The Laboratory Effect in Breast Cancer Detection Studies

描述（由申请人提供）： 在过去的二十年里，我们已经取得了很大的进展，在诊断系统的性能评估，无论是在绝对和相对条件下，在我们的理解使用观察员的性能研究。解释病例、读数器和模式可变性的分析方法正在迅速获得可信度;因此，它们的使用不仅在科学研究中越来越普遍，而且在系统实用性的行业演示中也越来越普遍，作为监管批准的条件。用于系统评估和比较的ROC型方法已经成为一种非常通用的工具，可以在实验室环境中解决广泛的科学和临床问题。在所有这些研究中，更重要的问题不是在研究/实验室条件下推广病例、阅片者、异常和模式的能力，而是对不同技术或实践对实际临床环境的潜在影响进行有效推断的能力。虽然直觉也许，到目前为止，没有确凿的证据证明后者。在这方面，我们所掌握的非常有限的实验数据表明情况恰恰相反。在这个项目中追求的主要目标是确定和比较的性能水平的观察员建议召回导致乳腺癌的检测在临床环境中，他们的性能在实验室中建议召回和检测乳腺癌。这将通过从QA和临床记录中回顾性地确定和验证参与者的性能水平以及通过执行双模式观察者性能研究来完成，一种是模拟临床环境中的评级，另一种是ROC型研究。在一种模式中，我们将模拟临床环境（使用BI-RADS评级），另一种模式将包括ROC类型研究（使用置信度评级）。读者将回顾和解释他们以前在诊所前瞻性诊断的病例，以及其他人诊断的病例。我们试图做的比较是我们以有效的方式将实验室观察员性能数据推广到一般临床环境的能力（或不）的核心。

DESCRIPTION (provided by applicant): Great progress has been made in the last two decades in our understanding of the use of observer performance studies in the evaluation of diagnostic systems performance, both in absolute and in relative terms. Analytical approaches that account for variability of cases, readers, and modes are rapidly gaining credibility; hence, their use is becoming common not only in scientific investigations, but also in industry demonstrations of system utility as a condition for regulatory approvals. ROC-type methodology for systems evaluations and comparisons has become an extremely versatile tool that can address a wide range of scientific and clinical questions in the laboratory environment. The more important question of interest in all of these studies is not the ability to generalize to cases, readers, abnormalities and modalities under the study/I laboratory conditions, but rather to enable valid inferences on the potential impact of different technologies orI practices on the actual clinical environment. Although intuitive perhaps, to date, there is no conclusivel evidence for the latter. The very limited experimental data we have in this regard suggests the contrary. The primary goal being pursued in this project is to determine and compare the performance levels of observers recommending recall leading to the detection of breast cancers in the clinical environment with their performance in recommending recall and detecting breast cancers in the laboratory. This will be done by ascertaining and verifying performance levels of participants retrospectively from QA and clinical records and by performing a two-mode observer performance study, one simulating the ratings in the clinical environment and the other, an ROC-type study. In one mode we will be simulating the clinical environment (using BI-RADS ratings) and the other will include an ROC-type study (using confidence ratings). Readers will review and interpret both cases that they had previously diagnosed prospectively in the clinic, as well as cases diagnosed by others. The comparison we are attempting to do is at the very core of our ability (or not) to generalize laboratory observer performance data to the general clinical environment in a valid manner.