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Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries

PURPOSE: About 70% of women with breast cancer survive at least 10 years after diagnosis. We constructed an algorithm to ascertain late breast cancer recurrence—which we define as breast cancer that recurs 10 years or more after primary diagnosis (excluding contralateral breast cancers)—using Danish...

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Autores principales: Pedersen, Rikke Nørgaard, Öztürk, Buket, Mellemkjær, Lene, Friis, Søren, Tramm, Trine, Nørgaard, Mette, Cronin-Fenton, Deirdre P
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7569071/
https://www.ncbi.nlm.nih.gov/pubmed/33116902
http://dx.doi.org/10.2147/CLEP.S269962
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author Pedersen, Rikke Nørgaard
Öztürk, Buket
Mellemkjær, Lene
Friis, Søren
Tramm, Trine
Nørgaard, Mette
Cronin-Fenton, Deirdre P
author_facet Pedersen, Rikke Nørgaard
Öztürk, Buket
Mellemkjær, Lene
Friis, Søren
Tramm, Trine
Nørgaard, Mette
Cronin-Fenton, Deirdre P
author_sort Pedersen, Rikke Nørgaard
collection PubMed
description PURPOSE: About 70% of women with breast cancer survive at least 10 years after diagnosis. We constructed an algorithm to ascertain late breast cancer recurrence—which we define as breast cancer that recurs 10 years or more after primary diagnosis (excluding contralateral breast cancers)—using Danish nationwide medical registries. We used clinical information recorded in medical records as a reference standard. METHODS: Using the Danish Breast Cancer Group clinical database, we ascertained data on 21,134 women who survived recurrence-free 10 years or more after incident stage I–III breast cancer diagnosed in 1987–2004. We used a combination of Danish registries to construct the algorithm—the Danish National Patient Registry for information on diagnostic, therapeutic and procedural codes; and cancer diagnoses from the Danish Pathology Registry, the Danish Cancer Registry and the Contralateral Breast Cancer database. To estimate the positive predictive value (PPV), we selected 105 patients who, according to our algorithm, had late recurrence diagnosed at Aarhus University Hospital. To estimate the sensitivity, specificity and negative predictive value (NPV), we selected 114 patients diagnosed with primary breast cancer at Aalborg University Hospital. We abstracted clinical information on late recurrence for patients with medical record-confirmed late recurrence at Aarhus University Hospital. RESULTS: Our algorithm had a PPV of late recurrence of 85.7% (95% CI: 77.5–91.3%), a sensitivity of 100.0% (95% CI, 39.8–100.0%), a specificity of 97.3 (95% CI, 92.2–99.4) and a NPV of 100% (95% CI, 96.6–100.0%). CONCLUSION: Our algorithm for late recurrence showed a moderate to high PPV and high sensitivity, specificity and negative predictive value. The algorithm could be an important tool for future studies of late breast cancer recurrence.
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spelling pubmed-75690712020-10-27 Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries Pedersen, Rikke Nørgaard Öztürk, Buket Mellemkjær, Lene Friis, Søren Tramm, Trine Nørgaard, Mette Cronin-Fenton, Deirdre P Clin Epidemiol Original Research PURPOSE: About 70% of women with breast cancer survive at least 10 years after diagnosis. We constructed an algorithm to ascertain late breast cancer recurrence—which we define as breast cancer that recurs 10 years or more after primary diagnosis (excluding contralateral breast cancers)—using Danish nationwide medical registries. We used clinical information recorded in medical records as a reference standard. METHODS: Using the Danish Breast Cancer Group clinical database, we ascertained data on 21,134 women who survived recurrence-free 10 years or more after incident stage I–III breast cancer diagnosed in 1987–2004. We used a combination of Danish registries to construct the algorithm—the Danish National Patient Registry for information on diagnostic, therapeutic and procedural codes; and cancer diagnoses from the Danish Pathology Registry, the Danish Cancer Registry and the Contralateral Breast Cancer database. To estimate the positive predictive value (PPV), we selected 105 patients who, according to our algorithm, had late recurrence diagnosed at Aarhus University Hospital. To estimate the sensitivity, specificity and negative predictive value (NPV), we selected 114 patients diagnosed with primary breast cancer at Aalborg University Hospital. We abstracted clinical information on late recurrence for patients with medical record-confirmed late recurrence at Aarhus University Hospital. RESULTS: Our algorithm had a PPV of late recurrence of 85.7% (95% CI: 77.5–91.3%), a sensitivity of 100.0% (95% CI, 39.8–100.0%), a specificity of 97.3 (95% CI, 92.2–99.4) and a NPV of 100% (95% CI, 96.6–100.0%). CONCLUSION: Our algorithm for late recurrence showed a moderate to high PPV and high sensitivity, specificity and negative predictive value. The algorithm could be an important tool for future studies of late breast cancer recurrence. Dove 2020-10-14 /pmc/articles/PMC7569071/ /pubmed/33116902 http://dx.doi.org/10.2147/CLEP.S269962 Text en © 2020 Pedersen et al. http://creativecommons.org/licenses/by-nc/3.0/ This work is published and licensed by Dove Medical Press Limited. The full terms of this license are available at https://www.dovepress.com/terms.php and incorporate the Creative Commons Attribution – Non Commercial (unported, v3.0) License (http://creativecommons.org/licenses/by-nc/3.0/). By accessing the work you hereby accept the Terms. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed. For permission for commercial use of this work, please see paragraphs 4.2 and 5 of our Terms (https://www.dovepress.com/terms.php).
spellingShingle Original Research
Pedersen, Rikke Nørgaard
Öztürk, Buket
Mellemkjær, Lene
Friis, Søren
Tramm, Trine
Nørgaard, Mette
Cronin-Fenton, Deirdre P
Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
title Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
title_full Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
title_fullStr Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
title_full_unstemmed Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
title_short Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
title_sort validation of an algorithm to ascertain late breast cancer recurrence using danish medical registries
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7569071/
https://www.ncbi.nlm.nih.gov/pubmed/33116902
http://dx.doi.org/10.2147/CLEP.S269962
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