Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases

Antoine G. Sreih, Narender Annapureddy, Jason Springer, George Casey, Kevin Byram, Andy Cruz, Maya Estephan, Vince Frangiosa, Michael D. George, Mei Liu, Adam Parker, Sapna Sangani, Rebecca Sharim, Peter A. Merkel, for the Vasculitis Patient-Powered Research Network

Research output: Contribution to journalArticle

5 Citations (Scopus)

Abstract

Purpose: The aim of this study was to develop and validate case-finding algorithms for granulomatosis with polyangiitis (Wegener's, GPA), microscopic polyangiitis (MPA), and eosinophilic GPA (Churg–Strauss, EGPA). Methods: Two hundred fifty patients per disease were randomly selected from two large healthcare systems using the International Classification of Diseases version 9 (ICD9) codes for GPA/EGPA (446.4) and MPA (446.0). Sixteen case-finding algorithms were constructed using a combination of ICD9 code, encounter type (inpatient or outpatient), physician specialty, use of immunosuppressive medications, and the anti-neutrophil cytoplasmic antibody type. Algorithms with the highest average positive predictive value (PPV) were validated in a third healthcare system. Results: An algorithm excluding patients with eosinophilia or asthma and including the encounter type and physician specialty had the highest PPV for GPA (92.4%). An algorithm including patients with eosinophilia and asthma and the physician specialty had the highest PPV for EGPA (100%). An algorithm including patients with one of the diagnoses (alveolar hemorrhage, interstitial lung disease, glomerulonephritis, and acute or chronic kidney disease), encounter type, physician specialty, and immunosuppressive medications had the highest PPV for MPA (76.2%). When validated in a third healthcare system, these algorithms had high PPV (85.9% for GPA, 85.7% for EGPA, and 61.5% for MPA). Adding the anti-neutrophil cytoplasmic antibody type increased the PPV to 94.4%, 100%, and 81.2% for GPA, EGPA, and MPA, respectively. Conclusion: Case-finding algorithms accurately identify patients with GPA, EGPA, and MPA in administrative databases. These algorithms can be used to assemble population-based cohorts and facilitate future research in epidemiology, drug safety, and comparative effectiveness.

Original languageEnglish (US)
Pages (from-to)1368-1374
Number of pages7
JournalPharmacoepidemiology and Drug Safety
Volume25
Issue number12
DOIs
StatePublished - Dec 1 2016
Externally publishedYes

Fingerprint

Anti-Neutrophil Cytoplasmic Antibody-Associated Vasculitis
Microscopic Polyangiitis
Databases
Delivery of Health Care
Physicians
Antineutrophil Cytoplasmic Antibodies
Eosinophilia
International Classification of Diseases
Immunosuppressive Agents
Asthma
Granulomatosis with Polyangiitis
Interstitial Lung Diseases
Glomerulonephritis
Chronic Renal Insufficiency
Inpatients
Epidemiology
Outpatients
Hemorrhage

Keywords

  • ANCA
  • computable phenotypes
  • eosinophilic granulomatosis with polyangiitis
  • granulomatosis with polyangiitis
  • microscopic polyangiitis
  • pharmacoepidemiology
  • vasculitis

ASJC Scopus subject areas

  • Epidemiology
  • Pharmacology (medical)

Cite this

Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases. / Sreih, Antoine G.; Annapureddy, Narender; Springer, Jason; Casey, George; Byram, Kevin; Cruz, Andy; Estephan, Maya; Frangiosa, Vince; George, Michael D.; Liu, Mei; Parker, Adam; Sangani, Sapna; Sharim, Rebecca; Merkel, Peter A.; for the Vasculitis Patient-Powered Research Network.

In: Pharmacoepidemiology and Drug Safety, Vol. 25, No. 12, 01.12.2016, p. 1368-1374.

