• Subjects: Dermatology -- Periodicals; Skin -- Diseases -- Periodicals; 616.5
• DOI: 10.1111/bjd.15771
• Languages: English
• ISSNs: 0007-0963

Abstract

Summary: Background: A third of patients with a first basal cell carcinoma (BCC) will develop subsequent (metachronous) BCCs. Objectives: To study the prognostic effect of the number of previous BCC diagnosis dates a patient has experienced to derive a prediction model to assess the risk of metachronous BCCs that may inform individualized decision making on surveillance. Methods: We considered participants of north‐western European ancestry from a prospective population‐based cohort study (Rotterdam Study). After linkage with the Dutch Pathology Registry, 1077 patients with a first BCC were included. Candidate predictors for metachronous BCCs included patient, lifestyle and tumour characteristics. The prognostic model was developed with Fine and Gray regression analysis to account for competing risk of death. We used bootstrapping to correct for within‐patient correlation and statistical optimism in predictive performance. Results: Second to fifth BCCs occurred in 293, 122, 58 and 36 patients, with median follow‐up times of 3·0, 2·1, 1·7 and 1·8 years after the previous BCC, respectively. The risk of a new BCC was higher for patients with more metachronous BCCs. Having more than one BCC at diagnosis was another strong predictor of metachronous BCCs. Discriminative ability of the model was reasonable with an optimism‐corrected c ‐index of 0·70 at 3 years. Conclusions: The number of previous BCC diagnosis dates was a strong prognostic factor and should be considered when predicting the risk of metachronous BCCs. When the number of previous BCC diagnosis dates is combined with other readily available characteristics into a prognostic model, patients at high risk of a new BCC can be identified.