Guerra Beniamino, Gaveikaite Violeta, Bianchi Camilla, Puhan Milo A
Epidemiology, Biostatistics and Prevention Institute, University of Zurich, Zurich, Switzerland.
Eur Respir Rev. 2017 Jan 17;26(143). doi: 10.1183/16000617.0061-2016. Print 2017 Jan.
Personalised medicine aims to tailor medical decisions to the individual patient. A possible approach is to stratify patients according to the risk of adverse outcomes such as exacerbations in chronic obstructive pulmonary disease (COPD). Risk-stratified approaches are particularly attractive for drugs like inhaled corticosteroids or phosphodiesterase-4 inhibitors that reduce exacerbations but are associated with harms. However, it is currently not clear which models are best to predict exacerbations in patients with COPD. Therefore, our aim was to identify and critically appraise studies on models that predict exacerbations in COPD patients. Out of 1382 studies, 25 studies with 27 prediction models were included. The prediction models showed great heterogeneity in terms of number and type of predictors, time horizon, statistical methods and measures of prediction model performance. Only two out of 25 studies validated the developed model, and only one out of 27 models provided estimates of individual exacerbation risk, only three out of 27 prediction models used high-quality statistical approaches for model development and evaluation. Overall, none of the existing models fulfilled the requirements for risk-stratified treatment to personalise COPD care. A more harmonised approach to develop and validate high- quality prediction models is needed to move personalised COPD medicine forward.
个性化医疗旨在根据个体患者的情况量身定制医疗决策。一种可能的方法是根据不良结局的风险对患者进行分层，如慢性阻塞性肺疾病（COPD）急性加重。对于像吸入性糖皮质激素或磷酸二酯酶-4抑制剂这类能减少急性加重但伴有危害的药物，风险分层方法尤其具有吸引力。然而，目前尚不清楚哪种模型最适合预测COPD患者的急性加重。因此，我们的目的是识别并严格评估关于预测COPD患者急性加重模型的研究。在1382项研究中，纳入了25项研究中的27个预测模型。这些预测模型在预测因子的数量和类型、时间范围、统计方法以及预测模型性能的衡量标准方面存在很大异质性。25项研究中只有两项对所开发的模型进行了验证，27个模型中只有一个提供了个体急性加重风险的估计值，27个预测模型中只有三个使用了高质量的统计方法进行模型开发和评估。总体而言，现有的模型均未满足风险分层治疗以实现COPD护理个性化的要求。需要一种更加统一的方法来开发和验证高质量的预测模型，以推动COPD个性化医疗的发展。
