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Article

Validation in Alberta of an Administrative Data Algorithm to Identify Cancer Recurrence

1
Department of Obstetrics and Gynecology, University of Calgary, Calgary, AB, Canada
2
Cancer Research and Analytics, CancerControl Alberta, Alberta Health Services, Calgary, AB, Canada
*
Author to whom correspondence should be addressed.
Curr. Oncol. 2020, 27(3), 343-346; https://doi.org/10.3747/co.27.5861
Submission received: 6 March 2020 / Revised: 7 April 2020 / Accepted: 10 May 2020 / Published: 1 June 2020

Abstract

Background: Readily available population-based data about cancer recurrence would improve surveillance and research for women of reproductive age. Methods: We randomly selected 200 women from the Alberta Cancer Registry who had received a cancer diagnosis and who ever had a pregnancy between 2003 and 2012. Administrative data were obtained and linked. Several definitions of recurrence were assessed using various minimum lengths of time between the initial diagnosis date and subsequent diagnoses or treatments, or both. Chart review was used as a “gold standard” definition of recurrence. Results: Chart review identified recurrences in 26 women. The definition that best captured “recurrence” was 2 or more cancer diagnosis codes 10 or more months from the diagnosis date [sensitivity: 80.8%; 95% confidence interval (ci): 60.7% to 93.5%; specificity: 81.0%; 95% ci: 74.4% to 86.6%; positive predictive value: 38.9%; 95% ci: 25.9% to 53.1%; negative predictive value: 96.6%; 95% ci: 92.2% to 98.9%; kappa = 0.42; 95% ci: 0.28 to 0.57]. Conclusions: Recurrence in reproductive-aged women can be captured with moderate validity using administrative data, but should be interpreted with caution.
Keywords: recurrence; breast cancer; validation; administrative data; registries recurrence; breast cancer; validation; administrative data; registries

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MDPI and ACS Style

Cairncross, Z.F.; Nelson, G.; Shack, L.; Metcalfe, A. Validation in Alberta of an Administrative Data Algorithm to Identify Cancer Recurrence. Curr. Oncol. 2020, 27, 343-346. https://doi.org/10.3747/co.27.5861

AMA Style

Cairncross ZF, Nelson G, Shack L, Metcalfe A. Validation in Alberta of an Administrative Data Algorithm to Identify Cancer Recurrence. Current Oncology. 2020; 27(3):343-346. https://doi.org/10.3747/co.27.5861

Chicago/Turabian Style

Cairncross, Z.F., G. Nelson, L. Shack, and A. Metcalfe. 2020. "Validation in Alberta of an Administrative Data Algorithm to Identify Cancer Recurrence" Current Oncology 27, no. 3: 343-346. https://doi.org/10.3747/co.27.5861

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