Predicting risk of undiagnosed COPD in primary care: Development and validation of the TargetCOPD model

Research output: Contribution to journalAbstractpeer-review

Standard

Predicting risk of undiagnosed COPD in primary care: Development and validation of the TargetCOPD model. / Haroon, Shamil; Adab, Peymane; Riley, Richard D; Dickens, Andrew.

In: European Respiratory Journal, Vol. 48, No. Supplement 60, 01.09.2016.

Research output: Contribution to journalAbstractpeer-review

Harvard

APA

Vancouver

Author

Bibtex

@article{4324256ae36a4c1787e0bfe863008212,
title = "Predicting risk of undiagnosed COPD in primary care:: Development and validation of the TargetCOPD model",
abstract = "Background: Previous prediction models for assessing risk of undiagnosed COPD used data from routine diagnoses, which may be inaccurate because of under- and misdiagnosis. We developed and externally validated a primary care-based model using data from a unique case finding trial.Methods: Patients aged 40-79 years with no prior diagnosis of COPD received a screening questionnaire either by post or opportunistically at primary care attendances through a large case finding trial based in primary care in the West Midlands, UK. Those reporting chronic respiratory symptoms were assessed with spirometry. COPD was defined as presence of respiratory symptoms and post-bronchodilator FEV1/FVCResults: A model containing age, smoking status, dyspnoea, and prescriptions of salbutamol and antibiotics discriminated between patients with and without undiagnosed COPD (validation c-statistic 0.74 [95% CI 0.68 to 0.80]). A cut-point of ≥7.5% predicted risk to prompt referral for diagnostic assessment had a sensitivity of 68.8% (95% CI 57.3 to 78.9%) and specificity of 68.8% (95% CI 65.8.1 to 71.6%), requiring 7 diagnostic assessments (95% CI 6 to 10) to identify 1 patient with undiagnosed COPD.Conclusion: We have developed and externally validated a readily applicable risk model for undiagnosed COPD using routine data from electronic health records in primary care.",
keywords = "COPD - diagnosis , public health , epidemiology",
author = "Shamil Haroon and Peymane Adab and Riley, {Richard D} and Andrew Dickens",
year = "2016",
month = sep,
day = "1",
doi = "10.1183/13993003.congress-2016.PA3930",
language = "English",
volume = "48",
journal = "The European respiratory journal",
issn = "0903-1936",
publisher = "European Respiratory Society",
number = "Supplement 60",

}

RIS

TY - JOUR

T1 - Predicting risk of undiagnosed COPD in primary care:

T2 - Development and validation of the TargetCOPD model

AU - Haroon, Shamil

AU - Adab, Peymane

AU - Riley, Richard D

AU - Dickens, Andrew

PY - 2016/9/1

Y1 - 2016/9/1

N2 - Background: Previous prediction models for assessing risk of undiagnosed COPD used data from routine diagnoses, which may be inaccurate because of under- and misdiagnosis. We developed and externally validated a primary care-based model using data from a unique case finding trial.Methods: Patients aged 40-79 years with no prior diagnosis of COPD received a screening questionnaire either by post or opportunistically at primary care attendances through a large case finding trial based in primary care in the West Midlands, UK. Those reporting chronic respiratory symptoms were assessed with spirometry. COPD was defined as presence of respiratory symptoms and post-bronchodilator FEV1/FVCResults: A model containing age, smoking status, dyspnoea, and prescriptions of salbutamol and antibiotics discriminated between patients with and without undiagnosed COPD (validation c-statistic 0.74 [95% CI 0.68 to 0.80]). A cut-point of ≥7.5% predicted risk to prompt referral for diagnostic assessment had a sensitivity of 68.8% (95% CI 57.3 to 78.9%) and specificity of 68.8% (95% CI 65.8.1 to 71.6%), requiring 7 diagnostic assessments (95% CI 6 to 10) to identify 1 patient with undiagnosed COPD.Conclusion: We have developed and externally validated a readily applicable risk model for undiagnosed COPD using routine data from electronic health records in primary care.

AB - Background: Previous prediction models for assessing risk of undiagnosed COPD used data from routine diagnoses, which may be inaccurate because of under- and misdiagnosis. We developed and externally validated a primary care-based model using data from a unique case finding trial.Methods: Patients aged 40-79 years with no prior diagnosis of COPD received a screening questionnaire either by post or opportunistically at primary care attendances through a large case finding trial based in primary care in the West Midlands, UK. Those reporting chronic respiratory symptoms were assessed with spirometry. COPD was defined as presence of respiratory symptoms and post-bronchodilator FEV1/FVCResults: A model containing age, smoking status, dyspnoea, and prescriptions of salbutamol and antibiotics discriminated between patients with and without undiagnosed COPD (validation c-statistic 0.74 [95% CI 0.68 to 0.80]). A cut-point of ≥7.5% predicted risk to prompt referral for diagnostic assessment had a sensitivity of 68.8% (95% CI 57.3 to 78.9%) and specificity of 68.8% (95% CI 65.8.1 to 71.6%), requiring 7 diagnostic assessments (95% CI 6 to 10) to identify 1 patient with undiagnosed COPD.Conclusion: We have developed and externally validated a readily applicable risk model for undiagnosed COPD using routine data from electronic health records in primary care.

KW - COPD - diagnosis

KW - public health

KW - epidemiology

U2 - 10.1183/13993003.congress-2016.PA3930

DO - 10.1183/13993003.congress-2016.PA3930

M3 - Abstract

VL - 48

JO - The European respiratory journal

JF - The European respiratory journal

SN - 0903-1936

IS - Supplement 60

ER -