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诊断试验的统计学评估:儿科外科医生入门指南

Statistical evaluation of diagnostic tests: A primer for pediatric surgeons.

作者信息

Staffa Steven J, Zurakowski David

机构信息

Department of Surgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.

Department of Surgery, Boston Children's Hospital, Harvard Medical School, Boston, MA, USA.

出版信息

J Pediatr Surg. 2019 Apr;54(4):799-804. doi: 10.1016/j.jpedsurg.2018.06.010. Epub 2018 Jun 18.

DOI:10.1016/j.jpedsurg.2018.06.010
PMID:29980347
Abstract

BACKGROUND/PURPOSE: Diagnostic tests are of paramount importance for informing decision making in the surgical setting. Certain statistical methods are necessary to properly analyze data for diagnostic or prognostic tests involving biomarkers and risk factor data. Our goal is to provide a useful primer for the surgical researcher when performing a diagnostic research study in order to best analyze their data.

METHODS

We present the key concepts and statistics for diagnostic tests and receiver operating characteristic (ROC) curve analysis, and we illustrate each with hypothetical surgery research examples. We use hypothetical data regarding CT imaging and WBC count in their diagnostic ability in predicting acute appendicitis, an extremely common surgical condition, while reviewing the statistical concepts of sensitivity, specificity, positive and negative predictive value, positive and negative likelihood ratio, relative risk, odds ratio, and ROC curves. Then we will consider a hypothetical a risk factor analysis on 30-day readmission to illustrate how multiple predictors can be combined.

CONCLUSIONS

The statistical concepts presented are useful to the pediatric surgeon researcher in assessing the ability of diagnostic tests, which will translate into decision making and patient management implications in the clinical setting.

TYPE OF STUDY

Review Article LEVEL OF EVIDENCE: N/A.

摘要

背景/目的:诊断测试对于指导外科手术决策至关重要。对于涉及生物标志物和风险因素数据的诊断或预后测试,需要某些统计方法来正确分析数据。我们的目标是为外科研究人员在进行诊断性研究时提供一份有用的入门指南,以便他们能最好地分析数据。

方法

我们介绍诊断测试和受试者操作特征(ROC)曲线分析的关键概念和统计方法,并用假设的外科研究实例进行说明。在回顾敏感性、特异性、阳性和阴性预测值、阳性和阴性似然比、相对风险、比值比和ROC曲线等统计概念时,我们使用关于CT成像和白细胞计数在预测急性阑尾炎(一种极其常见的外科病症)方面的诊断能力的假设数据。然后我们将考虑一个关于30天再入院的假设风险因素分析,以说明如何将多个预测因素结合起来。

结论

所介绍的统计概念对外科儿科研究人员评估诊断测试的能力很有用,这将转化为临床环境中的决策制定和患者管理方面的应用。

研究类型

综述文章 证据水平:无。

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