Different Case Finding Approaches to Optimise COPD Diagnosis: Evidence from the RADICALS Trial

Nawar Alotaibi,1 Brigitte M Borg,2,3 Michael J Abramson,3 Eldho Paul,3 Nicholas Zwar,4 Grant Russell,5 Sally Wilson,1,6 Anne E Holland,2,7 Billie Bonevski,8 Ajay Mahal,9 Johnson George1,3 1Centre for Medicine Use and Safety, Monash University, Melbourne, VIC, Australia; 2Respiratory Medicine, Alfred Health, Melbourne, VIC, Australia; 3School of Public Health & Preventive Medicine, Monash University, Melbourne, VIC, Australia; 4Faculty of Health Sciences and Medicine, Bond University, Robina, QLD, Australia; 5Department of General Practice, Monash University, Melbourne, VIC, Australia; 6Department of Infrastructure Engineering, The University of Melbourne, Melbourne, VIC, Australia; 7Central Clinical School, Monash University, Melbourne, VIC, Australia; 8College of Medicine and Public Health, Flinders University, Bedford Park, SA, Australia; 9The Nossal Institute for Global Health, The University of Melbourne, Melbourne, VIC, AustraliaCorrespondence: Johnson George, Centre for Medicine Use and Safety, Faculty of Pharmacy and Pharmaceutical Sciences, Monash University, 381 Royal Parade, Parkville, VIC, 3052, Australia, Email Johnson.George@monash.eduAim: Diagnosis of COPD in primary care is hindered by underuse of spirometry. Case finding using validated symptom and health status questionnaires, and simple handheld devices in high-risk populations may improve diagnosis. This study aimed to determine the best combination of measures to optimise COPD diagnosis in the primary care setting.Methods: We recruited 335 current or ex-smokers, including those with an established diagnosis of COPD from general practices. Participants’ FEV1 and FEV6 were measured using a handheld spirometry device (COPD-6®). Each completed the COPD assessment test (CAT), a modified Medical Research Council (mMRC) dyspnoea scale, St George’s Respiratory Questionnaire (SGRQ) and smoking history questionnaire. From these data we calculated the predictive validity for spirometry-confirmed diagnosis of COPD. Area under the receiver operating characteristic curve (AUROC), sensitivity, specificity, positive and negative predictive values (PPV, NPV) were calculated for each. Kappa coefficient was used to measure the agreement between the Fixed-Ratio (FR) and Lower Limit of Normal (LLN) spirometric criteria in diagnosing COPD.Results: FEV1/FEV6 < 0.70 alone showed significant association (p< 0.0001) with COPD diagnosis and good predictive accuracy (AUROC=0.725). However, no further improvement was found after combining SGRQ, CAT and mMRC with FEV1/FEV6. FEV1/FEV6 < 0.70 using the COPD-6® handheld device had moderate sensitivity (65.7%) and high PPV (90.1%), high specificity (79.3%) and NPV (44.8%). There was good agreement between FR and LLN definitions (κ=0.70).Conclusion: Handheld micro-spirometers can facilitate case finding of COPD in smokers and ex-smokers attending general practice. The fixed ratio criterion currently recommended by COPD-X guidelines offers the simplest method for diagnosing COPD in Australian primary care.Keywords: case finding, COPD, diagnosis, primary care