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

Rikke Nørgaard Pedersen,1 Buket Öztürk,1 Lene Mellemkjær,2 Søren Friis,2 Trine Tramm,3 Mette Nørgaard,1 Deirdre P Cronin-Fenton1 1Department of Clinical Epidemiology, Aarhus University, Aarhus, Denmark; 2Danish Cancer Society Research Center, Copenhagen, Denmark; 3Department of Pathology, Aarhus University Hospital, Aarhus, DenmarkCorrespondence: Rikke Nørgaard PedersenDepartment of Clinical Epidemiology, Aarhus University, Aarhus, DenmarkTel +4587167212Email rikp@clin.au.dkPurpose: 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, late breast cancer recurrence, breast cancer neoplasm, PPV, sensitivity