Optimising Outcomes in Chronic Myeloid Leukaemia Through Rational Drug Selection Using Predictive Assay Results and Maximising Treatment Free Remissions

利用预测分析结果合理选择药物，优化慢性粒细胞白血病的治疗效果，并最大限度地提高无治疗缓解率

• 批准号: nhmrc : GNT1146253
• 负责人: Dr David Yeung
• 金额: $ 18.94万
• 依托单位国家: 澳大利亚
• 项目类别: Early Career Fellowships
• 财政年份: 2018
• 资助国家: 澳大利亚
• 起止时间: 2018-01-01 至 无数据
• 项目状态: 已结题
• 来源: https://researchdata.edu.au/optimising-outcomes-chronic-free-remissions/1348747
• 关键词: Optimising; Outcomes; Chronic; Myeloid; Leukaemia

Although outcomes in chronic myeloid leukaemia are generally excellent, a number of important questions remain. In this grant, we propose to i) personalise the selection of frontline treatment for newly diagnosed patients, using biomarkers which can predict treatment response; ii) improve the probability of cure in patients aiming to stop their treatment, and iii) use ultra-sensitive molecular tests for disease detection to predict risk of disease relapse.

虽然慢性粒细胞白血病的预后一般都很好，但仍存在一些重要的问题。在这项拨款中，我们建议i）使用可以预测治疗反应的生物标志物，为新诊断患者个性化选择一线治疗; ii）提高旨在停止治疗的患者的治愈概率，以及iii）使用超敏感的分子检测进行疾病检测，以预测疾病复发的风险。