To evaluate the risk factors of malignant solitary pulmonary nodules (SPNs).

A literature search was conducted was performed using the Chinese CNKI, VIP, Wanfang, PubMed, and Embase databases to identify studies on the prediction model for differentiating benign and malignant SPNs, up to December 2018 A literature search was conducted using the Chinese CNKI, VIP, Wanfang, PubMed, and Embase databases to identify studies on the prediction model for differentiating benign and malignant SPNs, up to December 2018. The meta-analysis was performed using the Stata 15 software. The various factors were analyzed using a fixed- or random-effect model, pooled odds ratio (OR), and 95% confidence interval (CI). A sensitivity analysis was used to evaluate the influence of each study on the strength and stability of the meta-analysis results. The Begg rank correlation test was conducted to assess publication bias.

Eighteen studies met our inclusion criteria. The meta-analysis revealed that 19 factors, including 4 demographic characteristic-related factors (patient age, family history of cancer, and histories of cancer and smoking), 10 imaging characteristic-related factors (spiculation, SPN diameter, lobulation, calcification, ground-glass nodule, clear boundary, obscure boundary, pleural indentation sign, short spiculation, and SUVmax), and 1 biomarker (CYFRA21-1; all P<0.05), influenced the development of malignant SPN. The sensitivity analysis revealed that the study was stable and reliable, and no publication biases for all the variables. Age, spiculation, SPN diameter, and lobulation were chosen as prediction models in ≥9 studies (50%), and the other factors only existed in <30% studies.

Numerous factors can affect the development of malignant SPNs, with age, spiculation, SPN diameter, and lobulation being the main influencing factors.

Meta-analysis; Solitary pulmonary nodule; Pulmonary nodule; Lung cancer; Prediction model