Evidence map›Paper›PMID 30902064›Full record

ArticleBMC research notes2019

Development and use of a flexible data harmonization platform to facilitate the harmonization of individual patient data for meta-analyses.

Joeri Kalter, Maike G Sweegers, Irma M Verdonck-de Leeuw, Johannes Brug, Laurien M Buffart

Abstract read
In one paragraph

Article in BMC research notes, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed, 2 pooled it
–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

8 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Spinal manipulative therapy in older adults with chronic low back pain: an individual participant data meta-analysis.European spine journal : official publication of the European Spine Society, the European Spinal Deformity Society, and the European Section of the Cervical Spine Research Society · 2022
    Pooled it
  2. Pooled it
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  7. Article
  8. A Secure and Reusable Software Architecture for Supporting Online Data Harmonization.Proceedings : ... IEEE International Conference on Big Data. IEEE International Conference on Big Data · 2021
    Article
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

5 authors.

Joeri KalterDepartment of Epidemiology and Biostatistics, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands.
Maike G SweegersDepartment of Epidemiology and Biostatistics, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands.
Irma M Verdonck-de LeeuwAmsterdam Public Health Research Institute, Amsterdam, The Netherlands.
Johannes BrugDepartment of Epidemiology and Biostatistics, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands.
Laurien M BuffartDepartment of Epidemiology and Biostatistics, Amsterdam University Medical Centres, Vrije Universiteit Amsterdam, De Boelelaan 1089a, 1081 HV, Amsterdam, The Netherlands. l.buffart@vumc.nl.

Funding

KWF Kankerbestrijding VU 2011-5045
6 · The paper itself

Abstract

objectiveHarmonizing individual patient data (IPD) for meta-analysis has clinical and statistical advantages. Harmonizing IPD from multiple studies may benefit from a flexible data harmonization platform (DHP) that allows harmonization of IPD already during data collection. This paper describes the development and use of a flexible DHP that was initially developed for the Predicting OptimaL cAncer RehabIlitation and Supportive care (POLARIS) study.

resultsThe DHP that we developed (I) allows IPD harmonization with a flexible approach, (II) has the ability to store data in a centralized and secured database server with large capacity, (III) is transparent and easy in use, and (IV) has the ability to export harmonized IPD and corresponding data dictionary to a statistical program. The DHP uses Microsoft Access as front-end application and requires a relational database management system such as Microsoft Structured Query Language (SQL) Server or MySQL as back-end application. The DHP consists of five user friendly interfaces which support the user to import original study data, to harmonize the data with a master data dictionary, and to export the harmonized data into a statistical software program of choice for further analyses. The DHP is now also adopted in two other studies.

Indexed as

Database Management SystemsDatabases, FactualInformation Storage and RetrievalMedical Informatics ApplicationsMeta-Analysis as TopicHumansCentralized and secured database serverEasy in use infrastructureFlexible data harmonization platform

Identifiers

PMID30902064
PMCPMC6431032

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.