Power and Sample-Size Methodology for Radiology Research

放射学研究的功效和样本量方法

• 批准号: 8634095
• 负责人: Stephen Lawrence Hillis
• 金额: $ 32.96万
• 依托单位: UNIVERSITY OF IOWA
• 依托单位国家: 美国
• 财政年份: 2012
• 资助国家: 美国
• 起止时间: 2012-04-01 至 2016-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8634095
• 关键词: Accounting; Biomedical Technology; Calibration; Case Study; Clinical Research; Computer software; Data; Development; Diagnostic; Diagnostic radiologic examination; Disease; Dose; Ensure; Evaluation; Expenditure; Experimental Designs; Goals; Health; Human Resources; Image; Legal patent; Methodology; Methods; Mission; Modality; Modeling; National Institute of Biomedical Imaging and Bioengineering; Outcome; Patients; Performance; Pilot Projects; Play; Population; Probability; ROC Curve; Radiology Specialty; Reader; Reading; Receiver Operating Characteristics; Registries; Research; Research Design; Research Personnel; Risk; Role; Sample Size; Specific qualifier value; Thick; Time; Validation; design; experience; imaging modality; improved; innovation; interest; method development; models and simulation; novel strategies; radiologist; research study; response; user-friendly

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.

描述(申请人提供)：放射成像实验的常规功率和样本量(P&SS)方法未能考虑到放射科医生对变异性的不精确的先导研究估计，使得研究可能会无法接受地被压倒或不足。对样本大小的过高估计会导致放射科医生不必要的阅读时间、疾病状态验证以及对受试者可能的风险。对样本量的低估导致了不确定的结果。目前用于MRMC研究的P&SS方法的其他问题是，它只为一项研究设计而开发，经历了有限的评估，并且没有免费的独立软件来实施它。这一建议将显著提高DBM/OR能力和样本量方法，因为它提供了一种经过彻底验证的P&SS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施。长期目标是提供一种全面的统计方法，适用于诊断放射成像研究，同时考虑到患者和读者的可变性。此应用程序的目标是通过追求以下四个具体目标来改进该方法的能力和样本量(P&SS)方面：(1)开发一个现实的和可解释的模型来生成ROC决策数据，用于评估模拟临床研究数据的能力和样本量方法。(2)验证一种新的功率和样本量计算方法“置信度P&SS”，该方法考虑了不可靠的先导研究方差估计。(3)将方法论扩展到包括其他设计。(4)开发用户友好的、免费的独立软件，以实施该方法。AIM 1是必要的，因为当前的放射成像数据模拟模型可能不能准确地反映临床研究。AIM 2将使用在AIM1中开发的仿真模型来验证所提出的方法。AIM 3将扩展P&SS方法，以包括包含析因设计的附加因素(例如，CAD、放射科医生经验或阅读条件)以及嵌套设计(例如，分裂小区设计)的设计。目标4将确保基本统一执行和广泛使用该方法。拟议的研究将极大地推动P&SS方法学的发展。积极的影响将是加速生物医学技术的应用，这是以下结果的结果：(1)更有效地分配用于研究的财力和人力资源；(2)减少无果而终、动力不足的实验；以及(3)能够为其他几个有用的设计计算样本量估计。主要的创新将是P&SS方法的发展，该方法考虑到允许研究人员确定不仅对应于指定功率而且对应于定义指定功率将实际实现的概率的指定置信度的样本量估计的读者方差估计的精确度。

项目成果

Demonstration of Multi- and Single-Reader Sample Size Program for Diagnostic Studies software.

用于诊断研究软件的多和单读者样本量程序演示。

• DOI: 10.1117/12.2083150
• 发表时间: 2015
• 期刊: Proceedings of SPIE--the International Society for Optical Engineering
• 作者: Hillis,StephenL;Schartz,KevinM
• 通讯作者: Schartz,KevinM

Relationship between Roe and Metz simulation model for multireader diagnostic data and Obuchowski-Rockette model parameters.

多阅读器诊断数据的 Roe 和 Metz 仿真模型与 Obuchowski-Rockette 模型参数之间的关系。

• DOI: 10.1002/sim.7616
• 发表时间: 2018
• 期刊: Statistics in medicine
• 影响因子: 2
• 作者: Hillis,StephenL

Interpretation time for screening mammography as a function of the number of computer-aided detection marks.

筛查乳房 X 光检查的解释时间与计算机辅助检测标记数量的函数关系。

• DOI: 10.1117/1.jmi.7.2.022408
• 发表时间: 2020
• 期刊: Journal of medical imaging (Bellingham, Wash.)
• 作者: Schwartz,TaylerM;Hillis,StephenL;Sridharan,Radhika;Lukyanchenko,Olga;Geiser,William;Whitman,GaryJ;Wei,Wei;Haygood,TamaraMiner
• 通讯作者: Haygood,TamaraMiner