Kaiser Isabelle, Pfahlberg Annette B, Uter Wolfgang, Heppt Markus V, Veierød Marit B, Gefeller Olaf
Department of Medical Informatics, Biometry and Epidemiology, Friedrich Alexander University of Erlangen-Nuremberg, 91054 Erlangen, Germany.
Department of Dermatology, University Hospital Erlangen, 91054 Erlangen, Germany.
Int J Environ Res Public Health. 2020 Oct 28;17(21):7919. doi: 10.3390/ijerph17217919.
The rising incidence of cutaneous melanoma over the past few decades has prompted substantial efforts to develop risk prediction models identifying people at high risk of developing melanoma to facilitate targeted screening programs. We review these models, regarding study characteristics, differences in risk factor selection and assessment, evaluation, and validation methods. Our systematic literature search revealed 40 studies comprising 46 different risk prediction models eligible for the review. Altogether, 35 different risk factors were part of the models with nevi being the most common one ( = 35, 78%); little consistency in other risk factors was observed. Results of an internal validation were reported for less than half of the studies ( = 18, 45%), and only 6 performed external validation. In terms of model performance, 29 studies assessed the discriminative ability of their models; other performance measures, e.g., regarding calibration or clinical usefulness, were rarely reported. Due to the substantial heterogeneity in risk factor selection and assessment as well as methodologic aspects of model development, direct comparisons between models are hardly possible. Uniform methodologic standards for the development and validation of risk prediction models for melanoma and reporting standards for the accompanying publications are necessary and need to be obligatory for that reason.
在过去几十年中,皮肤黑色素瘤发病率不断上升,促使人们付出巨大努力来开发风险预测模型,以识别有患黑色素瘤高风险的人群,从而推动有针对性的筛查项目。我们回顾这些模型,涉及研究特征、风险因素选择与评估的差异、评价及验证方法。我们的系统文献检索发现了40项研究,包含46种不同的风险预测模型符合纳入综述的条件。这些模型总共纳入了35种不同的风险因素,其中痣是最常见的(n = 35,78%);在其他风险因素方面观察到的一致性较低。不到一半的研究(n = 18,45%)报告了内部验证结果,只有6项进行了外部验证。在模型性能方面,29项研究评估了其模型的判别能力;很少有研究报告其他性能指标,例如关于校准或临床实用性的指标。由于风险因素选择与评估以及模型开发方法学方面存在很大异质性,很难对模型进行直接比较。因此,黑色素瘤风险预测模型开发与验证的统一方法学标准以及相关出版物的报告标准是必要的,并且应该具有强制性。