Power and Sample-Size Methodology for Radiology Research

描述（由申请人提供）：放射成像实验的传统功效和样本量（P&SS）方法未能考虑放射科医师之间变异性的不精确的试点研究估计，使得研究可能无法接受过度或不足。样本量的高估导致不必要的放射科医师阅读时间、疾病状态验证和对受试者的可能风险。低估样本量会导致不确定的结果。目前MRMC研究的P&SS方法的其他问题是，它只针对一个研究设计开发，经过有限的评估，并且不存在用于实施它的免费独立软件。该提案将通过提供一种经过彻底验证的P&SS方法来显著提高DBM/OR功效和样本量方法，该方法有效地解释了不精确的试点读者方差估计，可以用于多种设计，并且可以使用免费的独立软件来实现。长期目标是提供一个全面的统计方法，适用于诊断放射成像研究，占病人和读者的变化。本应用程序的目标是通过追求以下四个具体目标来提高该方法的功效和样本量（P&SS）方面：（1）开发一个现实且可解释的模型，用于生成ROC决策数据，以评估功效和样本量模拟临床研究数据的方法。(2)一种新的方法，功率和样本量的计算，“置信水平P&SS”，考虑到不可靠的试点研究方差估计。(3)扩展该方法以包括其他设计。(4)开发便于使用的、免费的独立软件，用于实施该方法。 目标1是必要的，因为目前放射成像数据的模拟模型可能无法准确反映临床研究。目标2将使用Aim 1中开发的仿真模型验证所提出的方法。目标3将扩展P&SS方法，以包括包含附加因子的设计（例如，CAD、放射科医师经验或阅读条件）以及嵌套设计（例如，裂区设计）。目标4将确保基本的统一执行和广泛使用该方法。 该研究将大大推进P&SS方法。积极的影响将是加速生物医学技术的应用，因为（1）更有效地分配研究的财政和人力资源;（2）不太频繁的不确定的动力不足的实验;和（3）计算样本量估计的能力为几个额外的有用的设计。主要的创新将是P&SS方法的发展，该方法考虑到读者方差估计缺乏精确度，允许研究人员确定样本量估计值，该估计值不仅对应于指定的功效，而且对应于定义实际实现指定功效的概率的指定置信水平。

DESCRIPTION (provided by applicant): Conventional power and sample-size (P&SS) methodology for radiological imaging experiments fails to take into account imprecise pilot-study estimates of variability among radiologists, making it likely that studies will be unacceptably overpowered or underpowered. Overestimation of sample sizes results in unneeded radiologist reading time, disease-status verification, and possible risks to subjects. Underestimation of sample sizes results in inconclusive findings. Other problems with current P&SS methodology for MRMC studies are that it has only been developed for one study design, has undergone limited evaluation, and free stand-alone soft- ware does not exist for implementing it. This proposal will significantly advance DBM/OR power and sample-size methodology by contributing a thoroughly validated P&SS methodology that effectively accounts for imprecise pilot reader-variance estimates, can be used with several designs, and can be implemented using free stand-alone software. The long-term goal is to provide a thorough statistical methodology appropriate for diagnostic radiological imaging research that accounts for both patient and reader variability. The objective of this application is to improve the power and sample size (P&SS) aspect of this methodology by pursuing the following four specific aims: (1) Develop a realistic and interpretable model for generating ROC decision data for evaluating the power and sample size methodology that emulates data from clinical studies. (2) Validate a new approach to power and sample-size calculation, 'confidence-level P&SS,' that takes into account unreliable pilot-study variance estimates. (3) Extend the methodology to include other designs. (4) Develop user-friendly, free stand-alone software for implementing the methodology. Aim 1 is necessary because current simulation models for radiological imaging data may not accurately reflect clinical studies. Aim 2 will validate the proposed approach using the simulation model developed in Aim1. Aim 3 will extend the P&SS methodology to include designs which include an additional factor (e.g., CAD, radiologist experience, or reading condition) for factorial as wel as nested designs (e.g., split plot de- signs). Aim 4 will ensure essential uniform implementation and wide-spread use of the methodology. The proposed research will significantly advance P&SS methodology. The positive impact will be to accelerate the application of biomedical technologies as a result of (1) more efficient allocation of financial and human resources for research; (2) less frequent inconclusive underpowered experiments; and (3) the ability to compute sample-size estimates for several additional useful designs. The major innovation will be the development of P&SS methodology that takes into account the lack of precision in reader variance estimates by al- lowing researchers to determine sample-size estimates that correspond not only to a specified power but also to a specified confidence level that defines the probability that the specified power will actually be realized.