ArticleBMC medical research methodology2024
A database for oncological research and quality assurance: implementation and first experiences with the University Clinical Cancer Registry Regensburg.
Article in BMC medical research methodology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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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.
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.
Who cites it
1 citing paper in PubMed.
- Development of a digitalization concept for assessing patient-reported outcomes in the context of a University Cancer Center - a model for use in clinical routine.Journal of patient-reported outcomes · 2025Article
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Authors and funding
11 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Legal requirements, certification specifications, as well as the demand for real world data on cancer research and treatment led to the decision to establish the University Clinical Cancer Registry Regensburg. The first organizational step in the implementation process of this oncological data registry was the evaluation and acquisition of suitable tumor documentation and database software. For this purpose, an evaluation matrix comprising required database software criteria was designed and consented by a multidisciplinary group of experts. Next, a yearly report of the Institute for Cancer Center Certification (OnkoZert 2019) was considered to identify database software already in use. The identified systems were rated according to the established criteria matrix and other relevant aspects. Onkostar was the system considered most suited for building up an oncological data repository. In the second step, the central IT department implemented Onkostar on-premise and migrated digitally available data after an adaptation and verification process. In parallel, a uniformed process for handling emerging oncological research questions was established. For research requirements, a data analysis concept was established comprising a proposal for data extraction, procedural instructions, and statistical training materials. In the final step, the implemented software and the process for handling research requirements in practice were evaluated by using two exemplary use cases with the focus on clinic-wide analyses and currently relevant scientific topics. A 2-month test phase conducted by various user groups showed a preference for Onkostar tumor documentation software from IT-Choice, mainly because of its adjustability to support research and treatment. Newly added and migrated data can be used for certification and research purposes. This software also provides support in current tumor documentation by displaying the course of cancer disease for individual patients over time. Such oncological data registries can be a powerful tool for legally required cancer registration, the certification of medical centers, as well as for additional oncological research. Tumor databases can be helpful in projects on cancer treatment and scientific aims. The experiences made at the University Hospital Regensburg may be used as a guidance for implementing clinical databases in similar settings with interdisciplinary responsibilities.
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Registered trials
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.