Evidence map›Paper›PMID 26836255›Full record

ArticleJournal of clinical epidemiology2016

Poor record linkage sensitivity biased outcomes in a linked cohort analysis.

Cecilia L Moore, Heather F Gidding, Matthew G Law, Janaki Amin

Abstract read
In one paragraph

Article in Journal of clinical epidemiology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 citing papers in PubMed.

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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.

Cecilia L MooreThe Kirby Institute, UNSW Medicine, The University of New South Wales, Sydney 2052, Australia. Electronic address: cmoore@kirby.unsw.edu.au.
Heather F GiddingSchool of Public Health and Community Medicine, UNSW Medicine, The University of New South Wales, Sydney 2052, Australia.
Matthew G LawThe Kirby Institute, UNSW Medicine, The University of New South Wales, Sydney 2052, Australia.
Janaki AminThe Kirby Institute, UNSW Medicine, The University of New South Wales, Sydney 2052, Australia.

Funding

HIV Vaccine Design and Development Teams-26605395N01AI005395 · NIAID · UNIVERSITY OF NEW SOUTH WALES · 2000 to 2004
$3.2M
NIAID NIH HHS N01 AI005395
6 · The paper itself

Abstract

objectivesTo examine the validity of deterministic compared to probabilistic record linkage in the ascertainment of hospitalizations in two linked cohorts. STUDY DESIGN AND

settingHIV-negative (HIV-ve) (n = 1,325) and HIV-positive (HIV+ve) gay and bisexual men (n = 557) recruited in Sydney, Australia, were probabilistically and deterministically linked to a statewide hospital registry (July 2000-June 2012).

resultsUsing probabilistic linkage as the reference standard, deterministic linkage had higher specificity but much lower sensitivity [34.67% (95% confidence interval: 33.44, 35.92)]. A disproportionate number of links missed were individuals with poorer socioeconomic and health indicators, including HIV status. Risk of hospitalization compared to the general male population [HIV+ve standardized incidence ratio (SIR) = 1.45 (1.33-1.59); HIV-ve SIR = 0.72 (0.67-0.78)] was significantly underestimated when deterministic linkage was used [HIV+ve SIR = 0.46 (0.37-0.58); HIV-ve SIR = 0.29 (0.24-0.35)]. The impact of linkage strategy on the calculation of incidence rate ratios (IRRs) was less, but a greater discrepancy in IRRs was seen for diagnostic categories where event rates were low or where the sensitivity of the deterministic linkage was differential between the two cohorts.

conclusionLinkage without proven high sensitivity and specificity should be carefully considered. In circumstances of undetermined sensitivity, SIRs should not be calculated as the extent of underestimation is unknown. The comparison of linked events within or between cohorts is more robust to linkage misclassification; however, selection bias does affect estimates and should be considered before linkage.

Indexed as

Epidemiologic Research DesignAdultAustraliaBiasCohort StudiesHIV InfectionsHospitalizationHumansIncidenceMaleMedical Record LinkageMiddle AgedRegistriesReproducibility of ResultsSensitivity and SpecificityAustraliaCohort studyDeterministic record linkageEvaluationHospital dischargeProbabilistic record linkage

Identifiers

PMID26836255
PMCPMC4916010

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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.