Woodfield Rebecca, Sudlow Cathie L M
Clinical Centre for Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom.
Clinical Centre for Brain Sciences, University of Edinburgh, Edinburgh, United Kingdom; UK Biobank, Adswood, Stockport, United Kingdom.
PLoS One. 2015 Sep 10;10(9):e0137538. doi: 10.1371/journal.pone.0137538. eCollection 2015.
We performed a systematic review of the accuracy of patient self-report of stroke to inform approaches to ascertaining and confirming stroke cases in large prospective studies.
We sought studies comparing patient self-report against a reference standard for stroke. We extracted data on survey method(s), response rates, participant characteristics, the reference standard used, and the positive predictive value (PPV) of self-report. Where possible we also calculated sensitivity, specificity, negative predictive value (NPV), and stroke prevalence. Study-level risk of bias was assessed using the Quality Assessment of Diagnostic Studies tool (QUADAS-2).
From >1500 identified articles, we included 17 studies. Most asked patients to report a lifetime history of stroke but a few limited recall time to ≤5 years. Some included questions for transient ischaemic attack (TIA) or stroke synonyms. No study was free of risk of bias in the QUADAS-2 assessment, the most frequent causes of bias being incomplete reference standard data, absence of blinding of adjudicators to self-report status, and participant response rates (<80%). PPV of self-report ranged from 22-87% (17 studies), sensitivity from 36-98% (10 studies), specificity from 96-99.6% (10 studies), and NPV from 88.2-99.9% (10 studies). PPV increased with stroke prevalence as expected. Among six studies with available relevant data, if confirmed TIAs were considered to be true rather than false positive strokes, PPV of self-report was >75% in all but one study. It was not possible to assess the influence of recall time or of the question(s) asked on PPV or sensitivity.
Characteristics of the study population strongly influence self-report accuracy. In population-based studies with low stroke prevalence, a large proportion of self-reported strokes may be false positives. Self-report is therefore unlikely to be helpful for identifying cases without subsequent confirmation, but may be useful for case ascertainment in combination with other data sources.
我们对患者自我报告中风的准确性进行了系统评价,以为大型前瞻性研究中确定和确认中风病例的方法提供依据。
我们查找了将患者自我报告与中风参考标准进行比较的研究。我们提取了有关调查方法、应答率、参与者特征、所使用的参考标准以及自我报告的阳性预测值(PPV)的数据。在可能的情况下,我们还计算了敏感性、特异性、阴性预测值(NPV)和中风患病率。使用诊断性研究质量评估工具(QUADAS-2)评估研究水平的偏倚风险。
从1500多篇已识别的文章中,我们纳入了17项研究。大多数研究要求患者报告中风的终生病史,但也有少数研究将回忆时间限制在≤5年。一些研究纳入了短暂性脑缺血发作(TIA)或中风同义词的问题。在QUADAS-2评估中,没有一项研究没有偏倚风险,最常见的偏倚原因是参考标准数据不完整、裁决者对自我报告状态未设盲以及参与者应答率(<80%)。自我报告的PPV范围为22%-87%(17项研究),敏感性范围为36%-98%(10项研究),特异性范围为96%-99.6%(10项研究),NPV范围为88.2%-99.9%(10项研究)。正如预期的那样,PPV随着中风患病率的增加而升高。在六项有可用相关数据的研究中,如果将已确认的TIA视为真正的中风而非假阳性中风,则除一项研究外,所有研究中自我报告的PPV均>75%。无法评估回忆时间或所提问题对PPV或敏感性的影响。
研究人群的特征强烈影响自我报告的准确性。在中风患病率较低的基于人群的研究中,很大一部分自我报告的中风可能是假阳性。因此,自我报告对于识别未经后续确认的病例可能没有帮助,但与其他数据源结合使用时可能有助于病例确定。