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Pheochromocytoma in Denmark during 1977–2016: validating diagnosis codes and creating a national cohort using patterns of health registrations

Authors Ebbehoj A, Jacobsen SF, Trolle C, Robaczyk MG, Rasmussen ÅK, Feldt-Rasmussen U, Thomsen RW, Poulsen PL, Stochholm K, Søndergaard E

Received 23 January 2018

Accepted for publication 18 March 2018

Published 13 June 2018 Volume 2018:10 Pages 683—695


Checked for plagiarism Yes

Review by Single anonymous peer review

Peer reviewer comments 3

Editor who approved publication: Professor Henrik Toft Sørensen

Andreas Ebbehoj,1,2 Sarah Forslund Jacobsen,3 Christian Trolle,1 Maciej Grzegorz Robaczyk,4 Åse Krogh Rasmussen,3 Ulla Feldt-Rasmussen,3 Reimar Wernich Thomsen,5 Per Løgstrup Poulsen,1 Kirstine Stochholm,1 Esben Søndergaard1

1Department of Endocrinology and Internal Medicine, Aarhus University Hospital, Aarhus, Denmark; 2Department of Clinical Medicine, Aarhus University, Aarhus, Denmark; 3Department of Endocrinology, Rigshospitalet, Copenhagen, Denmark; 4Department of Endocrinology, Aalborg University Hospital, Aalborg, Denmark; 5Department of Clinical Epidemiology, Aarhus University Hospital, Aarhus, Denmark

Background: Pheochromocytoma and catecholamine-secreting paraganglioma (PPGL) are rare but potentially life-threatening tumors. We aimed to validate diagnosis codes for PPGL in the Danish National Patient Registry, the Danish National Pathology Registry, and the Danish Registry of Causes of Death and to create a national cohort of incident PPGL patients by linking these three registries.
Patients and methods: We obtained data from the three abovementioned registries for all individuals registered with pheochromocytoma or catecholamine hypersecretion in Denmark during 1977–2016 (average population 5.30 million). We then reviewed health records for all individuals living in the North Denmark Region and Central Denmark Region (average population 1.75 million) to validate the diagnosis of PPGL. We tested a number of algorithms for accurately identifying true cases of PPGL to maximize positive predictive values (PPVs) and completeness. The best algorithm was subsequently validated in an external sample.
Results: We identified 2626 individuals with a PPGL diagnosis code in Denmark, including 787 (30.0%) in the North Denmark Region and Central Denmark Region. In this subsample, we retrieved the health records of 771/787 (98.0%) individuals and confirmed 198 incident PPGL patients (25.3%). The PPV of PPGL diagnosis codes was 21.7% in the Danish National Patient Registry, 50.0% in the Danish Registry of Causes of Death, and 79.5% in the Danish National Pathology Registry. By combining patterns of registrations in the three registries, we could increase the PPV to 93.1% (95% confidence interval [CI]: 88.5–96.3) and completeness to 88.9% (95% CI: 83.7–92.9), thus creating a national PPGL cohort of 588 patients. PPV for the optimal algorithm was 95.3% (95% CI: 88.5–98.7) in the external validation sample.
Conclusion: Diagnosis codes for pheochromocytoma had low PPV in several individual health registries. However, with a combination of registries we were able to identify a near-complete national cohort of PPGL patients in Denmark, as a valuable source for epidemiological research.

Keywords: registry-based research, International Classification of Diseases, ICD, Systematized Nomenclature of Medicine, SNOMED, hospital register diagnoses, pathology register, cause of death register

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