The impact of diagnostic delay on survival in alpha-1-antitrypsin deficiency - results from the Austrian Alpha-1 Lung Registry

Meischl, Tobias; Schmid-Scherzer, Karin; Loeffler‐Ragg, Judith; Grabcanovic-Musija, Fikreta; Mueller, Simona; Wurzinger, Gert; Kaufmann, Norbert; Rauter, Markus; Valipour, Arschang; Funk, Georg‐Christian

doi:10.1183/13993003.congress-2021.pa3302

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“…Epidemiological data estimate that there are ∼100 000 individuals with severe AATD in the USA, although only ~10 000 have been identified [ 6 ]. People ultimately diagnosed with AATD see multiple physicians and experience long delays from symptom onset to diagnosis, which is associated with worsened clinical symptoms and overall survival, underscoring the importance of identifying persons with AATD earlier [ 7 , 8 ].…”

Section: Introductionmentioning

confidence: 99%

Development of a risk score to increase detection of severe alpha-1 antitrypsin deficiency

et al. 2023

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BackgroundAlpha-1 antitrypsin deficiency (AATD) is an underrecognised genetic cause of chronic obstructive lung disease, and many fewer cases than estimated have been identified. Can a reported respiratory and hepatic disease history from a large AATD testing database be used stratify a person's risk of severe AATD?MethodsWe analysed data extracted from the AATD National Detection Program. Demographics and medical history were evaluated to predict AATD PI*ZZ genotype. Logistic regression and integer programming models identified predictors and obtained risk scores. These were internally validated on a subset of the data.ResultsOf 301 343 subjects, 1529 (0.5%) had PI*ZZ genotype. Predictors of severe AATD were asthma, bronchitis, emphysema, allergies, bronchiectasis, family history of AATD, cirrhosis, hepatitis, and history of abnormal liver function tests. The derived model establishes a subject's risk of severe AATD, and scores ≥0 had an estimated risk of 0.41%, sensitivity 84.62%, and specificity 24.32%. A model simulating guideline recommendations had an estimated risk of 0.51% with a sensitivity of 37.98% and specificity 46.60%. By recommending screening for scores ≥0, we estimate that more subjects would be screened (75.7%versus53.4%) and detected (84.6%versus58.2%) compared to a guideline simulated model.ConclusionThis medical-history risk model is a useful predictive tool to detect subjects at greater risk of having severe AATD and improves sensitivity of detection. Scores below zero are at lower risk and may need not be screened; testing is recommended for scores zero and above and consistent with current guidelines.

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Section: Introductionmentioning

confidence: 99%