Predicting antidepressant remission in late-life depression using polygenic risk scoring and machine learning models

使用多基因风险评分和机器学习模型预测晚年抑郁症的抗抑郁药物缓解

• 批准号: 410637
• 负责人: Mueller Daniel J
• 金额: $ 64.65万
• 依托单位: Centre for Addiction and Mental Health (Toronto)
• 依托单位国家: 加拿大
• 项目类别: Operating Grants
• 财政年份: 2019
• 资助国家: 加拿大
• 起止时间: 2019-09-01 至 2024-09-01
• 项目状态: 已结题
• 来源: https://webapps.cihr-irsc.gc.ca/decisions/p/project_details.html?applId=410637&lang=en
• 关键词: Antidepressants; Genetics; Late-Life Depression; Machine Learning; Pharmacogenetics; Polygenic Risk Scores; Predictive Modelling; Treatment Response

The absolute health care cost of depression currently equals $1.2 billion in Ontario alone. Treating older adults with the first onset of major depressive disorder (age 50 years or older, affecting up to 16% of older adults) results in a 30-50% increase i

目前仅在安大略省，抑郁症的绝对医疗费用就达到 12 亿加元。对首次出现重度抑郁症的老年人（年龄在 50 岁或以上，影响高达 16% 的老年人）进行治疗会导致患病率增加 30-50%