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捕获-再捕获方法的价值,即使对于看似详尽无遗的调查也是如此。在试图进行完整患病率研究时,需要对确定来源交叉进行调整。

The value of capture-recapture methods even for apparent exhaustive surveys. The need for adjustment for source of ascertainment intersection in attempted complete prevalence studies.

作者信息

Hook E B, Regal R R

机构信息

School of Public Health, University of California, Berkeley.

出版信息

Am J Epidemiol. 1992 May 1;135(9):1060-7. doi: 10.1093/oxfordjournals.aje.a116400.

Abstract

Almost all reported prevalence studies of which we are aware make exhaustive attempts to find diagnosed individuals and report all affected individuals, but make no attempt to estimate or adjust for missing cases. Yet very simple methods introduced in the planning stage of a prevalence study may enable investigators, or at least those subsequently reading their reports, to derive such adjusted estimates. If investigators keep track of the nature of the ascertainment of cases by source and collect and report data that allow calculation of the number of cases by source intersection, then they, or at least others, may derive estimates of missing cases and of the total population affected, by using readily available analogues of capture-recapture methods developed for wildlife populations censuses. Unfortunately, such methods are often inappropriately disparaged or ignored by epidemiologists. The derived estimates are sensitive to assumptions about dependence or independence ("interaction") of various sources, assumptions that sometimes are unprovable, and these estimates have some uncertainty because of statistical fluctuation. Moreover, most investigators who attempt exhaustive prevalence studies apparently believe that they have ascertained all cases and that there is no need to attempt to adjust for, let alone provide data pertinent to, the number of missing cases or to use a statistical method that will at best imply a certain imprecision to their result. Yet a survey that reports prevalence data without adjustment for, or data on, source intersection in essence makes an estimate of missing cases--zero--while providing no quantitative grounds for that claim. The results of all such surveys should be regarded with skepticism because, at best (if the case reports are accurate), they provide only a lower boundary of prevalence. We illustrate the grounds for these views by analyzing data from an apparently exhaustive prevalence study that used at least 14 distinct sources for ascertainment, including advertising, to find cases. Available limited data on source intersection provided in the report enable the plausible inference that the study missed about 25-40% of cases. We urge that no attempted complete prevalence studies be presented without data on ascertainment by source intersection.

摘要

据我们所知,几乎所有已报道的患病率研究都竭尽全力去寻找已确诊个体并报告所有受影响个体,但却没有尝试估计或调整漏报病例。然而,在患病率研究的规划阶段引入非常简单的方法,可能会使研究人员,或者至少是那些随后阅读其报告的人,得出这样的调整后估计值。如果研究人员按来源跟踪病例确定的性质,并收集和报告允许按来源交叉计算病例数的数据,那么他们,或者至少其他人,可以通过使用为野生动物种群普查开发的捕获 - 再捕获方法的现成类似方法,得出漏报病例数和受影响总人口的估计值。不幸的是,此类方法常常被流行病学家不恰当地贬低或忽视。得出的估计值对关于各种来源的依赖性或独立性(“相互作用”)的假设很敏感,这些假设有时无法证实,并且由于统计波动,这些估计值存在一定的不确定性。此外,大多数尝试进行详尽患病率研究的研究人员显然认为他们已经确定了所有病例,并且没有必要尝试调整漏报病例数,更不用说提供与之相关的数据,或者使用一种充其量只会暗示其结果存在一定不精确性的统计方法。然而,一项在未调整来源交叉情况或未提供相关数据的情况下报告患病率数据的调查,实际上是对漏报病例数进行了估计——零——同时却没有为该声称提供定量依据。所有此类调查的结果都应受到质疑,因为充其量(如果病例报告准确),它们仅提供了患病率的下限。我们通过分析一项明显详尽的患病率研究的数据来说明这些观点的依据,该研究使用了至少14种不同的确定来源,包括广告来查找病例。报告中提供的关于来源交叉的有限可用数据使得可以合理推断该研究遗漏了约25 - 40%的病例。我们敦促,在没有按来源交叉确定情况的数据时,不要呈现任何尝试进行的完整患病率研究。

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