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Case definitions in Swedish register data to identify systemic lupus erythematosus
1Clinical Epidemiology Unit, Department of Medicine, Solna Karolinska Institute, Stockholm.
Department of Clinical Sciences, Lund University, Lund.
Department of Medical Sciences, Science for Life Laboratories, Uppsala University, Uppsala.
Rheumatology Unit, Department of Medicine, Karolinska University Hospital, Karolinska Institute, Stockholm.
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2016 (Engelska)Ingår i: BMJ Open, ISSN 2044-6055, E-ISSN 2044-6055, Vol. 6, nr 1Artikel i tidskrift (Refereegranskat) Published
Abstract [en]

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.

Ort, förlag, år, upplaga, sidor
B M J Group , 2016. Vol. 6, nr 1
Nationell ämneskategori
Reumatologi och inflammation
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URN: urn:nbn:se:liu:diva-124005DOI: 10.1136/bmjopen-2015-007769ISI: 000369993900007PubMedID: 26729375OAI: oai:DiVA.org:liu-124005DiVA, id: diva2:895007
Anmärkning

Funding agencies:  Strategic Research Programme in Epidemiology at Karolinska Institute; Stockholm County Council; Swedish Research Council; Swedish Heart-Lung Foundation; Swedish Rheumatism Foundation; King Gustaf V 80-year Foundation

Tillgänglig från: 2016-01-18 Skapad: 2016-01-18 Senast uppdaterad: 2017-11-30Bibliografiskt granskad

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