ArticleBMJ open2026
Temporal trends in epidemiology and patient characteristics of 36 cancers: a protocol for a multinational population-based cohort study using OMOP-standardised databases to investigate CANcer (OMOPCAN).
Article in BMJ open, 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
37 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
introductionCancer registries remain the gold standard for global cancer monitoring, yet complementing them with electronic health records and claims can significantly enhance the understanding of the cancer burden by providing a more complete picture of the patient journey. The main aim of this project is to serve as a proof of concept for using real-world data mapped to the Observational Medical Outcomes Partnership (OMOP) common data model (CDM) to monitor cancer epidemiology over time and characterise patients' clinical history and outcomes. METHODS AND ANALYSIS: This study will be conducted as an observational cohort study using a multinational network of large real-world data sources mapped to the OMOP CDM. Electronic health records (EHR) from primary and secondary care, health insurance claims and cancer registry data will be included. To date, 20 databases from 16 countries, mainly from Europe but also North America and Asia, have committed to participate in the project.We will investigate the temporal trends in incidence, prevalence and survival of 36 cancers across haematopoietic and solid tumours from 2000 (or the start of accurate data if later) to the last year with complete data. Data from all individuals registered in each of the participating data sources will be eligible for inclusion in the study. For primary care EHR and claims, individuals will be required to have at least 1 year of prior observation to ensure the identification of incident cases and adequate capture of patient characteristics. We will estimate crude and age-standardised incidence and 5-year partial prevalence. Additionally, we will estimate crude and age-standardised overall survival at 1, 5 and 10 years for the total study period and by diagnosis year groups defined according to data availability. All study objectives will be investigated at the database level, with results stratified by age and sex. For incidence and survival analyses, additional stratifications will be performed by clinical conditions and smoking status (where available). We will use the National Cancer Institute (NCI) Joinpoint Regression Programme to model overall trends in cancer incidence and the NCI JPSurv software to estimate trends in survival. Finally, we will characterise individuals diagnosed with an incident cancer based on demographics, clinical conditions and medication use at different time windows.Findings will be presented separately for each database and further summarised through descriptive aggregation by country and data source type. ETHICS AND DISSEMINATION: Each data partner will obtain study approval from their local institutional review boards prior to study execution. Distributed queries will be employed, whereby standardised analytical code is shared and run at each site locally. Deidentified, aggregated results will be returned from all participating sites. A minimum cell count of five will be used when reporting results, depending on each collaborator's data governance requirements.All study code will be publicly available, and findings will be submitted to open science journals to promote transparency and reproducibility.
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.