Estimating the Prevalence of AATD Patients in the UK to Identify Underdiagnosis and Determine the Eligibility for Potential Augmentation Therapy

Abstract

Purpose

Alpha 1 antitrypsin deficiency (AATD) is a genetic risk factor for chronic obstructive pulmonary disease (COPD). Whilst testing for the condition is relatively simple, there is a disconnect in published literature between genetic epidemiology and numbers of patients known to specialists. This makes planning services for patients difficult. We aimed to estimate the number of patients likely to have lung disease eligible for specific AATD therapy within the UK.

Patients and Methods

The THIN database was used to determine the prevalence of AATD and symptomatic COPD. This, and published rates of AATD were used to extrapolate THIN data to the population size of the UK to give an indicative population size for symptomatic AATD patients who have lung disease. The Birmingham AATD registry was used to describe age at diagnosis, rate of lung disease and symptomatic lung disease for patients with PiZZ (or equivalent) AATD, together with the time from symptom onset to diagnosis, in order to aid interpretation of the THIN data and improve modeling.

Results

THIN data showed COPD prevalence of 3%, and AATD prevalence of 0.005–0.2%, depending on how stringently AATD diagnostic codes were applied. The majority of Birmingham AATD patients were diagnosed between the ages 46–55, whilst patients recorded in THIN tended to be older. The rate of COPD was similar in the THIN and Birmingham patients diagnosed with AATD. Modelling to the size of the UK demonstrated a likely symptomatic AATD population of between 3016 and 9866 people.

Conclusion

AATD is likely to be under-diagnosed in the UK. Based on projected patient numbers an expansion to specialist services is desirable, in particular if specific therapy for AATD such as augmentation were to be introduced to the healthcare system.

Keywords:

• alpha 1 antitrypsin deficiency
• chronic obstructive pulmonary disease
• epidemiology

Acknowledgments

We would like to thank K Niranthakumar and T Marshall for access to THIN, as well as training in and use of the data extraction in epidemiological research (DExtER) tool.

Author Contributions

All authors made a significant contribution to the work reported, whether that is in the conception, study design, execution, acquisition of data, analysis and interpretation, or in all these areas; took part in drafting, revising or critically reviewing the article; gave final approval of the version to be published; have agreed on the journal to which the article has been submitted; and agree to be accountable for all aspects of the work.

Disclosure

Dr Michael Newnham reports grants from CSL Behring, during the conduct of the study. Professor Alice M Turner reports grants from CSL Behring, during the conduct of the study; grants, personal fees from Grifols, grants, personal fees from Vertex, grants, personal fees from AstraZeneca, personal fees from GSK, grants from Chiesi, outside the submitted work. The authors report no other conflicts of interest in this work.

Additional information

Funding

This research was funded by CSL Behring.