title: Case definitions in Swedish register data to identify systemic lupus erythematosus.
abstract: OBJECTIVE
  To develop and investigate the utility of several different case definitions for systemic lupus erythematosus (SLE) using national register data in Sweden.
  
  
  METHODS
  The reference standard consisted of clinically confirmed SLE cases pooled from four major clinical centres in Sweden (n=929), and a sample of non-SLE comparators randomly selected from the National Population Register (n=24,267). Demographics, comorbidities, prescriptions and autoimmune disease family history were obtained from multiple registers and linked to the reference standard. We first used previously published SLE definitions to create algorithms for SLE. We also used modern data mining techniques (penalised least absolute shrinkage and selection operator logistic regression, elastic net regression and classification trees) to objectively create data-driven case definitions. Sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) were calculated for the case definitions identified.
  
  
  RESULTS
  Defining SLE by using only hospitalisation data resulted in the lowest sensitivity (0.79). When SLE codes from the outpatient register were included, sensitivity and PPV increased (PPV between 0.97 and 0.98, sensitivity between 0.97 and 0.99). Addition of medication information did not greatly improve the algorithm's performance. The application of data mining methods did not yield different case definitions.
  
  
  CONCLUSIONS
  The use of SLE International Classification of Diseases (ICD) codes in outpatient clinics increased the accuracy for identifying individuals with SLE using Swedish registry data. This study implies that it is possible to use ICD codes from national registers to create a cohort of individuals with SLE.
authors.affiliation: Clinical Epidemiology Unit, Department of Medicine, Solna Karolinska Institute, Stockholm, Sweden.
authors.forename: Elizabeth V
authors.initials: EV
authors.lastname: Arkema
authors.affiliation: Department of Clinical Sciences, Lund University, Lund, Sweden.
authors.forename: Andreas
authors.initials: A
authors.lastname: Jönsen
authors.affiliation: Department of Medical Sciences, Science for Life Laboratories, Uppsala University, Uppsala, Sweden.
authors.forename: Lars
authors.initials: L
authors.lastname: Rönnblom
authors.affiliation: Rheumatology Unit, Department of Medicine, Karolinska University Hospital, Karolinska Institute, Stockholm, Sweden.
authors.forename: Elisabet
authors.initials: E
authors.lastname: Svenungsson
authors.affiliation: Rheumatology/AIR, Department of Clinical and Experimental Medicine, Linköping University, Linköping, Sweden.
authors.forename: Christopher
authors.initials: C
authors.lastname: Sjöwall
authors.affiliation: Clinical Epidemiology Unit, Department of Medicine, Solna Karolinska Institute, Stockholm, Sweden Division of Epidemiology, Department of Health Research and Policy, Stanford School of Medicine, Stanford, California, USA Division of Immunology and Rheumatology, Department of Medicine, Stanford School of Medicine, Stanford, California, USA.
authors.forename: Julia F
authors.initials: JF
authors.lastname: Simard
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D016208:Databases, Factual; D006760:Hospitalization; D006801:Humans; D038801:International Classification of Diseases; D008180:Lupus Erythematosus, Systemic / Q000175:diagnosis*; D008875:Middle Aged; D012042:Registries; D012680:Sensitivity and Specificity; D013548:Sweden
keywords: EPIDEMIOLOGY; RHEUMATOLOGY; STATISTICS & RESEARCH METHODS