Division of Applied Health Sciences, University of Aberdeen, Foresterhill, Aberdeen, UK.
Department of Research, Section of Biostatistics, Stavanger University Hospital, Stavanger, Norway.
Mov Disord. 2018 Jan;33(1):108-116. doi: 10.1002/mds.27177. Epub 2017 Oct 4.
The objective of this study was to develop valid prognostic models to predict mortality, dependency, and "death or dependency" for use in newly diagnosed Parkinson's disease (PD).
The models were developed in the Parkinsonism Incidence in North-East Scotland study (UK, 198 patients) and validated in the ParkWest study (Norway, 192 patients), cohorts that attempted to identify and follow-up all new PD cases in the study area. Dependency was defined using the Schwab & England scale. We selected variables measured at time of diagnosis to include in the models. Internal validation and external validation were performed by calculating C-statistics (discrimination) and plotting observed versus predicted risk in quantiles of predicted risk (calibration).
Older age, male sex, increased severity of axial features, and Charlson comorbidity index were independent prognostic factors in the mortality model. Increasing age, higher smoking history, increased severity of axial features, and lower MMSE score were independent predictors in the models of dependency and "death or dependency." Each model had very good internal calibration and very good or good discrimination (internal and external C-statistics for the models were 0.73-0.75 and 0.68-0.78, respectively). Although each model clearly separated patients into groups according to risk, they tended to overestimate risk in ParkWest. The models were recalibrated to the baseline risk in the ParkWest study and then calibrated well in this cohort.
We have developed prognostic models for predicting medium-term risk of important clinical outcomes in newly diagnosed PD. These models have validity for use for stratification of randomization, confounder adjustment, and case-mix correction, but they are inadequate for individualized prognostication. © 2017. The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.
本研究旨在开发有效的预后模型,以预测新发帕金森病(PD)患者的死亡率、依赖程度和“死亡或依赖”。
该模型在帕金森症在英国东北苏格兰的研究(英国,198 例患者)中建立,并在 ParkWest 研究(挪威,192 例患者)中进行验证,这两个研究队列都试图在研究区域内发现并跟踪所有新发 PD 病例。依赖程度使用 Schwab & England 量表进行定义。我们选择在诊断时测量的变量纳入模型。通过计算 C 统计量(区分度)和绘制观察到的风险与预测风险的分位数(校准)来进行内部和外部验证。
年龄较大、男性、轴向特征严重程度增加以及 Charlson 合并症指数是死亡率模型的独立预后因素。年龄增长、吸烟史增加、轴向特征严重程度增加和 MMSE 评分降低是依赖和“死亡或依赖”模型的独立预测因素。每个模型的内部校准都非常好,且具有很好或良好的区分度(内部和外部的模型 C 统计量分别为 0.73-0.75 和 0.68-0.78)。虽然每个模型都根据风险清楚地将患者分组,但在 ParkWest 中,它们往往高估了风险。对模型进行了重新校准以适应 ParkWest 研究中的基线风险,然后在该队列中进行了很好的校准。
我们已经开发了用于预测新发 PD 患者重要临床结局的中期风险的预后模型。这些模型可用于随机分组分层、混杂因素调整和病例组合校正,但不适合个体化预后预测。