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A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology

OBJECTIVES: To develop and validate a new algorithm to identify patients with rheumatoid arthritis (RA) and estimate disease prevalence using administrative health databases (AHDs) of the Italian Lombardy region. DESIGN: Case–control and cohort diagnostic accuracy study. METHODS: In a randomly selec...

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Autores principales: Carrara, Greta, Scirè, Carlo A, Zambon, Antonella, Cimmino, Marco A, Cerra, Carlo, Caprioli, Marta, Cagnotto, Giovanni, Nicotra, Federica, Arfè, Andrea, Migliazza, Simona, Corrao, Giovanni, Minisola, Giovanni, Montecucco, Carlomaurizio
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BMJ Publishing Group 2015
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4316439/
https://www.ncbi.nlm.nih.gov/pubmed/25631308
http://dx.doi.org/10.1136/bmjopen-2014-006029
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author Carrara, Greta
Scirè, Carlo A
Zambon, Antonella
Cimmino, Marco A
Cerra, Carlo
Caprioli, Marta
Cagnotto, Giovanni
Nicotra, Federica
Arfè, Andrea
Migliazza, Simona
Corrao, Giovanni
Minisola, Giovanni
Montecucco, Carlomaurizio
author_facet Carrara, Greta
Scirè, Carlo A
Zambon, Antonella
Cimmino, Marco A
Cerra, Carlo
Caprioli, Marta
Cagnotto, Giovanni
Nicotra, Federica
Arfè, Andrea
Migliazza, Simona
Corrao, Giovanni
Minisola, Giovanni
Montecucco, Carlomaurizio
author_sort Carrara, Greta
collection PubMed
description OBJECTIVES: To develop and validate a new algorithm to identify patients with rheumatoid arthritis (RA) and estimate disease prevalence using administrative health databases (AHDs) of the Italian Lombardy region. DESIGN: Case–control and cohort diagnostic accuracy study. METHODS: In a randomly selected sample of 827 patients drawn from a tertiary rheumatology centre (training set), clinically validated diagnoses were linked to administrative data including diagnostic codes and drug prescriptions. An algorithm in steps of decreasing specificity was developed and its accuracy assessed calculating sensitivity/specificity, positive predictive value (PPV)/negative predictive value, with corresponding CIs. The algorithm was applied to two validating sets: 106 patients from a secondary rheumatology centre and 6087 participants from the primary care. Alternative algorithms were developed to increase PPV at population level. Crude and adjusted prevalence estimates taking into account algorithm misclassification rates were obtained for the Lombardy region. RESULTS: The algorithms included: RA certification by a rheumatologist, certification for other autoimmune diseases by specialists, RA code in the hospital discharge form, prescription of disease-modifying antirheumatic drugs and oral glucocorticoids. In the training set, a four-step algorithm identified clinically diagnosed RA cases with a sensitivity of 96.3 (95% CI 93.6 to 98.2) and a specificity of 90.3 (87.4 to 92.7). Both external validations showed highly consistent results. More specific algorithms achieved >80% PPV at the population level. The crude RA prevalence in Lombardy was 0.52%, and estimates adjusted for misclassification ranged from 0.31% (95% CI 0.14% to 0.42%) to 0.37% (0.25% to 0.47%). CONCLUSIONS: AHDs are valuable tools for the identification of RA cases at the population level, and allow estimation of disease prevalence and to select retrospective cohorts.
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spelling pubmed-43164392015-02-10 A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology Carrara, Greta Scirè, Carlo A Zambon, Antonella Cimmino, Marco A Cerra, Carlo Caprioli, Marta Cagnotto, Giovanni Nicotra, Federica Arfè, Andrea Migliazza, Simona Corrao, Giovanni Minisola, Giovanni Montecucco, Carlomaurizio BMJ Open Rheumatology OBJECTIVES: To develop and validate a new algorithm to identify patients with rheumatoid arthritis (RA) and estimate disease prevalence using administrative health databases (AHDs) of the Italian Lombardy region. DESIGN: Case–control and cohort diagnostic accuracy study. METHODS: In a randomly selected sample of 827 patients drawn from a tertiary rheumatology centre (training set), clinically validated diagnoses were linked to administrative data including diagnostic codes and drug prescriptions. An algorithm in steps of decreasing specificity was developed and its accuracy assessed calculating sensitivity/specificity, positive predictive value (PPV)/negative predictive value, with corresponding CIs. The algorithm was applied to two validating sets: 106 patients from a secondary rheumatology centre and 6087 participants from the primary care. Alternative algorithms were developed to increase PPV at population level. Crude and adjusted prevalence estimates taking into account algorithm misclassification rates were obtained for the Lombardy region. RESULTS: The algorithms included: RA certification by a rheumatologist, certification for other autoimmune diseases by specialists, RA code in the hospital discharge form, prescription of disease-modifying antirheumatic drugs and oral glucocorticoids. In the training set, a four-step algorithm identified clinically diagnosed RA cases with a sensitivity of 96.3 (95% CI 93.6 to 98.2) and a specificity of 90.3 (87.4 to 92.7). Both external validations showed highly consistent results. More specific algorithms achieved >80% PPV at the population level. The crude RA prevalence in Lombardy was 0.52%, and estimates adjusted for misclassification ranged from 0.31% (95% CI 0.14% to 0.42%) to 0.37% (0.25% to 0.47%). CONCLUSIONS: AHDs are valuable tools for the identification of RA cases at the population level, and allow estimation of disease prevalence and to select retrospective cohorts. BMJ Publishing Group 2015-01-28 /pmc/articles/PMC4316439/ /pubmed/25631308 http://dx.doi.org/10.1136/bmjopen-2014-006029 Text en Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions This is an Open Access article distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
spellingShingle Rheumatology
Carrara, Greta
Scirè, Carlo A
Zambon, Antonella
Cimmino, Marco A
Cerra, Carlo
Caprioli, Marta
Cagnotto, Giovanni
Nicotra, Federica
Arfè, Andrea
Migliazza, Simona
Corrao, Giovanni
Minisola, Giovanni
Montecucco, Carlomaurizio
A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology
title A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology
title_full A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology
title_fullStr A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology
title_full_unstemmed A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology
title_short A validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. Results from the RECord linkage On Rheumatic Diseases study of the Italian Society for Rheumatology
title_sort validation study of a new classification algorithm to identify rheumatoid arthritis using administrative health databases: case–control and cohort diagnostic accuracy studies. results from the record linkage on rheumatic diseases study of the italian society for rheumatology
topic Rheumatology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4316439/
https://www.ncbi.nlm.nih.gov/pubmed/25631308
http://dx.doi.org/10.1136/bmjopen-2014-006029
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