Robustness of risk-based allocation of resources for disease prevention.
Robustness of risk-based allocation of resources for disease prevention.
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DOI：
10.1177/0962280220930055
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发表时间：
2020-12
影响因子：
2.3
通讯作者：
Pee D
中科院分区：
文献类型：
--
作者：
Gail MH;Pee D
如果风险评估费用不太高，疾病发病率风险模型可用于分配疾病预防资源。假设有一种预防性干预措施应该给予每个人，但预防性资源是有限的。我们优化基于风险的预防策略，并研究建模假设的鲁棒性。最佳战略确定了接受风险评估的人口比例以及应向谁提供干预。最佳战略取决于可用资源与对每个人进行干预所需资源的比例，以及风险评估与干预费用的比例。如果风险评估费用太高，则不建议进行风险评估。随着对风险评估或干预的依从性降低，预防效率也会降低。风险度量误差的影响很小，也没有错误的风险分布。忽略人口结构对最佳预防策略的影响很小，但可能导致适度的过度或不足支出。给出了忽略种群子结构对最优策略无影响的条件。因此，一个简单的单一人口模型为预防战略提供了强有力的指导，但需要关于现有资源、风险评估和干预费用、人口风险分布以及接受风险评估和干预的概率的数据。
Risk models for disease incidence can be useful for allocating resources for disease prevention if risk assessment is not too expensive. Assume there is a preventive intervention that should be given to everyone, but preventive resources are limited. We optimize risk-based prevention strategies and investigate robustness to modeling assumptions. The optimal strategy defines the proportion of the population to be given risk assessment and who should be offered intervention. The optimal strategy depends on the ratio of available resources to resources needed to intervene on everyone, and on the ratio of the costs of risk assessment to intervention. Risk assessment is not recommended if it is too expensive. Preventive efficiency decreases with decreasing compliance to risk assessment or intervention. Risk measurement error has little effect nor does misspecification of the risk distribution. Ignoring population substructure has small effects on optimal prevention strategy but can lead to modest over- or under-spending. We give conditions under which ignoring population substructure has no effect on optimal strategy. Thus, a simple one-population model offers robust guidance on prevention strategy but requires data on available resources, costs of risk assessment and intervention, population risk distribution, and probabilities of acceptance of risk assessment and intervention.
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影响因子：
45.3
作者：
Freedman, Andrew N.;Yu, Binbing;McCaskill-Stevens, Worta
通讯作者：
McCaskill-Stevens, Worta
影响因子：
1.9
作者：
Pfeiffer, R. M.;Gail, M. H.
通讯作者：
Gail, M. H.
影响因子：
120.7
作者：
Weinstein, MC;Siegel, JE;Russell, LB
通讯作者：
Russell, LB
影响因子：
158.5
作者：
STASON, WB;WEINSTEIN, MC
通讯作者：
WEINSTEIN, MC
DOI：
10.1093/jnci/91.21.1829
发表时间：
1999-11-03
期刊：
JOURNAL OF THE NATIONAL CANCER INSTITUTE
影响因子：
--
作者：
Gail, MH;Costantino, JP;Vogel, V
通讯作者：
Vogel, V