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Risk prediction models for incident primary cutaneous melanoma: A systematic review

机译:突发性原发性皮肤黑色素瘤的风险预测模型:系统评价

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IMPORTANCE Currently, there is no comprehensive assessment of melanoma risk prediction models. OBJECTIVE To systematically review published studies reporting multivariable risk prediction models for incident primary cutaneous melanoma for adults. EVIDENCE REVIEW EMBASE, MEDLINE, PREMEDLINE, and Cochrane databases were searched to April 30, 2013. Eligible studies were hand searched and citation tracked. Two independent reviewers extracted information. FINDINGS Nineteen studies reporting 28 melanoma prediction models were included. The number of predictors in the final models ranged from 2 to 13; the most common were nevi, skin type, freckle density, age, hair color, and sunburn history. There was limited reporting and substantial variation among the studies in model development and performance. Discrimination (the ability of the model to differentiate between patients with and without melanoma) was reported in 9 studies and ranged from fair to very good (area under the receiver operating characteristic curve, 0.62-0.86). Few studies assessed internal or external validity of the models or their use in clinical and public health practice. Of the published melanoma risk prediction models, the risk prediction tool developed by Fears and colleagues, which was designed for the US population, appears to be the most clinically useful and may also assist in identifying high-risk groups for melanoma prevention strategies. CONCLUSIONS AND RELEVANCE Few melanoma risk prediction models have been comprehensively developed and assessed. More external validation and prospective evaluation will help translate melanoma risk prediction models into useful tools for clinical and public health practice.
机译:重要性目前,尚无关于黑色素瘤风险预测模型的全面评估。目的系统回顾已发表的研究报告,该研究报告了成年人原发性皮肤黑色素瘤的多变量风险预测模型。证据审查EMBASE,MEDLINE,PREMEDLINE和Cochrane数据库的检索时间截止至2013年4月30日。对符合条件的研究进行了手工检索并跟踪了引文。两名独立的审阅者提取了信息。研究结果包括19个报告28种黑色素瘤预测模型的研究。最终模型中的预测变量数量为2到13。最常见的是痣,皮肤类型,雀斑密度,年龄,头发颜色和晒伤史。在模型开发和性能方面的研究报告有限,且差异很大。在9项研究中报告了区分(模型区分有无黑色素瘤患者的能力),范围从一般到非常好(接受者工作特征曲线下的面积0.62-0.86)。很少有研究评估模型的内部或外部有效性或它们在临床和公共卫生实践中的使用。在已发布的黑色素瘤风险预测模型中,由Fears和同事开发的,针对美国人群设计的风险预测工具似乎在临床上最有用,并且可能还有助于确定用于黑色素瘤预防策略的高风险人群。结论和相关性很少有全面开发和评估黑色素瘤风险预测模型。更多的外部验证和前瞻性评估将有助于将黑色素瘤风险预测模型转化为临床和公共卫生实践的有用工具。

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