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Cancer Epidemiol. 2019 Apr;59:129-134. doi: 10.1016/j.canep.2019.01.016. Epub 2019 Feb 8.

A validated algorithm for register-based identification of patients with recurrence of breast cancer-Based on Danish Breast Cancer Group (DBCG) data.

Author information

1
Research Centre for Cancer Diagnosis in Primary Care (CaP), Research Unit for General Practice, Bartholins Allé 2, 8000 Aarhus C, Denmark; Department of Public Health, Aarhus University, Bartholins Allé 2, 8000 Aarhus C, Denmark. Electronic address: linda.rasmussen@ph.au.dk.
2
Research Centre for Cancer Diagnosis in Primary Care (CaP), Research Unit for General Practice, Bartholins Allé 2, 8000 Aarhus C, Denmark.
3
Department of Experimental Clinical Oncology, Aarhus University Hospital, Noerrebrogade 44, 8000 Aarhus C, Denmark; Department of Oncology, Aarhus University Hospital, Noerrebrogade 44, 8000 Aarhus C, Denmark.

Abstract

BACKGROUND:

Cancer recurrence is not routinely and completely registered in Danish national health registers, which challenges register-based research. The aim of this study was to develop and validate a register-based algorithm to identify patients with recurrence of breast cancer (BC).

METHODS:

We conducted a cohort study based on data from Danish national health registers and used the Danish National Patient Register and the Danish National Pathology Register as sources to identify BC recurrence. We used data from the Danish Breast Cancer Group (DBCG) validated against medical records on recurrence status and recurrence date for 471 women with early stage unilateral BC as the gold standard of BC recurrence to assess the accuracy of the algorithm to identify BC recurrence.

RESULTS:

The algorithm displayed a sensitivity of 97.3% (95% confidence interval (CI): 93.2-99.3), a specificity of 97.2% (95% CI: 94.8-98.7) and a positive predictive value of 94.4% (95% CI: 89.2-97.3). The concordance correlation coefficient for the agreement between recurrence dates generated by the algorithm and the gold standard was 0.97 (95% CI: 0.96-0.98), and the date was estimated within +/-30 days of the gold standard in 66% of the patients and within +/-60 days in 76% of the patients.

CONCLUSION:

The developed algorithm almost perfectly identified BC recurrence and with reasonable timing compared to the gold standard.

KEYWORDS:

Algorithms; Breast neoplasms; Denmark; Recurrence; Registries; Validation studies

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