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Published on: September 20, 2018
Epidemiology of aplasia cutis congenita: A population-based study in Europe
Alessio Coi1, Ingeborg Barisic2, Ester Garne3
1Unit of Epidemiology of Rare Diseases and Congenital Anomalies, Institute of Clinical Physiology, National Research Council, Pisa, Italy.
Background:
Aplasia cutis congenita (ACC) is a rare congenital anomaly characterized by localized or widespread absence of skin at birth, mainly affecting the scalp. Most information about ACC exists as individual case reports and medium-sized studies.
Objectives:
This study aimed to investigate the epidemiology of ACC, using data from a large European network of population-based registries for congenital anomalies (EUROCAT).
Methods:
Twenty-eight EUROCAT population-based registries in 16 European countries were involved. Poisson regression models were exploited to estimate the overall and live birth prevalence, to test time trends in prevalence between four 5-year periods and to evaluate the impact of the change of coding for ACC from the unspecific ICD9-BPA code to the specific ICD10 code. Proportions of ACC cases associated with other anomalies were reported.
Results:
Five hundred cases were identified in the period 1998-2017 (prevalence: 5.10 per 100,000 births). Prevalence across 5-year periods did not differ significantly and no significant differences were evident due to the change from ICD9 to ICD10 in ACC coding. Heterogeneity in prevalence was observed across registries. The scalp was the most common site for ACC (96.4%) and associated congenital anomalies were present in 33.8% of cases. Patau and Adams-Oliver syndromes were the most frequent among the associated chromosomal anomalies (88.3%) and the associated genetic syndromes (57.7%), respectively. 16% of cases were associated with limb anomalies and 15.4% with congenital heart defects. A family history of ACC was found in 2% of cases.
Conclusion:
To our knowledge, this is the only population-based study on ACC. The EUROCAT methodologies provide reliable prevalence estimates and proportions of associated anomalies.
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