Related Experiment Video
Updated: May 3, 2026

Competing-Risk Nomogram for Predicting Cancer-Specific Survival in Multiple Primary Colorectal Cancer Patients after Surgery
Published on: September 27, 2024
Identification of patients with incident cancers using administrative registry data
Mette Bach Larsen1, Henry Jensen, Rikke Pilegaard Hansen
1Forskningsenheden for Almen Praksis, Aarhus Universitet, Bartholins Allé, Bygn. 1260, 8000 Aarhus C, Denmark. mette.bach.larsen@alm.au.dk.
Introduction:
On-time identification of incident cancer patients is important in cancer research to ensure quality in cancer treatment and care. Nevertheless, the Danish Cancer Registry (DCR) is updated on an annual basis rather than continuously, and no standardised algorithm exists to enable sampling from administrative data which are updated on a monthly basis. The aim of this study was to develop and validate an algorithm for on-time sampling of incident cancer patients based on administrative data.
Material And Methods:
The study was based on registry and questionnaire data from incident cancer patients' general practitioners (GPs). An algorithm for on-time sampling of incident cancer patients was developed and validated in 2008 (12,747 patients) and further developed and validated in 2010 (7,996 patients). Questionnaire data from the GPs and data from the DCR were used as gold standards. The completeness over time of the 2010 cohort was evaluated.
Results:
Further development of the 2008 algorithm into the 2010 algorithm increased its positive predictive value (PPV) to 95.0%. The PPV of a patient from the 2010 cohort being registered in the DCR was 97.4%. The 2010 algorithm displayed a completeness of 60% in the first month and 95% after four months.
Conclusion:
A valid and cost-saving algorithm for on-time sampling of incident cancer patients has been developed with great potential for research and quality assurance.
Funding:
This work was funded by the Danish Cancer Society and the Novo Nordisk Foundation.
Trial Registration:
not relevant.
More Related Videos
07:13Comparison of Predictive Performance of Three Lymph Node Staging Systems in Colorectal Signet Ring Cell Carcinoma Based on Machine Learning Model
Published on: April 18, 2025
07:41Performing Data Mining And Integrative Analysis Of Biomarker in Breast Cancer Using Multiple Publicly Accessible Databases
Published on: May 17, 2019
Related Concept Videos
Cancer Survival Analysis
Statistical Methods for Analyzing Epidemiological Data
Cancer Prevention
Some...
Kaplan-Meier Approach
Hazard Ratio
For example, in a clinical trial...
Documentation of Nursing Diagnosis
In some settings, data-driven computerized decision support systems are in place, allowing for more accurate nursing diagnoses. The database within one of these systems includes diagnostic labels defining characteristics, activities, and indicators for nursing. A nurse enters...