Role of Gut Microbiome in Cancer Therapy
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- Mayo Clinic
- 入组人数
- 3,000
- 试验地点
- 3
- 主要终点
- Associations between microbial community abundances and clinical outcomes
研究概览
简要总结
This study examines how gut microbiome can affect cancer therapy in cancer patients undergoing cancer therapy or stem cell transplant. The human microbiome affects the way some cancer drugs are metabolized in the human body. Information from this study may help doctors improve the way cancer treatment is delivered, and increase its effectiveness and success.
详细描述
PRIMARY OBJECTIVE:
I. To correlate gut microbiome with specific cancer diagnoses and the clinical response (efficacy), and adverse effects of cancer therapy (single or multiple) and stem cell transplant.
OUTLINE:
Patients undergo collection of blood and stool samples and have their medical records reviewed.
研究设计
- 研究类型
- Observational
- 观察模型
- Cohort
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 99 Years（Adult, Older Adult）
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- •Age 18-99
- •Diagnosis of cancer and undergoing cancer therapy or scheduled to start cancer therapy or undergoing stem cell transplant for any hematological condition
排除标准
- •Unable to provide informed consent
- •Vulnerable adults
研究组 & 干预措施
Observational (biospecimen collection, medical record review)
Patients undergo collection of blood and stool samples and have their medical records reviewed.
干预措施: Biospecimen Collection (Procedure)
Observational (biospecimen collection, medical record review)
Patients undergo collection of blood and stool samples and have their medical records reviewed.
干预措施: Electronic Health Record Review (Other)
结局指标
主要结局
Associations between microbial community abundances and clinical outcomes
时间窗: Through study completion, average of 1 year
Will use a linear multivariate regression model specifically developed for microbiome data (MaAsLin, Multivariate microbial Association by Linear models.
Gut microbiome associations with cancer diagnoses
时间窗: Through study completion, average of 1 year
Will be done using Shogun pipeline for metagenomics data followed by analysis using Quantitative Insights Into Microbial Ecology (QIIME) 2.0.
次要结局
未报告次要终点