Evidence map›Paper›PMID 38893186›Full record

ArticleCancers2024

Transforming a Large-Scale Prostate Cancer Outcomes Dataset to the OMOP Common Data Model-Experiences from a Scientific Data Holder's Perspective.

Nora Tabea Sibert, Johannes Soff, Sebastiano La Ferla, Maria Quaranta, Andreas Kremer, Christoph Kowalski

Abstract read
In one paragraph

Article in Cancers, 2024. 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

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

2 citing papers in PubMed.

  1. Article
  2. 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

6 authors.

Nora Tabea SibertHealth Services Research Department, German Cancer Society, 14057 Berlin, Germany.
Johannes SoffHealth Services Research Department, German Cancer Society, 14057 Berlin, Germany.ORCID 0000-0003-0515-9013
Sebastiano La FerlaITTM SA, Esch-sur-Alzette, 4354 Esch-sur-Alzette, Luxembourg.
Maria QuarantaITTM SA, Esch-sur-Alzette, 4354 Esch-sur-Alzette, Luxembourg.
Andreas KremerITTM SA, Esch-sur-Alzette, 4354 Esch-sur-Alzette, Luxembourg.ORCID 0000-0003-1466-0600
Christoph KowalskiHealth Services Research Department, German Cancer Society, 14057 Berlin, Germany.ORCID 0000-0002-7438-4321

Funding

This research was funded by an IMI EHDEN sub-grant for Data Partner call (EHDEN funding number: 806968). 806968
6 · The paper itself

Abstract

To enhance international and joint research collaborations in prostate cancer research, data from different sources should use a common data model (CDM) that enables researchers to share their analysis scripts and merge results. The OMOP CDM maintained by OHDSI is such a data model developed for a federated data analysis with partners from different institutions that want to jointly investigate research questions using clinical care data. The German Cancer Society as the scientific lead of the Prostate Cancer Outcomes (PCO) study gathers data from prostate cancer care including routine oncological care data and survey data (incl. patient-reported outcomes) and uses a common data specification (called OncoBox Research Prostate) for this purpose. To further enhance research collaborations outside the PCO study, the purpose of this article is to describe the process of transferring the PCO study data to the internationally well-established OMOP CDM. This process was carried out together with an IT company that specialised in supporting research institutions to transfer their data to OMOP CDM. Of n = 49,692 prostate cancer cases with 318 data fields each, n = 392 had to be excluded during the OMOPing process, and n = 247 of the data fields could be mapped to OMOP CDM. The resulting PostgreSQL database with OMOPed PCO study data is now ready to use within larger research collaborations such as the EU-funded EHDEN and OPTIMA consortium.

Indexed as

data harmonisationobservational datasetOMOP CDMprostate cancer

Identifiers

PMID38893186
PMCPMC11171220

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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.