Validation of an Algorithm to Ascertain Late Breast Cancer Recurrence Using Danish Medical Registries
| Autor: | Rikke Nørgaard Pedersen, Lene Mellemkjær, Mette Nørgaard, Deirdre Cronin-Fenton, Søren Friis, Trine Tramm, Buket Öztürk |
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| Rok vydání: | 2020 |
| Předmět: |
Epidemiology
Breast cancer recurrence business.industry Medical record Cancer 030204 cardiovascular system & hematology medicine.disease language.human_language Cancer registry Danish 03 medical and health sciences 0302 clinical medicine Breast cancer language Medicine 030212 general & internal medicine Medical diagnosis Stage (cooking) business Algorithm |
| Zdroj: | Clinical Epidemiology. 12:1083-1093 |
| ISSN: | 1179-1349 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
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