OPTIMAL SCREENING FOR PROSTATE CA WITH SERIAL PSA LEVELS

通过连续 PSA 水平对前列腺 CA 进行最佳筛查

• 批准号: 2796352
• 负责人: Steven J Skates
• 金额: $ 4.6万
• 依托单位: MASSACHUSETTS GENERAL HOSPITAL
• 依托单位国家: 美国
• 财政年份: 1997
• 资助国家: 美国
• 起止时间: 1997-09-30 至 2000-03-29
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/2796352
• 关键词: cancer risk; clinical research; computer simulation; diagnosis design /evaluation; disease /disorder model; early diagnosis; human subject; longitudinal human study; male; mass screening; mathematical model; neoplasm /cancer classification /staging; neoplasm /cancer diagnosis; prostate neoplasms; prostate specific antigen; veterans

DESCRIPTION (Applicant's Description) The goal of this pilot study is to develop an approach to early detection of carcinoma of the prostate (CP) that is optimized, i.e. that, when compared to the standard approach, results in the greatest increase in years of life saved for a given increment in testing. The principal investigator is currently developing precise statistical models of long term longitudinal PSA behavior using data from participants in the Veterans Affairs (VA) Normative Aging Study (NAS) as part of a currently funded study. After the distributional assumptions of these models have been tested, we will use them to develop an optimized early detection approach that reassesses the risk that the patient has prostate cancer after each successive PSA measurement based on all previous measurements. The decision for the next step, either biopsy or when to have the next PSA test, is based on the current assessment of risk. Those at elevated risk will be measured more frequently for PSA levels, and those at highest risk are referred for more invasive diagnostic workup such as biopsy. Thus, more screening resources are allocated to patients who are at increased risk. For the intermediate risk group, time until next PSA measurement will be optimized to maximize the expected years of life saved, using published estimates of treatment efficacy by stage and age. The approach will be developed in three stages: (I) A statistical method for estimating the risk of CP based on single or multiple longitudinal PSA levels, and the duration between the PSA levels will be developed, (II) A computer simulation of an early detection program for CP incorporating the method for calculating risk of CP will be written, and (III) The simulation will be used to identify the optimal scheme for assigning patients into normal, intermediate, and high risk categories. This program will be similar to an approach the PI has developed for early detection of ovarian cancer with longitudinal levels of the marker CA125. The long-term objectives, beyond the scope of this proposal, are to expand these approaches to early detection of CP to include other tests such as "free PSA" and digital rectal exam, to implement these approaches in software appropriate for use in clinical settings, and to compare such optimized screening strategies with current screening strategies in a randomized clinical trial.

描述(申请人的描述)这项初步研究的目的是 开发早期发现前列腺癌(CP)的方法 这是优化的，即，与标准方法相比， 结果最大限度地增加了为给定的 测试中的增量。首席调查员目前正在开发 使用数据建立长期纵向PSA行为的精确统计模型 来自退伍军人事务部(VA)标准老龄化研究(NAS)的参与者 作为目前资助的一项研究的一部分。在分布假设之后 对这些模型进行了测试，我们将利用它们来开发一个优化的 重新评估患者存在的风险的早期检测方法 前列腺癌后每一次连续测量PSA基于所有以前的 测量。下一步的决定，无论是活组织检查还是何时进行 下一次PSA测试将基于当前的风险评估。那些位于 增加的风险将更频繁地测量PSA水平，以及 风险最高的是更具侵入性的诊断检查，例如 活组织检查。因此，更多的筛查资源被分配给处于 风险增加。对于中等风险组，到下一次PSA的时间 测量将进行优化，以最大限度地延长预期寿命， 使用已发表的按分期和年龄划分的治疗效果估计。这个 将分三个阶段制定办法：(1)统计方法 基于单个或多个纵向PSA的慢性前列腺炎风险评估 将制定PSA级别之间的持续时间，(二)A CP早期检测程序的计算机模拟 将编写CP风险的计算方法，以及(Iii)模拟 将用于确定最佳方案，以便将患者分配到 正常、中等和高风险类别。这一计划将是 与PI开发的用于卵巢早期检测的方法类似 标记物CA125纵向水平的癌症。长期的 超出本提案范围的目标是扩大这些 早期检测CP的方法包括其他测试，如“FREE” PSA“和直肠指诊，以便在软件中实施这些方法 适合在临床环境中使用，并比较这种优化 筛查策略与当前筛查策略的随机化 临床试验。