Evidence map›Paper›PMID 31208407›Full record

ArticleBMC medical informatics and decision making2019

The index lift in data mining has a close relationship with the association measure relative risk in epidemiological studies.

Khanh Vu, Rebecca A Clark, Colin Bellinger, Graham Erickson, Alvaro Osornio-Vargas, Osmar R Zaïane, Yan Yuan

Abstract read
In one paragraph

Article in BMC medical informatics and decision making, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

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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

2 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

7 authors.

Khanh VuUniversity of Alberta School of Public Health, Edmonton, AB, Canada.
Rebecca A ClarkUniversity of Alberta School of Public Health, Edmonton, AB, Canada.
Colin BellingerDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.
Graham EricksonUniversity of Alberta Women and Children's Health Research Institute, Edmonton, AB, Canada.
Alvaro Osornio-VargasDepartment of Pediatrics, University of Alberta, Edmonton, AB, Canada.
Osmar R ZaïaneDepartment of Computing Science, University of Alberta, Edmonton, AB, Canada.
Yan YuanUniversity of Alberta School of Public Health, Edmonton, AB, Canada. yyuan@ualberta.ca.ORCID 0000-0002-2073-9924

Funding

Canadian Institutes of Health Research (CIHR) and Natural Sciences and Engineering Research Council of Canada (NSERC) FRN: 127789
6 · The paper itself

Abstract

backgroundData mining tools have been increasingly used in health research, with the promise of accelerating discoveries. Lift is a standard association metric in the data mining community. However, health researchers struggle with the interpretation of lift. As a result, dissemination of data mining results can be met with hesitation. The relative risk and odds ratio are standard association measures in the health domain, due to their straightforward interpretation and comparability across populations. We aimed to investigate the lift-relative risk and the lift-odds ratio relationships, and provide tools to convert lift to the relative risk and odds ratio.

methodsWe derived equations linking lift-relative risk and lift-odds ratio. We discussed how lift, relative risk, and odds ratio behave numerically with varying association strengths and exposure prevalence levels. The lift-relative risk relationship was further illustrated using a high-dimensional dataset which examines the association of exposure to airborne pollutants and adverse birth outcomes. We conducted spatial association rule mining using the Kingfisher algorithm, which identified association rules using its built-in lift metric. We directly estimated relative risks and odds ratios from 2 by 2 tables for each identified rule. These values were compared to the corresponding lift values, and relative risks and odds ratios were computed using the derived equations.

resultsAs the exposure-outcome association strengthens, the odds ratio and relative risk move away from 1 faster numerically than lift, i.e. |log (odds ratio)| ≥ |log (relative risk)| ≥ |log (lift)|. In addition, lift is bounded by the smaller of the inverse probability of outcome or exposure, i.e. lift≤ min (1/P(O), 1/P(E)). Unlike the relative risk and odds ratio, lift depends on the exposure prevalence for fixed outcomes. For example, when an exposure A and a less prevalent exposure B have the same relative risk for an outcome, exposure A has a lower lift than B.

conclusionsLift, relative risk, and odds ratio are positively correlated and share the same null value. However, lift depends on the exposure prevalence, and thus is not straightforward to interpret or to use to compare association strength. Tools are provided to obtain the relative risk and odds ratio from lift.

Indexed as

Data MiningEpidemiologic StudiesOdds RatioRiskAlbertaFemaleHumansInfant, Low Birth WeightInfant, NewbornMaleMaternal ExposureAir pollutionAssociation rule miningData miningEnvironmental healthInterestingness measuresLiftOdds ratioRelative risk

Identifiers

PMID31208407
PMCPMC6580490

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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.