Research output: Contribution to journalArticle

Sreih, AG, Annapureddy, N, Springer, J, Casey, G, Byram, K, Cruz, A, Estephan, M, Frangiosa, V, George, MD, Liu, M, Parker, A, Sangani, S, Sharim, R, Merkel, PA & for the Vasculitis Patient-Powered Research Network 2016, 'Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases', Pharmacoepidemiology and Drug Safety, vol. 25, no. 12, pp. 1368-1374. https://doi.org/10.1002/pds.4116
Sreih, Antoine G. ; Annapureddy, Narender ; Springer, Jason ; Casey, George ; Byram, Kevin ; Cruz, Andy ; Estephan, Maya ; Frangiosa, Vince ; George, Michael D. ; Liu, Mei ; Parker, Adam ; Sangani, Sapna ; Sharim, Rebecca ; Merkel, Peter A. ; for the Vasculitis Patient-Powered Research Network. / Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases. In: Pharmacoepidemiology and Drug Safety. 2016 ; Vol. 25, No. 12. pp. 1368-1374.
@article{2f4b36da166d4a02914a9962f5f14c97,
title = "Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases",
abstract = "Purpose: The aim of this study was to develop and validate case-finding algorithms for granulomatosis with polyangiitis (Wegener's, GPA), microscopic polyangiitis (MPA), and eosinophilic GPA (Churg–Strauss, EGPA). Methods: Two hundred fifty patients per disease were randomly selected from two large healthcare systems using the International Classification of Diseases version 9 (ICD9) codes for GPA/EGPA (446.4) and MPA (446.0). Sixteen case-finding algorithms were constructed using a combination of ICD9 code, encounter type (inpatient or outpatient), physician specialty, use of immunosuppressive medications, and the anti-neutrophil cytoplasmic antibody type. Algorithms with the highest average positive predictive value (PPV) were validated in a third healthcare system. Results: An algorithm excluding patients with eosinophilia or asthma and including the encounter type and physician specialty had the highest PPV for GPA (92.4{\%}). An algorithm including patients with eosinophilia and asthma and the physician specialty had the highest PPV for EGPA (100{\%}). An algorithm including patients with one of the diagnoses (alveolar hemorrhage, interstitial lung disease, glomerulonephritis, and acute or chronic kidney disease), encounter type, physician specialty, and immunosuppressive medications had the highest PPV for MPA (76.2{\%}). When validated in a third healthcare system, these algorithms had high PPV (85.9{\%} for GPA, 85.7{\%} for EGPA, and 61.5{\%} for MPA). Adding the anti-neutrophil cytoplasmic antibody type increased the PPV to 94.4{\%}, 100{\%}, and 81.2{\%} for GPA, EGPA, and MPA, respectively. Conclusion: Case-finding algorithms accurately identify patients with GPA, EGPA, and MPA in administrative databases. These algorithms can be used to assemble population-based cohorts and facilitate future research in epidemiology, drug safety, and comparative effectiveness.",
keywords = "ANCA, computable phenotypes, eosinophilic granulomatosis with polyangiitis, granulomatosis with polyangiitis, microscopic polyangiitis, pharmacoepidemiology, vasculitis",
author = "Sreih, {Antoine G.} and Narender Annapureddy and Jason Springer and George Casey and Kevin Byram and Andy Cruz and Maya Estephan and Vince Frangiosa and George, {Michael D.} and Mei Liu and Adam Parker and Sapna Sangani and Rebecca Sharim and Merkel, {Peter A.} and {for the Vasculitis Patient-Powered Research Network}",
year = "2016",
month = "12",
day = "1",
doi = "10.1002/pds.4116",
language = "English (US)",
volume = "25",
pages = "1368--1374",
journal = "Pharmacoepidemiology and Drug Safety",
issn = "1053-8569",
publisher = "John Wiley and Sons Ltd",
number = "12",

}

TY - JOUR

T1 - Development and validation of case-finding algorithms for the identification of patients with anti-neutrophil cytoplasmic antibody-associated vasculitis in large healthcare administrative databases

AU - Sreih, Antoine G.

AU - Annapureddy, Narender

AU - Springer, Jason

AU - Casey, George

AU - Byram, Kevin

AU - Cruz, Andy

AU - Estephan, Maya

AU - Frangiosa, Vince

AU - George, Michael D.

AU - Liu, Mei

AU - Parker, Adam

AU - Sangani, Sapna

AU - Sharim, Rebecca

AU - Merkel, Peter A.

