Evidence map›Paper›PMID 38857066›Full record

ArticleJournal of medical Internet research2024

Creation of Standardized Common Data Elements for Diagnostic Tests in Infectious Disease Studies: Semantic and Syntactic Mapping.

Caroline Stellmach, Sina Marie Hopff, Thomas Jaenisch, Susana Marina Nunes de Miranda, Eugenia Rinaldi, NAPKON, LEOSS, ORCHESTRA, and ReCoDID Working Groups

Abstract read
In one paragraph

Article in Journal of medical Internet research, 2024. 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
  3. Federated systems for automated infection surveillance: a perspective.Antimicrobial resistance and infection control · 2024
    Review
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

6 authors.

Caroline StellmachBerlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0001-6798-8533
Sina Marie HopffCenter for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Department I of Internal Medicine, University Hospital Cologne and Faculty of Medicine, University of Cologne, Cologne, Germany.ORCID 0000-0002-8886-4596
Thomas JaenischHeidelberg Institut für Global Health, Universitätsklinikum Heidelberg, Heidelberg, Germany.ORCID 0000-0002-9464-571X
Susana Marina Nunes de MirandaCenter for Integrated Oncology Aachen Bonn Cologne Duesseldorf, Department I of Internal Medicine, University Hospital Cologne and Faculty of Medicine, University of Cologne, Cologne, Germany.ORCID 0000-0003-2072-6979
Eugenia RinaldiBerlin Institute of Health, Charité - Universitätsmedizin Berlin, Berlin, Germany.ORCID 0000-0003-0343-6400
NAPKON, LEOSS, ORCHESTRA, and ReCoDID Working GroupsSee Acknowledgments, .

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundIt is necessary to harmonize and standardize data variables used in case report forms (CRFs) of clinical studies to facilitate the merging and sharing of the collected patient data across several clinical studies. This is particularly true for clinical studies that focus on infectious diseases. Public health may be highly dependent on the findings of such studies. Hence, there is an elevated urgency to generate meaningful, reliable insights, ideally based on a high sample number and quality data. The implementation of core data elements and the incorporation of interoperability standards can facilitate the creation of harmonized clinical data sets.

objectiveThis study's objective was to compare, harmonize, and standardize variables focused on diagnostic tests used as part of CRFs in 6 international clinical studies of infectious diseases in order to, ultimately, then make available the panstudy common data elements (CDEs) for ongoing and future studies to foster interoperability and comparability of collected data across trials.

methodsWe reviewed and compared the metadata that comprised the CRFs used for data collection in and across all 6 infectious disease studies under consideration in order to identify CDEs. We examined the availability of international semantic standard codes within the Systemized Nomenclature of Medicine - Clinical Terms, the National Cancer Institute Thesaurus, and the Logical Observation Identifiers Names and Codes system for the unambiguous representation of diagnostic testing information that makes up the CDEs. We then proposed 2 data models that incorporate semantic and syntactic standards for the identified CDEs.

resultsOf 216 variables that were considered in the scope of the analysis, we identified 11 CDEs to describe diagnostic tests (in particular, serology and sequencing) for infectious diseases: viral lineage/clade; test date, type, performer, and manufacturer; target gene; quantitative and qualitative results; and specimen identifier, type, and collection date.

conclusionsThe identification of CDEs for infectious diseases is the first step in facilitating the exchange and possible merging of a subset of data across clinical studies (and with that, large research projects) for possible shared analysis to increase the power of findings. The path to harmonization and standardization of clinical study data in the interest of interoperability can be paved in 2 ways. First, a map to standard terminologies ensures that each data element's (variable's) definition is unambiguous and that it has a single, unique interpretation across studies. Second, the exchange of these data is assisted by "wrapping" them in a standard exchange format, such as Fast Health care Interoperability Resources or the Clinical Data Interchange Standards Consortium's Clinical Data Acquisition Standards Harmonization Model.

Indexed as

Communicable DiseasesSemanticsCommon Data ElementsHumanscase report formCDEclinical datacommon elementcore data elementcovid19COVID-19CRFdata modeldiagnostic testFHIRinfectious diseaseinteroperabilityLOINCmpoxpatient datasemantic standardsSNOMED CTsyntactic interoperabilityvirus infectionZIKV

Identifiers

PMID38857066
PMCPMC11196918

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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.