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EUCLID:一种用于高维临床研究的结果分析工具。

EUCLID: an outcome analysis tool for high-dimensional clinical studies.

作者信息

Gayou Olivier, Parda David S, Miften Moyed

机构信息

Department of Radiation Oncology, Allegheny General Hospital, Pittsburgh, PA 15212, USA.

出版信息

Phys Med Biol. 2007 Mar 21;52(6):1705-19. doi: 10.1088/0031-9155/52/6/011. Epub 2007 Feb 27.

Abstract

Treatment management decisions in three-dimensional conformal radiation therapy (3DCRT) and intensity-modulated radiation therapy (IMRT) are usually made based on the dose distributions in the target and surrounding normal tissue. These decisions may include, for example, the choice of one treatment over another and the level of tumour dose escalation. Furthermore, biological predictors such as tumour control probability (TCP) and normal tissue complication probability (NTCP), whose parameters available in the literature are only population-based estimates, are often used to assess and compare plans. However, a number of other clinical, biological and physiological factors also affect the outcome of radiotherapy treatment and are often not considered in the treatment planning and evaluation process. A statistical outcome analysis tool, EUCLID, for direct use by radiation oncologists and medical physicists was developed. The tool builds a mathematical model to predict an outcome probability based on a large number of clinical, biological, physiological and dosimetric factors. EUCLID can first analyse a large set of patients, such as from a clinical trial, to derive regression correlation coefficients between these factors and a given outcome. It can then apply such a model to an individual patient at the time of treatment to derive the probability of that outcome, allowing the physician to individualize the treatment based on medical evidence that encompasses a wide range of factors. The software's flexibility allows the clinicians to explore several avenues to select the best predictors of a given outcome. Its link to record-and-verify systems and data spreadsheets allows for a rapid and practical data collection and manipulation. A wide range of statistical information about the study population, including demographics and correlations between different factors, is available. A large number of one- and two-dimensional plots, histograms and survival curves allow for an easy visual analysis of the population. Several visual and analytical methods are available to quantify the predictive power of the multivariate regression model. The EUCLID tool can be readily integrated with treatment planning and record-and-verify systems.

摘要

三维适形放射治疗(3DCRT)和调强放射治疗(IMRT)中的治疗管理决策通常基于靶区和周围正常组织的剂量分布做出。这些决策可能包括,例如,选择一种治疗方案而非另一种以及肿瘤剂量递增的水平。此外,诸如肿瘤控制概率(TCP)和正常组织并发症概率(NTCP)等生物学预测指标,其文献中可用的参数仅是基于群体的估计值,常被用于评估和比较治疗计划。然而,许多其他临床、生物学和生理因素也会影响放射治疗的结果,且在治疗计划和评估过程中常常未被考虑。开发了一种供放射肿瘤学家和医学物理学家直接使用的统计结果分析工具EUCLID。该工具构建一个数学模型,基于大量临床、生物学、生理和剂量学因素预测结果概率。EUCLID可首先分析一大组患者,如来自一项临床试验的患者,以得出这些因素与给定结果之间的回归相关系数。然后,它可在治疗时将这样一个模型应用于个体患者,以得出该结果的概率,从而使医生能够基于包含广泛因素的医学证据对治疗进行个体化。该软件的灵活性使临床医生能够探索多种途径来选择给定结果的最佳预测指标。它与记录和验证系统以及数据电子表格的链接允许快速且实际地收集和处理数据。可获得关于研究人群的广泛统计信息,包括人口统计学以及不同因素之间的相关性。大量的一维和二维图表、直方图和生存曲线便于对人群进行直观分析。有几种视觉和分析方法可用于量化多元回归模型的预测能力。EUCLID工具可轻松与治疗计划以及记录和验证系统集成。

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