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Validation of an algorithm to ascertain late breast cancer recurrence using danish medical registries

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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.

In: Clinical epidemiology, Vol. 12, 10.2020, p. 1083-1093.

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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. In: Clinical epidemiology. 2020 ; Vol. 12. pp. 1083-1093.

Bibtex

@article{c5af6936191e4b8595c7b396bc1fe350,
title = "Validation of an algorithm to ascertain late breast cancer recurrence using danish medical registries",
abstract = "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.",
keywords = "Algorithm, Breast cancer neoplasm, Late breast cancer recurrence, PPV, Sensitivity",
author = "Pedersen, {Rikke N{\o}rgaard} and Buket {\"O}zt{\"u}rk and Lene Mellemkj{\ae}r and S{\o}ren Friis and Trine Tramm and Mette N{\o}rgaard and Cronin-Fenton, {Deirdre P.}",
year = "2020",
month = oct,
doi = "10.2147/CLEP.S269962",
language = "English",
volume = "12",
pages = "1083--1093",
journal = "Clinical Epidemiology",
issn = "1179-1349",
publisher = "Dove Medical Press Ltd.",

}

RIS

TY - JOUR

T1 - Validation of an algorithm to ascertain late breast cancer recurrence using danish medical registries

AU - Pedersen, Rikke Nørgaard

AU - Öztürk, Buket

AU - Mellemkjær, Lene

AU - Friis, Søren

AU - Tramm, Trine

AU - Nørgaard, Mette

AU - Cronin-Fenton, Deirdre P.

PY - 2020/10

Y1 - 2020/10

N2 - 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.

AB - 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.

KW - Algorithm

KW - Breast cancer neoplasm

KW - Late breast cancer recurrence

KW - PPV

KW - Sensitivity

UR - http://www.scopus.com/inward/record.url?scp=85092462939&partnerID=8YFLogxK

U2 - 10.2147/CLEP.S269962

DO - 10.2147/CLEP.S269962

M3 - Journal article

C2 - 33116902

AN - SCOPUS:85092462939

VL - 12

SP - 1083

EP - 1093

JO - Clinical Epidemiology

JF - Clinical Epidemiology

SN - 1179-1349

ER -