ArticleClinical epidemiology2023
Identifying Recurrences Among Non-Metastatic Colorectal Cancer Patients Using National Health Data Registries: Validation and Optimization of a Registry-Based Algorithm in a Modern Danish Cohort.
Article in Clinical epidemiology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 12 citations in OpenAlex.
- The impact of time-to-recurrence on post-recurrence mortality in stage I-III colorectal cancer: A nationwide Danish cohort study.International journal of cancer · 2026Article
- Body mass index and colorectal cancer recurrence and mortality: A nationwide cohort study in Denmark.International journal of cancer · 2026Article
- Detecting cancer recurrence in general practice: a Danish national cohort study.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026Article
- Clinical assessment of recurrent cancer: a Danish cohort study in general practice.The British journal of general practice : the journal of the Royal College of General Practitioners · 2026Article
- Integrating a Shareable Artificial Intelligence Model Into Clinical Research for Cancer Recurrence in Patients With Breast and Colorectal Cancer.JCO clinical cancer informatics · 2025Article
- Refined Algorithm for Identifying Recurrence Among Patients with Non-Metastatic Colorectal Cancer Based on Danish National Health Data Registries.Clinical epidemiology · 2025Article
- Risk of recurrence in early-onset versus late-onset non-metastatic colorectal cancer, 2004-2019: a nationwide cohort study.The Lancet regional health. Europe · 2024Article
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Authors and funding
8 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Purpose: Colorectal cancer (CRC) recurrence is not routinely recorded in Danish health data registries. Here, we aimed to revalidate a registry-based algorithm to identify recurrences in a contemporary cohort and to investigate the accuracy of estimating the time to recurrence (TTR). Patients and Methods: We ascertained data on 1129 patients operated for UICC TNM stage I-III CRC during 2012-2017 registered in the CRC biobank at the Department of Molecular Medicine, Aarhus University Hospital, Denmark. Individual-level data were linked with data from the Danish Colorectal Cancer Group database, Danish Cancer Registry, Danish National Registry of Patients, and Danish Pathology Registry. The algorithm identified recurrence based on diagnosis codes of local recurrence or metastases, the receipt of chemotherapy, or a pathological tissue assessment code of recurrence more than 180 days after CRC surgery. A subgroup was selected for validation of the algorithm using medical record reviews as a reference standard. Results: We found a 3-year cumulative recurrence rate of 20% (95% CI: 17-22%). Manual medical record review identified 80 recurrences in the validation cohort of 522 patients. The algorithm detected recurrence with 94% sensitivity (75/80; 95% CI: 86-98%) and 98% specificity (431/442; 95% CI: 96-99%). The positive and negative predictive values of the algorithm were 87% (95% CI: 78-93%) and 99% (95% CI: 97-100%), respectively. The median difference in TTR (TTR Conclusion: The algorithm detected recurrence and TTR with high precision in this contemporary cohort. Restriction to chemotherapy codes from oncology departments using department classifications improves the algorithm. The algorithm is suitable for use in future observational studies.
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