How to Develop, Validate, and Compare Clinical Prediction Models Involving Radiological Parameters: Study Design and Statistical Methods.
How to Develop, Validate, and Compare Clinical Prediction Models Involving Radiological Parameters: Study Design and Statistical Methods.
复制标题
DOI：
10.3348/kjr.2016.17.3.339
复制
发表时间：
2016-05
影响因子：
4.8
通讯作者：
Choi BW
中科院分区：
文献类型：
--
作者：
Han K;Song K;Choi BW
开发临床预测模型以根据多个临床或非临床参数计算特定预后或诊断结果的存在/发生或未来过程的概率估计值。放射成像技术正在发展，以准确检测和早期诊断疾病，这将最终影响患者的结果。因此，通过放射学手段，特别是诊断成像获得的结果经常被纳入临床预测模型作为重要的预测参数，并且预测模型的性能可以在诊断和预后设置中得到改善。本文以概念性的方式解释了开发和验证临床预测模型的整个过程，该模型涉及与研究设计和统计方法相关的放射学参数。收集原始数据集;选择适当的统计模型;预测选择;使用校准图，Hosmer-Lemeshow检验和C指数评估模型性能;内部和外部验证;使用C指数，净重新分类改进和综合区分改进比较不同模型;以及创建易于使用的预测评分系统的方法。本文可为临床科研工作者提供实用的方法学参考。
Clinical prediction models are developed to calculate estimates of the probability of the presence/occurrence or future course of a particular prognostic or diagnostic outcome from multiple clinical or non-clinical parameters. Radiologic imaging techniques are being developed for accurate detection and early diagnosis of disease, which will eventually affect patient outcomes. Hence, results obtained by radiological means, especially diagnostic imaging, are frequently incorporated into a clinical prediction model as important predictive parameters, and the performance of the prediction model may improve in both diagnostic and prognostic settings. This article explains in a conceptual manner the overall process of developing and validating a clinical prediction model involving radiological parameters in relation to the study design and statistical methods. Collection of a raw dataset; selection of an appropriate statistical model; predictor selection; evaluation of model performance using a calibration plot, Hosmer-Lemeshow test and c-index; internal and external validation; comparison of different models using c-index, net reclassification improvement, and integrated discrimination improvement; and a method to create an easy-to-use prediction score system will be addressed. This article may serve as a practical methodological reference for clinical researchers.