Accuracy of FDG-PET to diagnose lung cancer in areas with infectious lung disease: a meta-analysis

Abstract

Importance: Positron emission tomography (PET) combined with fludeoxyglucose F 18 (FDG) is recommended for the noninvasive diagnosis of pulmonary nodules suspicious for lung cancer. In populations with endemic infectious lung disease, FDG-PET may not accurately identify malignant lesions.

Objectives: To estimate the diagnostic accuracy of FDG-PET for pulmonary nodules suspicious for lung cancer in regions where infectious lung disease is endemic and compare the test accuracy in regions where infectious lung disease is rare.

Data sources and study selection: Databases of MEDLINE, EMBASE, and the Web of Science were searched from October 1, 2000, through April 28, 2014. Articles reporting information sufficient to calculate sensitivity and specificity of FDG-PET to diagnose lung cancer were included. Only studies that enrolled more than 10 participants with benign and malignant lesions were included. Database searches yielded 1923 articles, of which 257 were assessed for eligibility. Seventy studies were included in the analysis. Studies reported on a total of 8511 nodules; 5105 (60%) were malignant.

Data extraction and synthesis: Abstracts meeting eligibility criteria were collected by a research librarian and reviewed by 2 independent reviewers. Hierarchical summary receiver operating characteristic curves were constructed. A random-effects logistic regression model was used to summarize and assess the effect of endemic infectious lung disease on test performance.

Main outcome and measures: The sensitivity and specificity for FDG-PET test performance.

Results: Heterogeneity for sensitivity (I2 = 87%) and specificity (I2 = 82%) was observed across studies. The pooled (unadjusted) sensitivity was 89% (95% CI, 86%-91%) and specificity was 75% (95% CI, 71%-79%). There was a 16% lower average adjusted specificity in regions with endemic infectious lung disease (61% [95% CI, 49%-72%]) compared with nonendemic regions (77% [95% CI, 73%-80%]). Lower specificity was observed when the analysis was limited to rigorously conducted and well-controlled studies. In general, sensitivity did not change appreciably by endemic infection status, even after adjusting for relevant factors.

Conclusions and relevance: The accuracy of FDG-PET for diagnosing lung nodules was extremely heterogeneous. Use of FDG-PET combined with computed tomography was less specific in diagnosing malignancy in populations with endemic infectious lung disease compared with nonendemic regions. These data do not support the use of FDG-PET to diagnose lung cancer in endemic regions unless an institution achieves test performance accuracy similar to that found in nonendemic regions.

Figure 1. Literature search PRISMA consort diagram

PRISMA diagram of systematic review of eligible studies (Preferred Reporting Items for Systematic reviews and Meta-Analyses). The same study could be excluded for multiple reasons.

Figure 2. Individual study estimates of sensitivity and specificity with average adjusted results

Forest plot reporting individual study sensitivity and specificity. Endemic infectious lung disease with are in blue and nonendemic studies are in black. Average adjusted results for endemic studies (n=10), non-endemic studies (n=60) and all studies combined (n=70) sensitivity and specificity are in red. Error bars are 95% confidence intervals for each study's corresponding test characteristic.

Figure 3. Performance by endemic status for 70 studies

Hierarchical Summary Receiver Operator (HSROC) Curve with operating points for endemic and nonendemic infectious lung disease studies and 95% Confidence and Prediction Intervals for those operating points. The horizontal box and whiskers plot represents the distribution of study specificity, and the vertical box and whiskers plot represents the distribution of study sensitivity. The box limits are the closest data point to the interquartile range of 25 and 75% with the bar being the median (50%). Error bar whiskers represent the data point closest to 1.5 times the interquartile range and the dots outside the whiskers represent outlier study values.