CT扫描在第一波COVID-19大流行中对癌症患者的作用探讨

Sylvain Bourdoncle , Thomas Eche , Jeremy McGale , Kevin Yiu , Ephraïm Partouche , Randy Yeh , Samy Ammari , Hervé Rousseau , Laurent Dercle , Fatima-Zohra Mokrane
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引用次数: 3

摘要

在当前的COVID-19大流行中,我们进行了这项系统综述,以确定医学成像的作用,特别强调计算机断层扫描(CT)在指导肿瘤患者的护理和管理方面的作用。材料和方法研究选择集中于2020年2月1日至2020年4月23日的文章。删除不相关文章后,所有少于5例患者的系统或非系统评价、评论、通信、社论、指南、meta分析和病例报告也被排除。对符合条件的出版物的全文文章进行审查,以选择所有基于成像的出版物,并报告每个出版物是否存在肿瘤人群。两位独立审稿人收集了以下信息:(1)一般出版数据;(2)研究设计特点;(3)人口学、临床和病理变量,如有可能,包括癌症患者的百分比;(4)影像性能。采用随机效应模型将胸部CT (C-CT)的敏感性和特异性分别汇总。C-CT的阳性预测值(PPV)和阴性预测值(NPV)作为一种测试估计了广泛的疾病患病率。结果共审阅了106篇文献。其中,96个被确定具有可提取的数据,用于2乘2的CT性能列联表。最终,53项研究(其中6项使用了两个不同的人群)被纳入诊断准确性分析(N = 59)。我们纳入了53项研究,共11,352例患者,其敏感性(95CI)为0.886 (0.880;0.894),但特异性较低,93%(55/59)的病例特异性≤0.5。在106项研究中,只有7项研究纳入了肿瘤患者,并被纳入C-CT表现的最终分析。在这些研究中,癌症患者的百分比为0.3%(34/11352例),低于全球癌症患病率。在所有这些研究中,只有1项(0.9%,1/106)报告了特定癌症患者队列的表现,但仅报告了真阳性。令人担忧的是,目前缺乏涉及肿瘤患者的COVID-19研究,这表明确实需要进一步调查和评估不同医学成像方式在这一特定患者群体中的表现。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Investigating of the role of CT scan for cancer patients during the first wave of COVID-19 pandemic

Introduction

Amidst this current COVID-19 pandemic, we undertook this systematic review to determine the role of medical imaging, with a special emphasis on computed tomography (CT), on guiding the care and management of oncologic patients.

Material and Methods

Study selection focused on articles from 01/02/2020 to 04/23/2020. After removal of irrelevant articles, all systematic or non-systematic reviews, comments, correspondence, editorials, guidelines and meta-analysis and case reports with less than 5 patients were also excluded. Full-text articles of eligible publications were reviewed to select all imaging-based publications, and the existence or not of an oncologic population was reported for each publication. Two independent reviewers collected the following information: ( 1) General publication data; (2) Study design characteristics; (3) Demographic, clinical and pathological variables with percentage of cancer patients if available; (4) Imaging performances. The sensitivity and specificity of chest CT (C-CT) were pooled separately using a random-effects model. The positive predictive value (PPV) and negative predictive value (NPV) of C-CT as a test was estimated for a wide range of disease prevalence rates.

Results

A total of 106 publications were fully reviewed. Among them, 96 were identified to have extractable data for a two-by-two contingency table for CT performance. At the end, 53 studies (including 6 that used two different populations) were included in diagnosis accuracy analysis (N = 59). We identified 53 studies totaling 11,352 patients for whom the sensitivity (95CI) was 0.886 (0.880; 0.894), while specificity remained low: in 93% of cases (55/59), specificity was ≤ 0.5. Among all the 106 reviewed studies, only 7 studies included oncologic patients and were included in the final analysis for C-CT performances. The percentage of patients with cancer in these studies was 0.3% (34/11352 patients), lower than the global prevalence of cancer. Among all these studies, only 1 (0.9%, 1/106) reported performance specifically in a cohort of cancer patients, but it however only reported true positives.

Discussion

There is a concerning lack of COVID-19 studies involving oncologic patients, showing there is a real need for further investigation and evaluation of the performance of the different medical imaging modalities in this specific patient population.

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