Diagnostic Performance of CT and Reverse Transcriptase Polymerase Chain Reaction for Coronavirus Disease 2019: A Meta-Analysis

Abstract

Background Recent studies have suggested that chest CT scans could be used as a primary screening or diagnostic tool for coronavirus disease 2019 (COVID-19) in epidemic areas. Purpose To perform a meta-analysis to evaluate diagnostic performance measures, including predictive values of chest CT and initial reverse transcriptase polymerase chain reaction (RT-PCR). Materials and Methods Medline and Embase were searched from January 1, 2020, to April 3, 2020, for studies on COVID-19 that reported the sensitivity, specificity, or both of CT scans, RT-PCR assays, or both. The pooled sensitivity and specificity were estimated by using random-effects models. The actual prevalence (ie, the proportion of confirmed patients among those tested) in eight countries was obtained from web sources, and the predictive values were calculated. Meta-regression was performed to reveal the effect of potential explanatory factors on the diagnostic performance measures. Results The pooled sensitivity was 94% (95% confidence interval [CI]: 91%, 96%; I2 = 95%) for chest CT and 89% (95% CI: 81%, 94%; I2 = 90%) for RT-PCR. The pooled specificity was 37% (95% CI: 26%, 50%; I2 = 83%) for chest CT. The prevalence of COVID-19 outside China ranged from 1.0% to 22.9%. For chest CT scans, the positive predictive value (PPV) ranged from 1.5% to 30.7%, and the negative predictive value (NPV) ranged from 95.4% to 99.8%. For RT-PCR, the PPV ranged from 47.3% to 96.4%, whereas the NPV ranged from 96.8% to 99.9%. The sensitivity of CT was affected by the distribution of disease severity, the proportion of patients with comorbidities, and the proportion of asymptomatic patients (all P < .05). The sensitivity of RT-PCR was negatively associated with the proportion of elderly patients (P = .01). Conclusion Outside of China where there is a low prevalence of coronavirus disease 2019 (range, 1%-22.9%), chest CT screening of patients with suspected disease had low positive predictive value (range, 1.5%-30.7%). © RSNA, 2020 Online supplemental material is available for this article.

Figures

Figure 1:

PRISMA flow diagram of the study selection process. CT = computed tomography; PRISMA = Preferred Reporting Items for Systematic Reviews and Metaanalyses; T-PCR = reverse transcriptase-polymerase chain reaction; WHO = World Health Organization.

Figure 2:

Grouped bar charts for risk of bias and concerns regarding the applicability of the 68 included studies using QUADAS-2. QUADAS-2 = Quality Assessment of Diagnostic Accuracy Studies-2.

Figure 3:

Forest plots of pooled sensitivity of (a) chest CT and (b) RT-PCR and pooled specificity of (c) chest CT. Univariate analyses were performed for sensitivity and specificity, respectively. CT = computed tomography; RT-PCR = reverse transcriptase-polymerase chain reaction.

Figure 4:

Estimated positive predictive value and negative predictive value of (a) chest CT and (b) RT-PCR. The solid line indicates the positive predictive value, and the dotted line denotes the negative predictive value. The red dots indicate the predictive values for eight different countries and China (the right-most point; prevalence, 39%). CT = computed tomography; RT-PCR = reverse transcriptase-polymerase chain reaction.

Figure 5:

Sensitivity analysis for the chest CT using studies with repeated RT-PCR assays as the reference standard. Forest plots of (a) pooled sensitivity and (b) pooled specificity. RTPCR = reverse transcriptase-polymerase chain reaction.

Figure 6:

Funnel plots. The likelihood of publication bias was low for the studies on chest CT scans and RT-PCR. CT = computed tomography; RT-PCR = reverse transcriptase-polymerase chain reaction.