UCSD Profile Related Evidence Determining Individualized Cancer Therapy (UCSD PREDICT)
概览
- 阶段
- 不适用
- 干预措施
- 未指定
- 疾病 / 适应症
- Cancer
- 发起方
- Shu Mei Kato
- 入组人数
- 10000
- 试验地点
- 3
- 主要终点
- Comparison of Tumor Biomarker Profiling to Treatment Outcome
- 状态
- 招募中
- 最后更新
- 上个月
概览
简要总结
The purpose of this study is to learn more about personalized cancer therapy including response to treatment and side effects. Information about the tests and treatments a person received, or will receive, for their cancer will be collected from medical records to help the researchers determine whether or not patients respond better when their physicians choose to treat them according to the genetic makeup of their tumor. Optional research tests may be performed on tissue, body cavity fluid, blood or urine provided, discarded biological samples taken during routine care that would normally be disposed of and not saved, or on blood samples collected for this study. These research tests will be used to create a "profile" of the collected specimens which will describe unique characteristics about the genes involved in a person's cancer. The tests will also help researchers look for biomarkers that may help predict how people respond to treatment.
详细描述
This is a correlative study of personalized medicine with retrospective and prospective components. Patient medical records will be examined for results of molecular profiling obtained through standard of care testing to help understand, in a descriptive fashion, how well molecular testing might predict response to therapy. Patient outcome parameters including, but not limited to, tumor response, time to treatment failure, patient survival, and toxicity will be analyzed, as well as pharmacodynamic (PD) and pharmacokinetic (PK) data when available. This study will also include optional research-related testing of tissue, blood, or urine specimens via a variety of simple or advanced techniques such as molecular, proteomic, and metabolic analyses for biomarker discovery or for PK and PD parameters. These specimens will be obtained from clinical specimens archived by UCSD Health System Pathology or from specimens collected via an existing IRB-approved protocol, discarded specimens, or from specimens collected for this protocol.
研究者
Shu Mei Kato
Associate Clinical Professor of Medicine
University of California, San Diego
入排标准
入选标准
- •Must be willing to provide informed consent, parent permission, or assent
排除标准
- •Subjects unable to give informed consent, parent permission, or assent
结局指标
主要结局
Comparison of Tumor Biomarker Profiling to Treatment Outcome
时间窗: 4 years
Tumor molecular profiles will be correlated to treatment outcome, assessed by measures including the response rate, the rate of stable disease (SD)\>6months/partial response (PR)/complete response (CR), progression-free survival (PFS), PFS ratio (comparison of the PFS used after molecular profiling to PFS on prior treatment), time to treatment failure, and overall survival. Logistic regression models (univariable and multivariables) will be used when the outcome variable is dichotomous. Kaplan-meier curves will be used for time-to event outcomes, and comparisons will be done with the log-rank test and Cox regression models.
次要结局
- Comparison of Tumor Biomarker Profiling to Toxicity Outcome(4 years)