Evidence map›Paper›PMID 25565606›Full record

ArticleDiagnostic pathology2014

A reference model based interface terminology for generic observations in Anatomic Pathology Structured Reports.

Gunter Haroske, Thomas Schrader

Abstract read
In one paragraph

Article in Diagnostic pathology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. 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

2 authors.

Gunter Haroske
Thomas Schrader

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCurrent terminology systems for structured reporting in pathology are more or less focused on tumor pathology. They have not been compiled in a systematic approach, therefore they gather terms of very different granularity. Generic models for terminology development could help in establishing reference terminologies for all fields of anatomic pathology.

methodsFor each element template of PathLex its possible generic nature and its value set was analyzed, looking for the uniqueness or multiplicity of the values in the value sets.

resultsThe 488 PathLex element templates for Anatomic Pathology (AP) observations can be reduced to 53 generic templates, leaving out only 17 templates very specific for organ and/or disease. Among those 53 templates 28 are describing UICC-TNM staging, ICD-O-classification, and grading. Further 15 templates describe the results from marker investigations. Almost all of the terms, used in those templates could be mapped to SNOMED CT. All of the generic elements have their “organ specific” counterparts by assigning them to one of 20 organs and invasive or noninvasive cancer, respectively. Studying the structure of generic and specific terms it becomes obvious that any AP observation: - occurs always in a context; - consists of three basic elements (target of observation, property of observation, additional qualifiers, added by value sets for coded data).

conclusionsIf a machine-readable terminology is aimed to preserve all the information of native speaking, then two principal solutions exist: - ystematic consideration of all the aspects mentioned above in each single term; - ocusing on the generic elements of terms and combining this with the structure of communication, reflecting the non-obvious elements of the terminology. The fastest way for establishing an interface terminology is the first approach, which lists all of the terms needed for e.g. a checklist in a comprehensive manner (precoordination).

Indexed as

Models, AnatomicPathology, ClinicalHumansResearch ReportSystematized Nomenclature of MedicineTerminology as Topic

Identifiers

PMID25565606
PMCPMC4305974

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.