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用于估计α-β比值的体内多分割实验设计。

The design of in vivo multifraction experiments to estimate the alpha-beta ratio.

作者信息

Taylor J M

机构信息

Department of Radiation Oncology, UCLA Medical Center.

出版信息

Radiat Res. 1990 Jan;121(1):91-7.

PMID:2300673
Abstract

Using statistical methods, the designs of multifraction experiments which are likely to give the most precise estimate of the alpha-beta ratio in the linear-quadratic model are investigated. The aim of the investigation is to try to understand what features of an experimental design make it efficient for estimating alpha/beta rather than to recommend a specific design. A plot of the design on an nd2 versus nd graph is suggested, and this graph is called the design plot. The best designs are those which have a large spread in the isoeffect direction in the design plot, which means that a wide range of doses per fraction should be used. For binary response assays, designs with expected response probabilities near to 0.5 are most efficient. Furthermore, dose points with expected response probabilities outside the range 0.1 to 0.9 contribute negligibly to the efficiency with which alpha/beta can be estimated. For "top-up" experiments, the best designs are those which replace as small a portion as possible of the full experiment with the top-up scheme. In addition, from a statistical viewpoint, it makes no difference whether a single large top-up dose or several smaller top-up doses are used; however, other considerations suggest that two or more top-up doses may be preferable. The practical realities of designing experiments as well as the somewhat idealized statistical considerations are discussed.

摘要

运用统计方法,对多分割实验的设计进行了研究,这类实验有望在线性二次模型中对α/β比值给出最精确的估计。研究目的是试图理解实验设计的哪些特征使其在估计α/β时是高效的,而非推荐一种特定的设计。建议在nd2对nd的图上绘制设计,该图称为设计图。最佳设计是那些在设计图中等效效应方向上分布较广的设计,这意味着应使用范围广泛的分次剂量。对于二元反应测定,预期反应概率接近0.5的设计效率最高。此外,预期反应概率在0.1至0.9范围之外的剂量点对估计α/β的效率贡献可忽略不计。对于“补充”实验,最佳设计是那些用补充方案替代完整实验尽可能小的部分的设计。另外,从统计学角度看,使用单个大的补充剂量还是几个较小的补充剂量并无差别;然而,其他因素表明两个或更多补充剂量可能更可取。讨论了设计实验的实际情况以及一些理想化的统计考量。

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