Validation of Register-Based Diabetes Classifiers in Danish Data
To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data. After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare...
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          | Published in | Clinical epidemiology Vol. 15; pp. 569 - 581 | 
|---|---|
| Main Authors | , , | 
| Format | Journal Article | 
| Language | English | 
| Published | 
        New Zealand
          Dove Medical Press Limited
    
        01.01.2023
     Dove Dove Medical Press  | 
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| Online Access | Get full text | 
| ISSN | 1179-1349 1179-1349  | 
| DOI | 10.2147/CLEP.S407019 | 
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| Abstract | To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.
After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18-74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the
(OSDC), and 2) an existing Danish diabetes classifier, the
(RSCD). These classifications were validated against self-reported data from the
survey - overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source
package
.
A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730-0.813] (RSCD: 0.700 [0.653-0.744]) and positive predictive value (PPV) 0.943 [0.913-0.966] (RSCD: 0.944 [0.912-0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933-0.953] (RSCD: 0.905 [0.892-0.917]) and PPV 0.875 [0.861-0.888] (RSCD: 0.898 [0.884-0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40.
Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers. | 
    
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| AbstractList | Purpose: To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data. Patients and Methods: After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18-74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifer incorporating diagnostic hemoglobin-A1C measurements, the Open-Source Diabetes Classifer (OSDC), and 2) an existing Danish diabetes classifer, the Register for Selected Chronic Diseases (RSCD). These classifications were validated against self-reported data from the Health in Central Denmark survey - overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source R package osdc. Results: A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730-0.813] (RSCD: 0.700 [0.653-0.744]) and positive predictive value (PPV) 0.943 [0.913-0.966] (RSCD: 0.944 [0.912-0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933-0.953] (RSCD: 0.905 [0.892-0.917]) and PPV 0.875 [0.861-0.888] (RSCD: 0.898 [0.884-0.910]). In age at onsetstratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40. Conclusion: Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers. Keywords: type 1 diabetes, type 2 diabetes, classification, population-based, open-source Anders Aasted Isaksen,1,2 Annelli Sandbæk,1,2 Lasse Bjerg1,2 1Department of Public Health, Aarhus University, Aarhus, Denmark; 2Steno Diabetes Center Aarhus, Aarhus University Hospital, Aarhus N, DenmarkCorrespondence: Anders Aasted Isaksen, Institut for Folkesundhed, Aarhus Universitet, Bartholins Allé 2, Aarhus, 8000, Denmark, Email aai@ph.au.dkPurpose: To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.Patients and Methods: After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18– 74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the Open-Source Diabetes Classifier (OSDC), and 2) an existing Danish diabetes classifier, the Register for Selected Chronic Diseases (RSCD). These classifications were validated against self-reported data from the Health in Central Denmark survey – overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source R package osdc.Results: A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730– 0.813] (RSCD: 0.700 [0.653– 0.744]) and positive predictive value (PPV) 0.943 [0.913– 0.966] (RSCD: 0.944 [0.912– 0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933– 0.953] (RSCD: 0.905 [0.892– 0.917]) and PPV 0.875 [0.861– 0.888] (RSCD: 0.898 [0.884– 0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40.Conclusion: Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers.Keywords: type 1 diabetes, type 2 diabetes, classification, population-based, open-source To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.PurposeTo validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18-74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the Open-Source Diabetes Classifier (OSDC), and 2) an existing Danish diabetes classifier, the Register for Selected Chronic Diseases (RSCD). These classifications were validated against self-reported data from the Health in Central Denmark survey - overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source R package osdc.Patients and MethodsAfter linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18-74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the Open-Source Diabetes Classifier (OSDC), and 2) an existing Danish diabetes classifier, the Register for Selected Chronic Diseases (RSCD). These classifications were validated against self-reported data from the Health in Central Denmark survey - overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source R package osdc.A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730-0.813] (RSCD: 0.700 [0.653-0.744]) and positive predictive value (PPV) 0.943 [0.913-0.966] (RSCD: 0.944 [0.912-0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933-0.953] (RSCD: 0.905 [0.892-0.917]) and PPV 0.875 [0.861-0.888] (RSCD: 0.898 [0.884-0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40.ResultsA total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730-0.813] (RSCD: 0.700 [0.653-0.744]) and positive predictive value (PPV) 0.943 [0.913-0.966] (RSCD: 0.944 [0.912-0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933-0.953] (RSCD: 0.905 [0.892-0.917]) and PPV 0.875 [0.861-0.888] (RSCD: 0.898 [0.884-0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40.Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers.ConclusionBoth register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers. To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data. After linking data on prescription drug usage, hospital diagnoses, laboratory results and diabetes-specific healthcare services from nationwide healthcare registers, diabetes type was defined for all individuals in Central Denmark Region age 18-74 years on 31 December 2018 according to two distinct register-based classifiers: 1) a novel register-based diabetes classifier incorporating diagnostic hemoglobin-A1C measurements, the (OSDC), and 2) an existing Danish diabetes classifier, the (RSCD). These classifications were validated against self-reported data from the survey - overall and stratified by age at onset of diabetes. The source-code of both classifiers was made available in the open-source package . A total of 2633 (9.0%) of 29,391 respondents reported having any type of diabetes, divided across 410 (1.4%) self-reported cases of T1D and 2223 (7.6%) cases of T2D. Among all self-reported diabetes cases, 2421 (91.9%) were classified as diabetes cases by both classifiers. In T1D, sensitivity of OSDC-classification was 0.773 [95% CI 0.730-0.813] (RSCD: 0.700 [0.653-0.744]) and positive predictive value (PPV) 0.943 [0.913-0.966] (RSCD: 0.944 [0.912-0.967]). In T2D, sensitivity of OSDC-classification was 0.944 [0.933-0.953] (RSCD: 0.905 [0.892-0.917]) and PPV 0.875 [0.861-0.888] (RSCD: 0.898 [0.884-0.910]). In age at onset-stratified analyses of both classifiers, sensitivity and PPV were low in individuals with T1D onset after age 40 and T2D onset before age 40. Both register-based classifiers identified valid populations of T1D and T2D in a general population, but sensitivity was substantially higher in OSDC compared to RSCD. Register-classified diabetes type in cases with atypical age at onset of diabetes should be interpreted with caution. The validated, open-source classifiers provide robust and transparent tools for researchers.  | 
    
| Audience | Academic | 
    
| Author | Sandbæk, Annelli Isaksen, Anders Aasted Bjerg, Lasse  | 
    
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| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37180566$$D View this record in MEDLINE/PubMed | 
    
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| Keywords | type 1 diabetes open-source type 2 diabetes classification population-based  | 
    
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| Snippet | To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.
After linking... Purpose: To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.... To validate two register-based algorithms classifying type 1 (T1D) and type 2 diabetes (T2D) in a general population using Danish register data.PurposeTo... Anders Aasted Isaksen,1,2 Annelli Sandbæk,1,2 Lasse Bjerg1,2 1Department of Public Health, Aarhus University, Aarhus, Denmark; 2Steno Diabetes Center Aarhus,...  | 
    
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| SubjectTerms | Algorithms Chronic diseases classification Diabetes therapy Drugs Glycosylated hemoglobin Health care industry open-source Original Research population-based Prescribing type 1 diabetes Type 2 diabetes  | 
    
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| Title | Validation of Register-Based Diabetes Classifiers in Danish Data | 
    
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