ArticleiScience2025
Real-time data in cancer registries: Validation of an automated data extraction system.
Article in iScience, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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
5 citing papers in PubMed.
- Feasibility of a prospective real-time monitoring system capturing real-world data from elderly patients with acute myeloid leukemia.ESMO real world data and digital oncology · 2026Article
- Creation of a Retinoblastoma Registry in a Resource-Limited Country in Sub-Saharan Africa.Cancer medicine · 2026Article
- The role of artificial intelligence in advancing population-based cancer registration.Science bulletin · 2026Review
- Real-world evidence on data quality in precision oncology platforms: insights from the Molecular Twin Research Umbrella protocol.Frontiers in digital health · 2026Article
- The intersection of health information management and clinical registries.Health information management : journal of the Health Information Management Association of Australia · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
13 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Timely surveillance of cancer treatment requires real-time integration of electronic health records (EHR) data into population-based registries. We validated data from the Datagateway, an automated system that harmonizes structured EHR data across hospitals into a common model to support near real-time enrichment of the Netherlands Cancer Registry (NCR). Data from patients with acute myeloid leukemia, multiple myeloma, lung cancer, and breast cancer were extracted via the Datagateway and compared to NCR data and EHR source data. The system achieved 100% accuracy compared to registered NCR diagnoses, and an accuracy of 95% when comparing new diagnoses to the NCR inclusion criteria. Treatment was correctly identified in all cases, with only 3% of combination therapies misclassified. Laboratory values matched virtually completely; toxicity indicators showed 72%-100% accuracy. Automated real-time EHR data integration using a harmonized model is feasible and reliable, enabling scalable, high-quality support for real-world oncology research.
Indexed as
Identifiers
What Socratic 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 Socratic graph.