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）本试点研究的目标是 开发一种早期检测前列腺癌（CP）的方法 经过优化，即与标准方法相比， 导致在给定的情况下可以最大程度地延长寿命 测试中的增量。 主要研究者目前正在开发 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) 规范老龄化研究 (NAS) 参与者的意见 作为当前资助的研究的一部分。 经过分布假设 这些模型已经过测试，我们将使用它们来开发优化的 重新评估患者风险的早期检测方法 前列腺癌在每次连续 PSA 测量后基于之前所有 测量。 下一步的决定，无论是活检还是何时进行 下一次 PSA 测试是基于当前的风险评估。 那些在 升高的风险将更频繁地测量 PSA 水平，并且那些处于 最高风险被转介进行更具侵入性的诊断检查，例如 活检。 因此，更多的筛查资源被分配给处于以下状态的患者： 风险增加。 对于中度风险组，距离下一次 PSA 的时间 将优化测量以最大限度地延长预期寿命， 使用已发表的按阶段和年龄划分的治疗效果估计值。 这 方法将分三个阶段开发： (I) 统计方法 基于单项或多项纵向 PSA 评估 CP 风险 水平，以及 PSA 水平之间的持续时间，(II) A CP 早期检测程序的计算机模拟 将编写计算CP风险的方法，以及（III）模拟 将用于确定将患者分配到的最佳方案 正常、中度和高风险类别。 该计划将 类似于 PI 开发的用于早期检测卵巢的方法 具有标记物 CA125 纵向水平的癌症。 长期来看 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，例如“免费测试” PSA”和直肠指检，在软件中实施这些方法 适合在临床环境中使用，并比较这种优化的 随机筛选策略与当前筛选策略 临床试验。