The Role of Malignancy Risk Scores in Assessing Cancer Risk in Pure Ground-Glass and Part-Solid Nodules

Aim: This study aimed to evaluate the effectiveness of commonly used malignancy risk prediction models in assessing the likelihood of malignancy in pure ground-glass opacities (pGGNs) and part solid pulmonary nodules (PSNs) among patients with solitary pulmonary nodules (SPN). Methods: Between January 2021 and June 2024, 75 patients undergoing the uniportal video-assisted thoracoscopic (U-VATS) segmentectomy due to SPNs were retrospectively reviewed. Of these, 32 patients undergoing segmentectomy for radiologically defined pGGN or PSNs were included in the study. Demographic data, smoking history, nodule characteristics, and surgical details were collected. Malignancy risk scores were calculated separately using the Mayo Clinic, Brock, Bayesian, and Herder models. These scores were then compared with the final histopathological results. Results: The mean age of the included patients was 62.89±10.53 years (range: 35–80), with a male to-female ratio of 17:15. The smoking prevalence was 50%, with a history of malignancy present in 8 patients and a family history of lung cancer in 3 patients. The prevalence of chronic immune mediated diseases was 43.8%. The mean radiological nodule size was 13.04±5.14 mm (range: 6–26 mm). Among the nodules, 59.4% (n=19) were pGGNs, and 40.6% (n=13) were PSNs. The median malignancy risk scores were 11.95% (IQR: 15.7) for the Mayo Clinic model, 9.77% (IQR: 18.15) for the Brock model, 13% (IQR: 36.25) for the Bayesian model, and 12.1% (IQR: 14.58) for Herder model. The overall malignancy rate was 93.8%, with invasive adenocarcinoma (37.5%) and adenocarcinoma in situ (28.1%) being the most common histopathological subtypes. The median chest tube removal time was 2 days (IQR: 1), and the median length of hospital stay was 3 days (IQR: 2). No postoperative mortality was observed. Conclusions: Our findings suggest that the widely used risk prediction models are insufficient in accurately identifying early-stage lung adenocarcinoma in patients with pGGN and PSNs. Incorporating additional patient-related factors, such as chronic immune-mediated conditions, into multivariate analyses may enhance the predictive accuracy of malignancy-risk assessments in SPN.