SynthesisEuropean journal of epidemiology2026
Quality of cancer-related data from the Danish National patient registry (1994-2025) and the Danish cancer registry (2004-2025): a systematic review.
Synthesis in European journal of epidemiology, 2026. 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
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
1 citing paper in PubMed.
- Comprehensive, near real-time national systemic anti-cancer therapy (SACT) data: descriptive study of implementation and applications in Scotland (UK) from 2014.ESMO real world data and digital oncology · 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
5 authors.
Funding
Abstract
The Danish National Patient Registry (DNPR) and the Danish Cancer Registry (DCR) are central to registry-based cancer research. This systematic review evaluates studies assessing the quality of cancer-related data in these registries under their current data structures. PubMed and Embase were systematically searched on January 24, 2025 (PROSPERO: CRD420251005952). Studies validating cancer-related data in the DNPR or DCR against a gold standard were included. Findings were synthesized narratively and categorized by DNPR data, DCR data, or multi-source algorithms. The literature search generated 915 records, of which 50 were included: 23 validated DNPR data, 9 DCR data, and 18 algorithm performance. The quality of DNPR cancer diagnoses and treatment showed positive predictive values (PPVs) of 57-100%, highest for common malignancies and treatments. The quality of DNPR comorbidities and complications varied substantially (PPVs 0-98%). The PPV of a melanoma diagnosis in the DCR was 97%. The DCR staging completeness varied considerably (34-95%). Algorithms presented PPVs of 60-96% for recurrence, active cancer, and recognized metastases, and 28% for unrecognized metastases. The DNPR and DCR provide high-quality data for many cancer diagnoses, treatments, and outcomes, supporting their use in register-based research. While some data elements, including data on complications, exhibit lower quality, algorithmic approaches can enhance utility for less robust data. However, several aspects of cancer-related data remain unvalidated.
Indexed as
Identifiers
41524884What 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.