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ORIGINAL RESEARCH

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

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Pages 241-250 | Received 03 Nov 2022, Accepted 20 Feb 2023, Published online: 27 Feb 2023
 

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 (TTRMedical_chart-TTRalgorithm) was −8 days (IQR: −21 to +3 days). Restricting the algorithm to chemotherapy codes from oncology departments increased the positive predictive value from 87% to 94% without changing the negative predictive value (99%).

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.

Abbreviations

CRC, colorectal cancer; TTR, time to recurrence; DCCG, Danish Colorectal Cancer Group; DCR, Danish Cancer Registry, DNPR, Danish National Patient Registry; DPR, Danish Pathology Registry; CRS, Civil Registration System; NMSC, non-melanoma skin cancer; IQR, interquartile range; RECORD, The REporting of studies Conducted using Observational Routinely-collected health Data.

Acknowledgments

We would like to extend our gratitude to the Danish Colorectal Cancer Group (DCCG) for providing data from the national colorectal cancer database. The registry and clinical data used in this study is considered personal and protected patient data, in accordance with the Danish Data Protection act and the General Data Protection Regulations, and therefore cannot be disclosed.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

Mr Jesper Nors reports personal fees from Aarhus University, during the conduct of the study. Prof. Dr Claus Lindbjerg Andersen reports grants from The Novo Nordic Foundation and The Danish Cancer Society, during the conduct of the study. The authors report no other conflicts of interest in this work.

Additional information

Funding

This study was funded by a PhD scholarship from Institute of Clinical Medicine, Aarhus University (Nors) and supported by the Danish Cancer Society [grant numbers R133-A8520-00-S41, R146-A9466-16-S2, R231-A13845, R257-A14700, R307-A17932 (Andersen)] and the Novo Nordisk Foundation [grant number NNF17OC0025052 (Andersen)].