Percutaneous computed tomography-guided core needle biopsy can be used to histologically confirm the clinical features and long-term prognosis of pulmonary neuroendocrine neoplasms

Purpose We investigated the clinical features and prognosis outcomes of pulmonary neuroendocrine neoplasms (PNENs) which were histologically confirmed after percutaneous computed tomography-guided core needle biopsy (PCT-CNB). Materials and methods We retrospectively investigated 173 patients who had PNENs which were histologically confirmed after PCT-CNB; patients were split into low and intermediate-grade neuroendocrine tumor (LIGNET) (typical carcinoid (TC) and atypical carcinoid (AC)) and high-grade neuroendocrine carcinoma-tumor (HGNEC) groups. In this latter group, patients were further subdivided into large-cell neuroendocrine carcinoma (LCNEC), small-cell lung cancer (SCLC), and high-grade neuroendocrine carcinoma-not otherwise specified (HGNEC-NOS) groups. Complications after biopsy were recorded. We also assessed overall survival (OS) rates using Kaplan–Meier curves, with prognostic factors determined using univariate and multivariate analyses. Results Complications were mainly pneumothorax (22.5; 39/173 patients), chest tube placement (4.0; 7/173 patients), and pulmonary bleeding (33.5%; 58/173 procedures)—no patient mortality was recorded. Definitive diagnoses were ascribed to 102 SCLC, 10 LCNEC, 43 HGNEC-NOS, 7 TC, and 11 AC patients. The 1- and 3-year OS rates in the LIGNET group were 87.5% and 68.1%, respectively, and 59.2 and 20.9% in the HGNEC group, respectively these data were statistically significant ( P = 0.010). For SCLC, 1- and 3-year OS rates were 63.3 and 22.3%, 30.0 and 10.0% for LCNEC, and 53.3% and 20.1% for HGNEC-NOS, respectively ( P = 0.031). Independent prognostic factors for OS included disease type and distant metastasis. Conclusion PNENs may be pathologically diagnosed using PCT-CNB. While differential diagnoses between LCNEC and SCLC are problematic in some patients, a HGNEC-NOS diagnosis was ascribed and PCT-CNB samples were shown to predict NEN OS rates.