Predicting occult lymph node metastasis by nomogram in patients with lung adenocarcinoma ≤2 cm.

ABSTRACT

Background: Previous researches had not proposed any prediction models for occult lymph node metastasis (OLNM). Considering the occurrence of OLNM and the importance of OLNM management, we aimed to develop a nomogram to predict OLNM of patients with lung adenocarcinoma ≤2 cm. Methods: Characteristics of patients with lung adenocarcinoma of ≤2 cm diameter at the Peking Union Medical College Hospital were retrospectively reviewed. Univariate and multivariate logistic regressions were performed. A nomogram model was developed. The concordance index (C-index) and calibration and decision curves were used to evaluate the predictive ability. Results: A total of 473 patients were enrolled, with an OLNM incidence of 7.4%. Four factors were selected as risk factors. The model had a C-index of 0.932. Calibration and decision curves were determined. Conclusion: Patients with pure ground-glass opacity (pGGO) or noninvasive adenocarcinoma have significantly lower risk of OLNM. SUVmax, CEA, micropapillary and solid component were identified as independent risk factors. The nomogram model was effective in predicting OLNM preoperatively.

Lay abstract Lung cancer was once the leading cause of death among tumors. Today, as routine examination has become more common, the incidence of lung cancers ≤2 cm diameter has been increasing. Much research had explored treatment for these patients. Lobectomy and lymph node dissection in particular were recommended. Furthermore, lymph node dissection was strongly recommended for lymph-node-positive patients. During treatment, occult lymph node metastasis (OLNM) had been observed in some cases. And OLNM referred to a postoperative positive pathological result among preoperative imaging-negative cases. The study was designed to establish a model for predicting OLNM. In a cohort of 473 patients, we found certain risk factors for OLNM and established a predictive model. Relevant findings were shown in the 'Conclusion' section.