Abdulaziz Kasim E, Perry Jeffrey J, Yadav Krishan, Dowlatshahi Dar, Stiell Ian G, Wells George A, Taljaard Monica
Clinical Epidemiology Program, Ottawa Hospital Research Institute, Ottawa, Ontario, Canada.
School of Epidemiology and Public Health, Faculty of Medicine, University of Ottawa, Ottawa, Ontario, Canada.
Diagn Progn Res. 2022 May 19;6(1):9. doi: 10.1186/s41512-022-00123-z.
Clinical prediction models/scores help clinicians make optimal evidence-based decisions when caring for their patients. To critically appraise such prediction models for use in a clinical setting, essential information on the derivation and validation of the models needs to be transparently reported. In this systematic review, we assessed the quality of reporting of derivation and validation studies of prediction models for the prognosis of recurrent stroke in patients with transient ischemic attack or minor stroke.
MEDLINE and EMBASE databases were searched up to February 04, 2020. Studies reporting development or validation of multivariable prognostic models predicting recurrent stroke within 90 days in patients with TIA or minor stroke were included. Included studies were appraised for reporting quality and conduct using a select list of items from the Transparent Reporting of a Multivariable Prediction Model for Individual Prognosis or Diagnosis (TRIPOD) Statement.
After screening 7026 articles, 60 eligible articles were retained, consisting of 100 derivation and validation studies of 27 unique prediction models. Four models were newly derived while 23 were developed by validating and updating existing models. Of the 60 articles, 15 (25%) reported an informative title. Among the 100 derivation and validation studies, few reported whether assessment of the outcome (24%) and predictors (12%) was blinded. Similarly, sample size justifications (49%), description of methods for handling missing data (16.1%), and model calibration (5%) were seldom reported. Among the 96 validation studies, 17 (17.7%) clearly reported on similarity (in terms of setting, eligibility criteria, predictors, and outcomes) between the validation and the derivation datasets. Items with the highest prevalence of adherence were the source of data (99%), eligibility criteria (93%), measures of discrimination (81%) and study setting (65%).
The majority of derivation and validation studies for the prognosis of recurrent stroke in TIA and minor stroke patients suffer from poor reporting quality. We recommend that all prediction model derivation and validation studies follow the TRIPOD statement to improve transparency and promote uptake of more reliable prediction models in practice.
The protocol for this review was registered with PROSPERO (Registration number CRD42020201130 ).
临床预测模型/评分有助于临床医生在照顾患者时做出基于最佳证据的决策。为了严格评估此类预测模型在临床环境中的应用，需要透明地报告模型推导和验证的基本信息。在这项系统评价中，我们评估了短暂性脑缺血发作或轻度卒中患者复发性卒中预后预测模型的推导和验证研究的报告质量。
检索MEDLINE和EMBASE数据库至2020年2月4日。纳入报告多变量预后模型的开发或验证的研究，这些模型预测TIA或轻度卒中患者90天内的复发性卒中。使用来自个体预后或诊断多变量预测模型透明报告（TRIPOD）声明的选定项目清单，对纳入研究的报告质量和实施情况进行评估。
在筛选7026篇文章后，保留了60篇符合条件的文章，包括27个独特预测模型的100项推导和验证研究。4个模型是新推导的，23个是通过验证和更新现有模型开发的。在60篇文章中，15篇（25%）报告了信息丰富的标题。在100项推导和验证研究中，很少有研究报告结局评估（24%）和预测因素评估（12%）是否采用盲法。同样，样本量合理性（49%）、处理缺失数据的方法描述（16.1%）和模型校准（5%）很少被报告。在96项验证研究中，17项（17.7%）明确报告了验证数据集和推导数据集之间的相似性（在设置、纳入标准、预测因素和结局方面）。依从性最高的项目是数据来源（99%）、纳入标准（93%）、区分度测量（81%）和研究设置（65%）。
TIA和轻度卒中患者复发性卒中预后的大多数推导和验证研究报告质量较差。我们建议所有预测模型推导和验证研究遵循TRIPOD声明，以提高透明度并促进在实践中采用更可靠的预测模型。
本评价方案已在PROSPERO注册（注册号CRD42020201130）。
