Evidence map›Paper›PMID 31205285›Full record

ArticleEpidemiology (Cambridge, Mass.)2019

Adjustment for Urinary Creatinine or Serum Lipids for Analytes Assayed in Pooled Specimens.

Clarice R Weinberg, Min Shi, Katie M O'Brien, David M Umbach

Abstract read
In one paragraph

Article in Epidemiology (Cambridge, Mass.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

  1. Article
  2. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Clarice R WeinbergFrom the Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC (CRW, MS, DMU).
Min ShiFrom the Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC (CRW, MS, DMU).
Katie M O'BrienEpidemiology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC (KMO).
David M UmbachFrom the Biostatistics and Computational Biology Branch, National Institute of Environmental Health Sciences, Research Triangle Park, NC (CRW, MS, DMU).

Funding

Statistical Methods In Epidemiology--generalZIAES040006 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 2009 to 2025
$4.5M
STATISTICAL METHODS IN EPIDEMIOLOGY--GENERALZ01ES040006 · NIEHS · NATIONAL INSTITUTE OF ENVIRONMENTAL HEALTH SCIENCES · PI WEINBERG, CLARICE · 1997 to 2008
$65k
Intramural NIH HHS Z01 ES040006
6 · The paper itself

Abstract

backgroundFor case-control studies, pooling biologic specimens (cases with cases and controls with controls) can make it affordable to study a biomarker that is expensive to assay, while conserving quantities of archived specimens. For a fixed number of participants, pooling designs incur little loss of estimation precision, and they can even improve precision by enabling inclusion of more participants with the same number of assays. A limitation that has discouraged the use of these methods in environmental epidemiology, however, is the lack of a valid way to adjust for creatinine (urinary dilution) when assaying a biomarker in urine or to adjust for serum lipids when assaying a lipophilic biomarker in serum. We aimed to develop practical strategies to accomplish those adjustments.

methodsOur strategies either differentially dilute specimens before pooling equal aliquots or, alternatively, pool deliberately unequal aliquots from each specimen, where prior determinations of the adjustment factor in each individual specimen inform their differential dilution or unequal aliquot volumes. In addition, we show how to modify these strategies if, instead of just adjusting for creatinine per se, one needs to account for factors that influence creatinine. We carry out simulations under several causal scenarios.

resultsWe demonstrate that the proposed strategies perform well in estimating the same adjusted association parameter as would be estimated by using individually-assayed specimens.

conclusionBy implementing the proposed strategies when forming specimen pools, one can greatly improve the efficiency of case-control studies that involve an expensive-to-assay exposure measured in biospecimens.

Indexed as

Epidemiologic Research DesignBiomarkersCase-Control StudiesComputer SimulationCreatinineData Interpretation, StatisticalEnvironmental ExposureHumansLipidsModels, BiologicalModels, StatisticalBiomarkersCreatinineLipids

Identifiers

PMID31205285
PMCPMC6679734

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.