Predictability and Utility of Contrast-Enhanced CT on Occult Lymph Node Metastasis for Patients with Clinical Stage IA-IIA Lung Adenocarcinoma: A Double-Center Study.

RATIONALE AND

OBJECTIVES

With the advantage of minimizing damage and preserving more functional lung tissue, limited surgery is considered depend on the lymph node (LN) involvement situation. However, occult lymph node metastasis (OLM) may be ignored by limited surgery and become a risk factor for local recurrence after surgical resection. The aim of this study was to assess the risk factors for OLM based on computed tomography enhanced image in patients with clinical lung adenocarcinoma (ADC).

MATERIALS AND

METHODS

From January 2016 to July 2022, 707 patients with clinical stage IA-IIA ADC underwent lobectomy with systematic LN dissection and were divided into training and validation group based on different institution. Univariate analysis followed by multivariable logistic regression were performed to estimate different risk factors of OLM. A predictive model was established with visual nomogram and external validation, and evaluated in terms of accuracy, sensitivity, specificity, and area under the receiver operating characteristic curve (AUC).

RESULTS

Fifty-nine patients were diagnosed with OLM (11.9%), and four independent predictors of LN involvement were identified: larger consolidation diameter (odds ratio [OR], 2.35, 95% confidence interval [CI]: 1.06, 5.22, p = 0.013), bronchovascular bundle thickening (OR, 1.99, 95% CI: 1.00, 3.95, p = 0.049), lobulation (OR, 2.92, 95% CI: 1.22, 6.99, p = 0.016) and obstructive change (OR, 1.69, 95% CI: 1.17, 6.16, p = 0.020). The model showed good calibration (Hosmer-Lemeshow goodness-of-fit, p = 0.816) with an AUC of 0.821 (95% CI: 0.775, 0.853). For the validation group, the AUC was 0.788 (95% CI: 0.732, 0.806).

CONCLUSION

Our predictive model can non-invasively assess the risk of OLM in patients with clinical stage IA-IIA ADC, enable surgeons perform an individualized prediction preoperatively, and assist the clinical decision-making procedure.