谷歌浏览器插件
订阅小程序
在清言上使用

Patient and tumor characteristics and their influence on early therapy persistence with letrozole in postmenopausal patients with early breast cancer.

Annals of Oncology(2018)

引用 29|浏览20
暂无评分
摘要
Background: Patients' compliance and persistence with endocrine treatment has a significant effect on the prognosis in early breast cancer (EBC). The purpose of this analysis was to identify possible reasons for non-persistence, defined as premature cessation of therapy, on the basis of patient and tumor characteristics in individuals receiving adjuvant treatment with letrozole. Patients and methods: The EvAluate-TM study is a prospective, multicenter, noninterventional study in which treatment with the aromatase inhibitor letrozole was evaluated in postmenopausal women with hormone receptor-positive EBC in the early therapy phase. Treatment persistence was evaluated at two pre-specified study visits after 6 and 12 months. As a measure of early therapy persistence the time from the start to the end of treatment (TTEOT) was analyzed. Cox regression analyses were carried out to identify patient characteristics and tumor characteristics predicting TTEOT. Results: Out of the total population of 3941 patients with EBC, 540 (13.7%) events involving treatment cessation unrelated to disease progression were observed. This was due to drug-related toxicity in the majority of cases (73.5%). Persistence rates were 92.2%, 86.9%, and 86.3% after 6, 12, and 15 months, respectively. The main factors influencing premature treatment discontinuation were older age [hazard ratio (HR) 1.02/year], comorbidities (HR 1.06 per comorbidity), low body mass index, and lower tumor grade (HR 0.85 per grade unit). Conclusion: These results support the view that older, multimorbid patients with low tumor grade and low body mass index are at the greatest risk for treatment discontinuation and might benefit from compliance and support programs.
更多
查看译文
关键词
breast cancer,compliance,adherence,endocrine treatment/therapy,aromatase inhibitor,persistence
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