Department of Clinical Epidemiology, Julius Center for Health Sciences and Primary Care, University Medical Center (UMC), Utrecht, the Netherlands.
J Thromb Haemost. 2013 Jun;11 Suppl 1:129-41. doi: 10.1111/jth.12262.
Risk prediction models can be used to estimate the probability of either having (diagnostic model) or developing a particular disease or outcome (prognostic model). In clinical practice, these models are used to inform patients and guide therapeutic management. Examples from the field of venous thrombo-embolism (VTE) include the Wells rule for patients suspected of deep venous thrombosis and pulmonary embolism, and more recently prediction rules to estimate the risk of recurrence after a first episode of unprovoked VTE. In this paper, the three phases that are recommended before a prediction model may be used in daily practice are described: development, validation, and impact assessment. In the development phase, the focus is on model development commonly using a multivariable logistic (diagnostic) or survival (prognostic) regression analysis. The performance of the developed model is expressed by discrimination, calibration and (re-) classification. In the validation phase, the developed model is tested in a new set of patients using these same performance measures. This is important, as model performance is commonly poorer in a new set of patients, e.g. due to case-mix or domain differences. Finally, in the impact phase the ability of a prediction model to actually guide patient management is evaluated. Whereas in the development and validation phase single cohort designs are preferred, this last phase asks for comparative designs, ideally randomized designs; therapeutic management and outcomes after using the prediction model is compared to a control group not using the model (e.g. usual care).
风险预测模型可用于估计个体患有（诊断模型）或发展为特定疾病或结局（预后模型）的概率。在临床实践中，这些模型用于为患者提供信息并指导治疗管理。静脉血栓栓塞症（VTE）领域的示例包括怀疑深静脉血栓形成和肺栓塞的 Wells 规则，以及最近用于估计首次无诱因 VTE 发作后复发风险的预测规则。本文描述了预测模型在日常实践中使用前推荐的三个阶段：开发、验证和影响评估。在开发阶段，重点是使用多变量逻辑（诊断）或生存（预后）回归分析进行模型开发。所开发模型的性能通过区分度、校准和（重新）分类来表示。在验证阶段，使用相同的性能指标在新的患者群体中测试开发的模型。这很重要，因为模型性能在新的患者群体中通常较差，例如由于病例组合或领域差异。最后，在影响阶段，评估预测模型实际指导患者管理的能力。虽然在开发和验证阶段首选单队列设计，但最后一个阶段需要比较设计，理想情况下是随机设计；使用预测模型的治疗管理和结局与不使用模型的对照组（例如常规护理）进行比较。
