The Role of Malignancy Risk Scores in Assessing Cancer Risk in Pure Ground-Glass and Part-Solid Nodules
Öz
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.
Anahtar Kelimeler
Ground-glass nodule, risk prediction models, segmentectomy, subsolid nodule
Destekleyen Kurum
Yok.
Etik Beyan
Bu çalışma Ondokuz Mayıs Üniversitesi Etik Kurulu tarafından onaylanmıştır (Onay No: 2025/66 , tarih: 12 Şubat 2025).
Yazarların beyan edecekleri herhangi bir çıkar çatışması bulunmamaktadır.
Teşekkür
Bu çalışmanın bir versiyonu 2-3 Kasım 2024 tarihlerinde Konya'da düzenlenen Türk Toraks Derneği 2024 Güz Sempozyumu'nda sözlü bildiri olarak sunulmuştur.
Kaynakça
- 1. Saji H, Okada M, Tsuboi M, Nakajima R, Suzuki K, Aokage K, et al. Segmentectomy versus lobectomy in small-sized peripheral non-small-cell lung cancer (JCOG0802/WJOG4607L): a multicentre, open-label, phase 3, randomized, controlled, non-inferiority trial. Lancet. 2022;399(10335):1607-17.
- 2. Miyoshi T, Ito H, Wakabayashi M, Hashimoto T, Sekino Y, Suzuki K, et al. Risk factors for loss of pulmonary function after wedge resection for peripheral ground-glass opacity dominant lung cancer. Eur J Cardiothorac Surg. 2023;64(6).
- 3. Piskorski L, Debic M, von Stackelberg O, Schlamp K, Welzel L, Weinheimer O, et al. Malignancy risk stratification for pulmonary nodules: comparing a deep learning approach to multiparametric statistical models in different disease groups. Eur Radiol. 2025.
- 4. MacMahon H, Naidich DP, Goo JM, Lee KS, Leung ANC, Mayo JR, et al. Guidelines for Management of Incidental Pulmonary Nodules Detected on CT Images: From the Fleischner Society 2017. Radiology. 2017;284(1):228-43.
- 5. Zhong D, Sidorenkov G, Jacobs C, de Jong PA, Gietema HA, Stadhouders R, et al. Lung Nodule Management in Low-Dose CT Screening for Lung Cancer: Lessons from the NELSON Trial. Radiology. 2024;313(1):e240535.
- 6. Gould MK, Donington J, Lynch WR, Mazzone PJ, Midthun DE, Naidich DP, et al. Evaluation of individuals with pulmonary nodules: when is it lung cancer? Diagnosis and management of lung cancer, 3rd ed: American College of Chest Physicians evidence-based clinical practice guidelines. Chest. 2013;143(5 Suppl):e93S-e120S.
- 7. Baldwin DR, Callister ME, Graham R, Gleeson F. Pulmonary nodules again? The 2015 British Thoracic Society guidelines on the investigation and management of pulmonary nodules. Clin Radiol. 2016;71(1):18-22.
- 8. Heideman BE, Kammer MN, Paez R, Swanson T, Godfrey CM, Low SW, et al. The Lung Cancer Prediction Model "Stress Test": Assessment of Models' Performance in a High-Risk Prospective Pulmonary Nodule Cohort. CHEST Pulm. 2024;2(1): 100033.
- 9. White CS, Dharaiya E, Campbell E, Boroczky L. The Vancouver Lung Cancer Risk Prediction Model: Assessment by Using a Subset of the National Lung Screening Trial Cohort. Radiology. 2017;283(1):264-72.
- 10. Perandini S, Soardi GA, Motton M, Rossi A, Signorini M, Montemezzi S. Solid pulmonary nodule risk assessment and decision analysis: comparison of four prediction models in 285 cases. Eur Radiol. 2016;26(9):3071-6.