OUTCOME AND THERAPEUTIC INTERVENTIONS IN RELAPSED AND REFRACTORY ATRT - THE EU-RHAB PERSPECTIVE

Neuro-Oncology(2022)

引用 2|浏览14
暂无评分
摘要
Abstract Currently an internationally accepted consensus treatment for relapsed/refractory ATRT is missing. Little is known about relapse patterns, prognostic factors and outcome. In a recently published cohort of 143 ATRTs from the EU-RHAB registry, progression on therapy or relapse occurred in 64% (n=91). Previously published strategies for treatment failure have been restricted to individual, mostly clinically guided, attempts or early phase trials with limited sample sizes. We present a cohort of 55 patients with relapsed/refractory ATRT identified between 2015 and 2021 (total ATRT recruited n=147). Median age was 19 months; in 27.3% (n=15) a germline mutation was identified. A total of 43/55 tumors were subgrouped [60.5% SHH (n=26), 14.0% MYC (n=6), 23.3% TYR (n=10), one patient with SHH+TYR]. Salvage therapy was applied to 83.6% (46/55). Sixty therapy attempts with 17 different regimens subclassified into conventional chemotherapy, epigenetic, targeted or metronomic therapy were applied to 40/55 patients. Median overall survival (OS) was 20±1.8 weeks following the first event, median time to progression was 11±1.8 weeks. 12 months OS was 23.1%. No significant differences in survival were noted between different molecular subgroups; neither was germline mutation in SMARCB1 prognostic. Patients <12 months (n=9;16.4%) had a significantly reduced OS compared to older patients. (9±6.0wks vs. 22±3.2wks, p<0.05) Those who received therapy according to metronomic approaches such as MEMMAT (8/55;14.5%) survived longer than patients treated with other regimens, including epigenetic and targeted therapy. (72±36.8wks vs. 25±6.2wks, p<0.05) Our data provide valuable insights into a vulnerable group of patients deserving evidence based clinical management and access to clinical trials of all phases. Prospectively we aim to merge the results with data from other, international cohorts to generate more robust and valuable results.
更多
查看译文
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