BACKGROUND: Computed tomography (CT)-based spiculated sign is a risk factor for malignancy in patients with lung nodules (LNs). The present meta-analysis aimed to evaluate the diagnostic utility of CT-based spiculated sign as a means of differentiating between malignant and benign LNs. METHODS: PubMed, Cochrane Library and Embase were reviewed from January 2000 to March 2020 for eligible studies. Stata v12.0 was used to conduct this meta-analysis. RESULTS: We identified 19 retrospective studies for inclusion in this meta-analysis. These studies compiled data pertaining to 8549 LNs (5547 malignant and 3003 benign). Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratios (DOR) were 0.51 (95% CI: 0.36-0.65), 0.84 (95% CI: 0.74-0.91), 3.15 (95% CI: 2.34-4.23), 0.59 (95% CI: 0.47-0.73) and 5.36 (95% CI: 3.93-7.31), respectively. The area under curve (AUC) was 0.76. Significant heterogeneity was detected among these studies with respect to sensitivity (I2 = 98.4%, P = .00), specificity (I2 = 95.8%, P = .00), PLR (I2 = 78.9%, P = .00), NLR (I2 = 99.3%, P = .00) and DOR (I2 = 100%, P = .00). A meta-regression analysis revealed that the country in which a study was conducted (China vs Not China) had a strong influence on reported sensitivity and specificity. No significant publication bias was detected via Deeks' funnel plot asymmetry test (P = .191). CONCLUSIONS: CT-based spiculated sign can achieve moderate diagnostic performance as a means of differentiating between malignant and benign LNs.
BACKGROUND: Computed tomography (CT)-based spiculated sign is a risk factor for malignancy in patients with lung nodules (LNs). The present meta-analysis aimed to evaluate the diagnostic utility of CT-based spiculated sign as a means of differentiating between malignant and benign LNs. METHODS: PubMed, Cochrane Library and Embase were reviewed from January 2000 to March 2020 for eligible studies. Stata v12.0 was used to conduct this meta-analysis. RESULTS: We identified 19 retrospective studies for inclusion in this meta-analysis. These studies compiled data pertaining to 8549 LNs (5547 malignant and 3003 benign). Pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR) and diagnostic odds ratios (DOR) were 0.51 (95% CI: 0.36-0.65), 0.84 (95% CI: 0.74-0.91), 3.15 (95% CI: 2.34-4.23), 0.59 (95% CI: 0.47-0.73) and 5.36 (95% CI: 3.93-7.31), respectively. The area under curve (AUC) was 0.76. Significant heterogeneity was detected among these studies with respect to sensitivity (I2 = 98.4%, P = .00), specificity (I2 = 95.8%, P = .00), PLR (I2 = 78.9%, P = .00), NLR (I2 = 99.3%, P = .00) and DOR (I2 = 100%, P = .00). A meta-regression analysis revealed that the country in which a study was conducted (China vs Not China) had a strong influence on reported sensitivity and specificity. No significant publication bias was detected via Deeks' funnel plot asymmetry test (P = .191). CONCLUSIONS: CT-based spiculated sign can achieve moderate diagnostic performance as a means of differentiating between malignant and benign LNs.