Prognostic thresholds of fluorine-18 fluorodeoxyglucose-positron emission tomography mean and maximum standardized uptake values for survival and nodal involvement in lung neuroendocrine neoplasms

Abstract

Abstract OBJECTIVES The mean standardized uptake value (SUVmean) and maximum standardized uptake value (SUVmax) on fluorine-18 fluorodeoxyglucose-positron emission tomography are prognostic biomarkers for survival and nodal involvement in non-small-cell lung cancer but their prognostic value in lung neuroendocrine neoplasms (NENs) remains unexplored. In this study, we aimed to examine whether they are also prognostic biomarkers for survival and nodal involvement in lung NENs. METHODS We retrospectively studied patients with typical carcinoid, atypical carcinoid or large cell neuroendocrine carcinoma who had been radically resected at our institution between 2008 and 2020. We measured SUVmean and SUVmax on all primary tumours and lymph nodes that were clinically and/or pathologically involved. We dichotomized the patients into groups of high or low SUVmean and SUVmax of the primary tumour using time-dependent receiver operating characteristic curves and compared their overall survival using Kaplan–Meier curves and Cox models. Lastly, we predicted the patients’ pathological nodal status with SUVmean and SUVmax of the lymph nodes using binomial logistic models. RESULTS The study included 245 patients. Patients died earlier if their SUVmean of the primary tumour exceeded 3.9 [hazard ratio 1.97, 95% confidence interval (CI) 1.27–3.04, P = 0.002] or SUVmax exceeded 5.3 (hazard ratio 1.85, 95% CI 1.20–2.87, P = 0.006). Likewise, patients had a higher risk of pathological nodal involvement if their SUVmean of the lymph nodes exceeded 3.3 (odds ratio 10.00, 95% CI 2.59–51.01, P = 0.002) or SUVmax exceeded 4.2 (odds ratio 4.00, 95% CI 1.20–14.65, P = 0.028). CONCLUSIONS The fluorine-18 fluorodeoxyglucose-positron emission tomography SUVmean and SUVmax are strong prognostic biomarkers for survival and nodal involvement in lung NENs and could be important guides for making treatment decisions.