What is the discriminative accuracy of COPD screening instruments in 3 low- and middle-income country settings?
In this cross-sectional study that included 10 709 adults in Nepal, Peru, and Uganda, 3 screening instruments for COPD were feasible to administer and, using postbronchodilator spirometry as the reference standard, yielded area under receiver operating characteristic curves ranging from 0.72 to 0.79.
This study demonstrated that 3 screening instruments for COPD were feasible to administer in low- and middle-income settings, although further research is needed to assess their performance in other settings and determine whether implementation is associated with improved clinical outcomes.
Most of the global morbidity and mortality in chronic obstructive pulmonary disease (COPD) occurs in low- and middle-income countries (LMICs), with significant economic effects.
To assess the discriminative accuracy of 3 instruments using questionnaires and peak expiratory flow (PEF) to screen for COPD in 3 LMIC settings.
Design, Setting, and Participants
A cross-sectional analysis of discriminative accuracy, conducted between January 2018 and March 2020 in semiurban Bhaktapur, Nepal; urban Lima, Peru; and rural Nakaseke, Uganda, using a random age- and sex-stratified sample of the population 40 years or older.
Three screening tools, the COPD Assessment in Primary Care to Identify Undiagnosed Respiratory Disease and Exacerbation Risk (CAPTURE; range, 0-6; high risk indicated by a score of 5 or more or score 2-5 with low PEF [<250 L/min for females and <350 L/min for males]), the COPD in LMICs Assessment questionnaire (COLA-6; range, 0-5; high risk indicated by a score of 4 or more), and the Lung Function Questionnaire (LFQ; range, 0-25; high risk indicated by a score of 18 or less) were assessed against a reference standard diagnosis of COPD using quality-assured postbronchodilator spirometry. CAPTURE and COLA-6 include a measure of PEF.
Main Outcomes and Measures
The primary outcome was discriminative accuracy of the tools in identifying COPD as measured by area under receiver operating characteristic curves (AUCs) with 95% CIs. Secondary outcomes included sensitivity, specificity, positive predictive value, and negative predictive value.
Among 10 709 adults who consented to participate in the study (mean age, 56.3 years (SD, 11.7); 50% female), 35% had ever smoked, and 30% were currently exposed to biomass smoke. The unweighted prevalence of COPD at the 3 sites was 18.2% (642/3534 participants) in Nepal, 2.7% (97/3550) in Peru, and 7.4% (264/3580) in Uganda. Among 1000 COPD cases, 49.3% had clinically important disease (Global Initiative for Chronic Obstructive Lung Disease classification B-D), 16.4% had severe or very severe airflow obstruction (forced expiratory volume in 1 second <50% predicted), and 95.3% of cases were previously undiagnosed. The AUC for the screening instruments ranged from 0.717 (95% CI, 0.677-0.774) for LFQ in Peru to 0.791 (95% CI, 0.770-0.809) for COLA-6 in Nepal. The sensitivity ranged from 34.8% (95% CI, 25.3%-45.2%) for COLA-6 in Nepal to 64.2% (95% CI, 60.3%-67.9%) for CAPTURE in Nepal. The mean time to administer the instruments was 7.6 minutes (SD 1.11), and data completeness was 99.5%.
Conclusions and Relevance
This study demonstrated that screening instruments for COPD were feasible to administer in 3 low- and middle-income settings. Further research is needed to assess instrument performance in other low- and middle-income settings and to determine whether implementation is associated with improved clinical outcomes.
Siddharthan T, Pollard SL, Quaderi SA, et al. Discriminative Accuracy of Chronic Obstructive Pulmonary Disease Screening Instruments in 3 Low- and Middle-Income Country Settings. JAMA. 2022;327(2):151–160. doi:10.1001/jama.2021.23065
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