Abstract
INTRODUCTION: Multiple endocrine neoplasia type 1 (MEN1)-related neuroendocrine tumors (NETs) of the lung are mostly indolent, with a good prognosis. Nevertheless, cases of aggressive lung NET do occur, and therefore the management of individual patients is challenging.
AIM: To assess tumor growth and the survival of patients with MEN1-related lung NETs at long-term follow-up.
METHODS: The population-based Dutch MEN1 Study Group database (n = 446) was used to identify lung NETs by histopathological and radiological examinations. Tumor diameter was assessed. Linear mixed models and the Kaplan-Meier method were used for analyzing tumor growth and survival. Molecular analyses were performed on a lung NET showing particularly aggressive behavior.
RESULTS: In 102 patients (22.9% of the total MEN1 cohort), 164 lesions suspected of lung NETs were identified and followed for a median of 6.6 years. Tumor diameter increased 6.0% per year. The overall 15-year survival rate was 78.0% (95% confidence interval: 64.6-94.2%) without lung NET-related death. No prognostic factors for tumor growth or survival could be identified. A somatic c.3127A > G (p.Met1043Val) PIK3CA driver mutation was found in a case of rapid growing lung NET after 6 years of indolent disease, presumably explaining the sudden change in course.
CONCLUSION: MEN1-related lung NETs are slow growing and have a good prognosis. No accurate risk factors for tumor growth could be identified. Lung NET screening should therefore be based on well-informed, shared decision-making, balancing between the low absolute risk of an aggressive tumor in individuals and the potential harms of frequent thoracic imaging.
| Original language | English |
|---|---|
| Pages (from-to) | e1014-e1027 |
| Journal | The Journal of clinical endocrinology and metabolism |
| Volume | 106 |
| Issue number | 2 |
| Early online date | 2 Nov 2020 |
| DOIs | |
| Publication status | Published - 1 Feb 2021 |
Keywords
- lung NET
- multiple endocrine neoplasia type 1
- surveillance
- survival
- tumor growth
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