Evidence map›Paper›PMID 41379764›Full record

ArticleOncology2026

Development of a Rule-Based Knowledge Base for Digitalization of Standard Operating Procedures on Radiotherapy in Breast Cancer.

Fabio Dennstädt, Johannes Zink, Nikola Cihoric, Dagmar Weder, Markus Glatzer, Julie Crommelinck, Krisztian Süveg, Galina Farina Fischer, Hông-Linh Hà, Detlef Brügge and 2 more

Abstract read
In one paragraph

Article in Oncology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

12 authors.

Fabio DennstädtDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland, fabio.dennstaedt@insel.ch.
Johannes ZinkTUM School of Computation, Information and Technology (CIT), Technical University of Munich, Heilbronn, Germany.
Nikola CihoricDepartment of Radiation Oncology, Inselspital, Bern University Hospital, University of Bern, Bern, Switzerland.
Dagmar WederDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Markus GlatzerDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Julie CrommelinckDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Krisztian SüvegDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Galina Farina FischerDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Hông-Linh HàDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Detlef BrüggeDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Ludwig PlassilmDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.
Paul Martin PutoraDepartment of Radiation Oncology, HOCH, Cantonal Hospital St.Gallen, St. Gallen, Switzerland.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

<p>Introduction: Traditional text-based standard operating procedures (SOPs) have limitations in today's data-rich environment, as they provide limited support for automated reasoning, contextual guidance, and real-time clinical decision-making. We developed a rule-based knowledge base to overcome these challenges through digitalization of SOPs on breast cancer radiotherapy.

methodsWe designed and developed a web application with a relational database structured around common data elements, a rule-based inference engine, and a responsive user interface (UI). The system's information retrieval success was evaluated in a single-center study over 14 months, where nine radiation oncologists submitted clinical queries and provided feedback on the relevance of the results.

resultsThe knowledge base incorporated 103 specific information entries covering 8 main topics, structured around critical clinicopathological features such as tumor stage, receptor status, grading, and lymphovascular invasion. During a 14-month testing period, nine radiation oncologists submitted 62 distinct clinical queries (e.g., determining boost indication for a patient of certain age and tumor situation). Of these queries, 56.5% were successfully answered as indicated by the user. Analysis of unsuccessful queries revealed that the information was mostly present but inaccessible due to user experience issues.

conclusionOur rule-based knowledge base demonstrates the feasibility of transforming static SOPs into interactive, evidence-linked resources. While promising, substantial user experience barriers remain. Future enhancements will prioritize UI improvements, sustainable knowledge-updating mechanisms, and AI integration to strengthen the system for practical use. </p>.

Indexed as

Breast NeoplasmsKnowledge BasesDatabases, FactualFemaleHumansInternetUser-Computer InterfaceBreast cancerKnowledge baseOncologyRadiation therapyStandard operating procedures

Identifiers

PMID41379764
PMCPMC12810961

What Socratic holds

Textmetadata
LicenceCC BY-NC
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 Socratic graph.