Prospective validation of a multi-marker prostate cancer prediction model

多标志物前列腺癌预测模型的前瞻性验证

• 批准号: 8676733
• 负责人: Stephen Boorjian
• 金额: $ 45.29万
• 依托单位: SLOAN-KETTERING INST CAN RESEARCH
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-08-08 至 2016-05-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8676733
• 关键词: Affect; Archives; Area Under Curve; Biopsy; Blood; Blood specimen; Cancer Detection; Clinical; Decision Analysis; Diagnostic Neoplasm Staging; Dry Ice; Europe; European; Freezing; Kininogenase; Laboratories; Laboratory Research; Limited Stage; Malignant Neoplasms; Malignant neoplasm of prostate; Measurement; Measures; Modeling; Outcome; Participant; Patients; Peptide Hydrolases; Population; Prostate; Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial; Prostate-Specific Antigen; Protein Isoforms; Randomized; Research; Sampling; Schedule; Screening for Prostate Cancer; Serum; Shipping; Ships; Simulate; Site; Sorting - Cell Movement; Specific qualifier value; Statistical Models; Testing; Time; Urologist; Validation; base; clinical decision-making; clinical practice; cohort; men; prospective; simulation

DESCRIPTION (provided by applicant): Approximately one million biopsies for prostate cancer are conducted each year in the US. The majority are unnecessary: the most common reason for a prostate biopsy is an elevated level of prostate-specific antigen (PSA) in the blood, but most men with elevated PSA do not have prostate cancer. In seven separate studies, involving over 7500 men and 2250 cancers, we have shown that a statistical model based on measuring isoforms of PSA, and kallikrein-related peptidase 2 (hK2), is a highly accurate predictor of prostate biopsy outcome in men with elevated PSA. In our primary study, the area-under-the-curve of the model was applied to an independent validation set was 0.76, far higher than PSA alone (0.64). We have also conducted decision analyses demonstrating that use of the statistical model to determine referral for prostate biopsy would reduce the number of unnecessary biopsies by about half, but miss only a small number of cancers, almost all of which would be the sort of low grade and stage cancers typically thought to constitute overdiagnosis. All of our prior studies were retrospectively conducted on European populations using frozen archived samples analyzed in a single research laboratory. In this proposal, we will first seek to evaluate the statistical model when applied retrospectively to a US cohort. We will then test whether independent clinical laboratories can measure the panel of four kallikreins accurately using control samples. We will then go on to prospectively collect research blood from patients before a scheduled biopsy. This sample will be analyzed locally, in real time, although the scheduled biopsy will continue irrespective of marker results, with biopsy outcome compared with the prediction from the statistical model. Finally, we will explore how implementation of the model would affect clinical practice using decision-analytic simulation and a vignette study.

描述（由申请人提供）：美国每年进行大约一百万个针对前列腺癌的活检。大多数是不必要的：前列腺活检的最常见原因是血液中前列腺特异性抗原（PSA）的水平升高，但大多数PSA升高的男性没有前列腺癌。在涉及7500多名男性和2250次癌症的七项独立研究中，我们表明，基于测量PSA的同工型和Kallikrein相关肽酶2（HK2）的统计模型是对PSA升高男性的前列腺活检结果的高度准确预测指标。在我们的主要研究中，该模型的区域范围用于独立验证集，为0.76，远高于PSA（0.64）。我们还进行了决策分析，表明使用统计模型来确定前列腺活检的转诊会使不必要的活检的数量减少大约一半，但只错过了少数癌症，几乎所有这些癌症通常都是通常被认为是构成过度诊断的低级和阶段癌症。我们所有先前的研究均在单个研究实验室中分析的冷冻存档样本对欧洲人群进行了回顾性进行。在此提案中，我们将首先寻求评估统计模型，以追溯应用于美国队列。然后，我们将测试独立的临床实验室是否可以使用对照样品准确地测量四个Kallikreins的面板。然后，我们将在预定的活检之前继续从患者那里收集研究血液。该样本将在本地进行实时分析，尽管与统计模型的预测相比，预定的活检将继续进行，并进行活检结果。最后，我们将探讨该模型的实施将如何使用决策分析模拟和小插图研究影响临床实践。