title: How Suitable Are Registry Data for Recurrence Risk Calculations? Validation of Diagnoses on 1,593 Families With Congenital Heart Disease.
abstract: BACKGROUND
  Congenital heart disease (CHD) occurs in approximately 1% of all live births, and 3% to 8% of these have until now been considered familial cases, defined as the occurrence of two or more affected individuals in a family. The validity of CHD diagnoses in Danish administrative registry data has only been studied previously in highly selected patient populations. These studies identified high positive predictive values (PPVs) and recurrence risk ratios (RRRs-ratio between probabilities of CHD given family history of CHD and no family history). However, the RRR can be distorted if registry data are used indiscriminately. Here, we investigated the consequences of misclassifications for the RRR using validated diagnoses on Danish patients with familial CHD.
  
  
  METHODS
  Danish citizens are assigned a civil registration number (CPR number) at birth or immigration, which acts as a unique identifier in the Danish registries, thus enabling connection of information from several registries. Utilizing the CPR number, we identified Danish patients with familial CHD and reviewed each patient's file. We compared diagnoses from the registries with those manually assigned, which enabled calculation of the PPVs of diagnoses in the Danish registries, and from this, we deduced the false discovery rate (FDR). To measure the consequences on the RRR, the FDR was applied to a simulated data set with true RRR values of 2 and 10.
  
  
  RESULTS
  We validated diagnoses of 2,442 patients from 1,593 families. Of these, 874 patients were misclassified corresponding to an FDR of 36%. Applying this FDR on the simulated data sets, we found that the RRR decreased from 2 and 10 to 1.4 and 5.1, respectively. Lastly, we estimated that 11% of all cases with CHD were familial.
  
  
  CONCLUSIONS
  We found that approximately one of nine of all cases with CHD are familial, and we also found that 36% of individuals with CHD in administrative medical registries are misclassified, which distort the RRR in simulated scenarios.
authors.affiliation: Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark sabrina.ellesoe@cpr.ku.dk soren.brunak@cpr.ku.dk.
authors.forename: Sabrina Gade
authors.initials: SG
authors.lastname: Ellesøe
authors.affiliation: Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Anders Boeck
authors.initials: AB
authors.lastname: Jensen
authors.affiliation: Institute of Preventive Medicine, Frederiksberg and Bispebjerg Hospital, Frederiksberg, Denmark.
authors.forename: Lars Henrik
authors.initials: LH
authors.lastname: Ängquist
authors.affiliation: Department of Cardiothoracic and Vascular Surgery, Aarhus University Hospital, Aarhus, Denmark.
authors.forename: Vibeke Elisabeth
authors.initials: VE
authors.lastname: Hjortdal
authors.affiliation: Department of Cellular and Molecular Medicine, Wilhelm Johannsen Center for Functional Genome Research, University of Copenhagen, Copenhagen, Denmark.
authors.forename: Lars Allan
authors.initials: LA
authors.lastname: Larsen
authors.affiliation: Novo Nordisk Foundation Center for Protein Research, University of Copenhagen, Copenhagen, Denmark sabrina.ellesoe@cpr.ku.dk soren.brunak@cpr.ku.dk.
authors.forename: Søren
authors.initials: S
authors.lastname: Brunak
mesh_terms: D000068598:Data Accuracy; D003718:Denmark; D020022:Genetic Predisposition to Disease; D006330:Heart Defects, Congenital / Q000175:diagnosis / Q000235:genetics*; D006801:Humans; D016017:Odds Ratio; D012042:Registries / Q000592:standards*; D018570:Risk Assessment
keywords: adult congenital heart disease; cardiology; congenital heart disease (CHD); statistics