Department of Public Health, Erasmus MC Cancer Institute, Rotterdam, the Netherlands.
Department of Dermatology, Erasmus MC Cancer Institute, Rotterdam, the Netherlands.
Br J Dermatol. 2017 Oct;177(4):1113-1121. doi: 10.1111/bjd.15771. Epub 2017 Sep 11.
A third of patients with a first basal cell carcinoma (BCC) will develop subsequent (metachronous) BCCs.
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.
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.
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.
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.
三分之一的首次基底细胞癌（BCC）患者会发展出随后的（异时性）BCC。
研究患者经历过的先前 BCC 诊断日期数量对预后的影响，以建立预测模型来评估异时性 BCC 的风险，从而为监测提供个体化决策依据。
我们考虑了来自前瞻性基于人群的队列研究（鹿特丹研究）的北欧血统参与者。在与荷兰病理登记处链接后，纳入了 1077 名首次 BCC 患者。异时性 BCC 的候选预测因子包括患者、生活方式和肿瘤特征。使用 Fine 和 Gray 回归分析来建立预测模型，以考虑死亡的竞争风险。我们使用自举法来纠正患者内相关性和预测性能的统计乐观性。
293、122、58 和 36 例患者分别发生了第二至第五个 BCC，前一个 BCC 后的中位随访时间分别为 3.0、2.1、1.7 和 1.8 年。发生更多异时性 BCC 的患者新发生 BCC 的风险更高。诊断时患有多个 BCC 也是异时性 BCC 的另一个强烈预测因子。该模型的判别能力合理，在 3 年内经校正后的 C 指数为 0.70。
先前 BCC 诊断日期的数量是一个强有力的预后因素，在预测异时性 BCC 的风险时应予以考虑。当先前 BCC 诊断日期的数量与其他易于获得的特征结合到一个预测模型中时，可以识别出发生新的 BCC 风险较高的患者。
