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: 8302113
• 负责人: Stephen Lawrence Hillis
• 金额: $ 33.98万
• 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 2015-03-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/8302113
• 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. PUBLIC HEALTH RELEVANCE: By allowing radiology researchers to more precisely estimate the numbers of patients and radiologists needed for imaging experiments, the proposed research will result in more efficient utilization of financial and human resources for evaluating new imaging modalities. Thus the proposed research is relevant to the mission of the National Institute of Biomedical Imaging and Bioengineering, namely to improve health by leading the development and accelerating the application of biomedical technologies.

描述（由申请人提供）：放射成像实验的常规功率和样本量（P&SS）方法未能考虑到对放射科医生变异性的不精确的试点研究估计，这可能使研究的功率过大或功率不足，这是不可接受的。高估样本量会导致不必要的放射科医生阅读时间，疾病状态验证和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，它只针对一个研究设计而开发，经过了有限的评估，并且没有免费的独立软件来实现它。该提案将通过提供一种经过彻底验证的P&SS方法，有效地解释不精确的试点读者方差估计，从而显著推进DBM/OR功率和样本量方法，可用于多种设计，并可使用免费的独立软件实现。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，考虑到患者和读者的可变性。本应用程序的目标是通过追求以下四个具体目标来改善该方法的功率和样本量（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，以评估模拟临床研究数据的功率和样本量方法。(2)验证一种新的功率和样本量计算方法，即“置信度P&SS”，该方法考虑了不可靠的试点研究方差估计。(3)扩展方法论以包括其他设计。(4)开发用户友好的、免费的独立软件来实施该方法。Aim 1是必要的，因为目前的放射成像数据模拟模型可能不能准确反映临床研究。Aim 2将使用Aim1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，以包括包括因子的额外因素（例如，CAD，放射科医生经验或阅读条件）以及嵌套设计（例如，分裂图设计）的设计。目标4将确保基本统一执行和广泛使用该方法。拟议的研究将显著推进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)更有效地为研究分配财政和人力资源；(2)不确定的低功率实验次数减少；(3)计算几个额外有用设计的样本大小估计的能力。主要的创新将是P&SS方法的发展，它考虑到读者方差估计缺乏精度，允许研究人员确定样本大小估计，这些估计不仅对应于指定的功率，而且对应于指定的置信水平，该置信水平定义了指定功率实际实现的概率。