AU - for the Vasculitis Patient-Powered Research Network

PY - 2016/12/1

Y1 - 2016/12/1

N2 - Purpose: The aim of this study was to develop and validate case-finding algorithms for granulomatosis with polyangiitis (Wegener's, GPA), microscopic polyangiitis (MPA), and eosinophilic GPA (Churg–Strauss, EGPA). Methods: Two hundred fifty patients per disease were randomly selected from two large healthcare systems using the International Classification of Diseases version 9 (ICD9) codes for GPA/EGPA (446.4) and MPA (446.0). Sixteen case-finding algorithms were constructed using a combination of ICD9 code, encounter type (inpatient or outpatient), physician specialty, use of immunosuppressive medications, and the anti-neutrophil cytoplasmic antibody type. Algorithms with the highest average positive predictive value (PPV) were validated in a third healthcare system. Results: An algorithm excluding patients with eosinophilia or asthma and including the encounter type and physician specialty had the highest PPV for GPA (92.4%). An algorithm including patients with eosinophilia and asthma and the physician specialty had the highest PPV for EGPA (100%). An algorithm including patients with one of the diagnoses (alveolar hemorrhage, interstitial lung disease, glomerulonephritis, and acute or chronic kidney disease), encounter type, physician specialty, and immunosuppressive medications had the highest PPV for MPA (76.2%). When validated in a third healthcare system, these algorithms had high PPV (85.9% for GPA, 85.7% for EGPA, and 61.5% for MPA). Adding the anti-neutrophil cytoplasmic antibody type increased the PPV to 94.4%, 100%, and 81.2% for GPA, EGPA, and MPA, respectively. Conclusion: Case-finding algorithms accurately identify patients with GPA, EGPA, and MPA in administrative databases. These algorithms can be used to assemble population-based cohorts and facilitate future research in epidemiology, drug safety, and comparative effectiveness.

AB - Purpose: The aim of this study was to develop and validate case-finding algorithms for granulomatosis with polyangiitis (Wegener's, GPA), microscopic polyangiitis (MPA), and eosinophilic GPA (Churg–Strauss, EGPA). Methods: Two hundred fifty patients per disease were randomly selected from two large healthcare systems using the International Classification of Diseases version 9 (ICD9) codes for GPA/EGPA (446.4) and MPA (446.0). Sixteen case-finding algorithms were constructed using a combination of ICD9 code, encounter type (inpatient or outpatient), physician specialty, use of immunosuppressive medications, and the anti-neutrophil cytoplasmic antibody type. Algorithms with the highest average positive predictive value (PPV) were validated in a third healthcare system. Results: An algorithm excluding patients with eosinophilia or asthma and including the encounter type and physician specialty had the highest PPV for GPA (92.4%). An algorithm including patients with eosinophilia and asthma and the physician specialty had the highest PPV for EGPA (100%). An algorithm including patients with one of the diagnoses (alveolar hemorrhage, interstitial lung disease, glomerulonephritis, and acute or chronic kidney disease), encounter type, physician specialty, and immunosuppressive medications had the highest PPV for MPA (76.2%). When validated in a third healthcare system, these algorithms had high PPV (85.9% for GPA, 85.7% for EGPA, and 61.5% for MPA). Adding the anti-neutrophil cytoplasmic antibody type increased the PPV to 94.4%, 100%, and 81.2% for GPA, EGPA, and MPA, respectively. Conclusion: Case-finding algorithms accurately identify patients with GPA, EGPA, and MPA in administrative databases. These algorithms can be used to assemble population-based cohorts and facilitate future research in epidemiology, drug safety, and comparative effectiveness.

KW - ANCA

KW - computable phenotypes

KW - eosinophilic granulomatosis with polyangiitis

KW - granulomatosis with polyangiitis

KW - microscopic polyangiitis

KW - pharmacoepidemiology

KW - vasculitis

UR - http://www.scopus.com/inward/record.url?scp=84996957274&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84996957274&partnerID=8YFLogxK

U2 - 10.1002/pds.4116

DO - 10.1002/pds.4116

M3 - Article

VL - 25

SP - 1368

EP - 1374

JO - Pharmacoepidemiology and Drug Safety

JF - Pharmacoepidemiology and Drug Safety

SN - 1053-8569

IS - 12

ER -