Clinical prediction models assist clinicians to estimate the natural course of a condition, and thus facilitate treatment decisions. The development of prediction models is increasingly common in obstetric research. Composite outcomes, whereby multiple outcomes are combined into a single endpoint, are frequently used in obstetric prediction models to increase statistical power when predicting rare events. Although existing literature has reviewed the positives and negatives of using composite outcomes in clinical trials, there has been minimal commentary on the implications of their use in the development and reporting of prognostic models. In this article, we review these issues, in particular, highlighting how unequal individual relationships between predictors and individual component outcomes can result in misleading conclusions, which may result in the omission of important but rare predictors or inappropriately inform clinical decisions to implement an intervention. We propose careful use, or where possible avoidance, of composite outcomes in the development of prognostic models in obstetrics. Methodological standards for developing prognostic models should be updated to standardise and appraise composite outcomes when their use is necessary. We also support previous recommendations to report on the accuracy of key components and inconsistencies among predictor variables.

临床预测模型可帮助临床医生估计疾病的自然病程，从而促进治疗决策。预测模型的开发在产科研究中越来越普遍。复合结果，即多个结果组合成一个终点，经常用于产科预测模型，以增加预测罕见事件时的统计能力。尽管现有文献已经回顾了在临床试验中使用复合结果的积极和消极因素，但很少有人评论它们在预后模型的开发和报告中的应用意义。在这篇文章中，我们回顾了这些问题，特别强调了预测变量和各个组成部分结果之间不平等的个体关系如何导致误导性结论，这可能会导致遗漏重要但罕见的预测因素或不恰当地告知临床决策以实施干预措施。我们建议在开发产科预后模型时谨慎使用或尽可能避免使用复合结果。应更新用于开发预后模型的方法学标准，以便在必要时对复合结果进行标准化和评估。我们还支持之前的建议，以报告关键组件的准确性和预测变量之间的不一致性。应更新用于开发预后模型的方法学标准，以便在必要时对复合结果进行标准化和评估。我们还支持之前的建议，以报告关键组件的准确性和预测变量之间的不一致性。应更新用于开发预后模型的方法学标准，以便在必要时对复合结果进行标准化和评估。我们还支持之前的建议，以报告关键组件的准确性和预测变量之间的不一致性。