Article Abstract

Multidisciplinary treatment of thymic neuroendocrine tumors: surgery remains a key component

Authors: Erin M. Corsini, Kyle G. Mitchell, Eric L. Sceusi, Reza J. Mehran, David C. Rice, Boris Sepesi, Garrett L. Walsh, Stephen G. Swisher, Jack A. Roth, Ara A. Vaporciyan, Wayne L. Hofstetter, Mara B. Antonoff

Abstract

Background: Thymic neuroendocrine tumors (NETs) are rare malignancies often treated in a multidisciplinary fashion. However, evidence for adjunctive therapy is limited, and predictors of survival and recurrence are not well established.
Methods: Patients treated for thymic NETs at a single center from 1975 to 2018 were reviewed. Variables collected pertained to tumor factors, stage, and treatments, including surgery. Univariate and multivariate regression analyses were used to determine predictors of overall survival (OS) and recurrence.
Results: We identified treated 49 patients, among whom 36 (73%) were male with a median age of 46 years. Surgical resection was pursued in 41 (84%) patients, and chemotherapy and radiation therapy were used in 27 (55%) and 21 (43%) instances as either neoadjuvant, adjuvant, or definitive therapy. Median tumor size was 6.5 centimeters and most tumors were intermediate-grade. During a median follow-up time of 60.8 months following surgical resection, disease recurrence was observed in 29 (71%) patients and median survival time was 83.7 months. In Kaplan-Meier analysis for survival, surgical resection was associated with a longer survival time (P=0.002), while receipt of neoadjuvant therapy was associated with poorer survival. Larger tumor size was associated with recurrence following resection (P=0.047).
Conclusions: Thymic NETs represent a heterogeneous disease with variable survival. While we are unable to report clear evidence that supports the use of adjunctive therapies, surgery is important to survival. Additionally, it is likely that those receiving induction chemotherapy represent a unique cohort with advanced or aggressive disease. Among surgical candidates, tumor size predicts disease recurrence.