Natural history of non-functioning pituitary microadenomas: results from the UK non-functioning pituitary adenoma consortium

Endocrine Abstracts(2023)

引用 1|浏览13
暂无评分
摘要
Objective The optimal approach to the surveillance of non-functioning pituitary microadenomas (micro-NFPAs) is not clearly established. Our aim was to generate evidence on the natural history of micro-NFPAs to support patient care. Design Multi-centre, retrospective, cohort study involving 23 endocrine departments (UK NFPA consortium). Methods Clinical, imaging, and hormonal data of micro-NFPA cases between January, 1, 2008 and December, 21, 2021 were analysed. Results Data for 459 patients were retrieved [median age at detection 44 years (IQR 31-57)-152 males/307 females]. Four hundred and nineteen patients had more than two magnetic resonance imagings (MRIs) [median imaging monitoring 3.5 years (IQR 1.71-6.1)]. One case developed apoplexy. Cumulative probability of micro-NFPA growth was 7.8% (95% CI, 4.9%-8.1%) and 14.5% (95% CI, 10.2%-18.8%) at 3 and 5 years, respectively, and of reduction 14.1% (95% CI, 10.4%-17.8%) and 21.3% (95% CI, 16.4%-26.2%) at 3 and 5 years, respectively. Median tumour enlargement was 2 mm (IQR 1-3) and 49% of micro-NFPAs that grew became macroadenomas (nearly all >5 mm at detection). Eight (1.9%) patients received surgery (only one had visual compromise with surgery required >3 years after micro-NFPA detection). Sex, age, and size at baseline were not predictors of enlargement/reduction. At the time of detection, 7.2%, 1.7%, and 1.5% patients had secondary hypogonadism, hypothyroidism, and hypoadrenalism, respectively. Two (0.6%) developed hypopituitarism during follow-up (after progression to macroadenoma). Conclusions Probability of micro-NFPA growth is low, and the development of new hypopituitarism is rare. Delaying the first follow-up MRI to 3 years and avoiding hormonal re-evaluation in the absence of tumour growth or clinical manifestations is a safe approach for micro-NFPA surveillance.
更多
查看译文
关键词
non-functioning,non-functioning
AI 理解论文
溯源树
样例
生成溯源树,研究论文发展脉络
Chat Paper
正在生成论文摘要