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 above-mentioned registries for all persons registered with pheochromocytoma or catecholamine-hypersecretion in Denmark 1977-2016 (average population 5.30 million). We then reviewed health records for all persons living in the North and Central Denmark Regions (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 (PPV) and completeness. The best algorithm was subsequently validated in an external sample. Results: We identified 2626 persons with a PPGL diagnosis code in Denmark, including 787 (30.0%) in the North and Central Denmark Regions. In this subsample, we retrieved the health records of 771/787 (98.0%) persons 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% 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 a 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; ICD; SNOMED; hospital register diagnoses; pathology register; cause of death register