ArticlePathologie (Heidelberg, Germany)2026
[Pathology data in spatial epidemiology (REDPath) : A web-based application for oncology and service planning].
Article in Pathologie (Heidelberg, Germany), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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.
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
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundPathological routine diagnostics generate extensive datasets, yet their potential for spatial epidemiological analyses-for instance for studying disease distributions, environmental exposures, or healthcare structures-has so far remained largely untapped.
objectiveWith REDPath (Spatial Epidemiological Data Analysis of Pathology Data), a web-based tool to unlock this data source has been developed. Its goal is to visualize oncological disease burden and healthcare provision across different geographic levels, thereby supporting data-driven prevention and resource allocation strategies. MATERIALS AND
methodsThe basis consists of 41,707 oncological diagnoses (ICD-10: C00-C97, 2019-2025) from the Institute of Pathology, University Medical Center Mainz, supplemented by demographic and environmental context variables. REDPath was programmed in C++ and Python; visualizations were generated with Leaflet and statistical analyses were performed in R using the lme4 and CARBayes packages. Data were processed on two levels (individual/aggregated) to ensure data protection and differentiated access rights.
resultsREDPath comprises three modules: (1) descriptive analyses for interactive visualization of disease distributions; (2) statistical models to examine spatial relationships and autocorrelations; and (3) a health services module currently in development, visualizing submitting institutions.
conclusionREDPath enables spatial epidemiological analysis of routine pathology data-in a user-friendly and accessible manner without statistical expertise. Its modular structure allows for the integration of additional disease entities and data sources, positioning the tool as an interface between pathology and epidemiology, with direct relevance for evidence-based healthcare planning.
Indexed as
Identifiers
What OpenQuestion holds
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.