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Table 1. Pediatric Deaths Through Age 14 Years in Victoria, Australia, During 1997 Through 2007
Table 1. Pediatric Deaths Through Age 14 Years in Victoria, Australia, During 1997 Through 2007
Table 2. Deaths According to Category of Inborn Errors of Metabolism and Age
Table 2. Deaths According to Category of Inborn Errors of Metabolism and Age
1.
Hutchesson AC, Bundey S, Preece MA, Hall SK, Green A. A comparison of disease and gene frequencies of inborn errors of metabolism among different ethnic groups in the West Midlands, UK.  J Med Genet. 1998;35(5):366-370PubMedArticle
2.
Applegarth DA, Toone JR, Lowry RB. Incidence of inborn errors of metabolism in British Columbia, 1969-1996.  Pediatrics. 2000;105(1):e10PubMedArticle
3.
Dionisi-Vici C, Rizzo C, Burlina AB,  et al.  Inborn errors of metabolism in the Italian pediatric population: a national retrospective survey.  J Pediatr. 2002;140(3):321-327PubMedArticle
4.
 Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM). Victorian Perinatal Data Collection (VPDC). Victorian Birth Defects Register (VBDR). Victoria Department of Health Web site. http://www.health.vic.gov.au/ccopmm/index.htm. Accessed June 10, 2010
5.
Bernier FP, Boneh A, Dennett X, Chow CW, Cleary MA, Thorburn DR. Diagnostic criteria for respiratory chain disorders in adults and children.  Neurology. 2002;59(9):1406-1411PubMedArticle
6.
 Interactive statistical calculation pages. http://statpages.org/index.html. Accessed June 11, 2010
Research Letter
September 8, 2010

Pediatric Mortality Due to Inborn Errors of Metabolism in Victoria, Australia: A Population-Based Study

JAMA. 2010;304(10):1070-1072. doi:10.1001/jama.2010.1259

To the Editor: Inborn errors of metabolism (IEM) constitute an important group of individually rare disorders, with a combined prevalence of 1:318 to 1:3760 live births in different populations.13 We assessed the population-based contribution of IEM to pediatric mortality in Victoria, Australia.

Methods

Overall pediatric mortality data up to age 14 years in Victoria from 1997 through 2007 were retrieved from the Victorian Perinatal Data Collection Unit (VPDCU).4 All patients diagnosed with IEM in Victoria are managed by a centralized service at the Victorian Clinical Genetics Services and the Royal Children's Hospital, Melbourne. Patient information was retrieved from databases of these organizations, using the Online Mendelian Inheritance in Man coding system and the coding systems of the International Classification of Diseases, Ninth Revision, Clinical Modification, and International Statistical Classification of Diseases, 10th Revision, Australian Modification, respectively. The medical records were reviewed for all patients who had a confirmed IEM (diagnosed clinically or through a perimortem metabolic autopsy [biochemical examination of blood, urine, bile, cerebrospinal fluid, and muscle and liver biopsies] and the coroner's court)—and who were born in Victoria and were living in Victoria on the date of death (between January 1997 and December 2007).

Strict diagnostic criteria for the diagnosis of disorders of energy metabolism were used.5 The VPDCU template was used for stratifying patients according to their ages at death. Information about each patient was cross-validated between the databases. Medians and Poisson exact interquartile ranges (IQRs) were calculated for the percentage mortality due to IEM relative to the total number of pediatric deaths and to the number of pediatric deaths due to nonacquired causes (eg, deaths not due to prematurity, infections, cancer, accidents, suicides) for each year.6 This study was considered an audit of unidentified patients and did not require formal ethics committee approval.

Results

A total of 120 children (60 boys) aged 0 to 14 years died due to IEM during the study period, including 27 neonates (23%), 30 infants aged 29 to 364 days (25%), and 63 children aged 1 to 14 years (52%) (Table 1 and Table 2). An overall median of 9.5% (IQR, 7.3%-12.5%) deaths due to nonacquired causes were due to IEM, representing 5.1% (IQR, 3.4%-7.4%) of neonatal deaths, 7.1% (IQR, 5.1%-9.7%) of deaths at age 29 to 364 days, and 17.9% (IQR, 14.5%-21.2%) of deaths at older than 1 year.

The most common causes of death across all age groups were disorders of energy metabolism (n = 36; 30%) and lysosomal storage disease (n = 36; 30%) (Table 2). In the neonatal period, disorders of intermediary metabolism (n = 11) and disorders of energy metabolism (n = 10) (39.2% and 35.7% of neonatal deaths due to IEM, respectively) were the most common causes of death. Smith-Lemli-Opitz syndrome, a disorder of cholesterol biosynthesis, was also a prominent cause (n = 4; 14%) in this age group. In the age group 29 to 364 days, the most common causes of death were lysosomal storage disease (n = 14; 46.6%) and disorders of energy metabolism (n = 7; 23.3%). Lysosomal storage disease (n = 22; 35.4%) and disorders of energy metabolism (n = 19; 30.6%) were the most common causes of deaths at older than 1 year (Table 2).

Comment

The estimated mortality rate due to IEM in Victoria from 1997 through 2007 was 3.5% of the overall mortality and 9.5% of mortality due to nonacquired causes. Considering a conservative prevalence of 0.3% IEM in the general population, this indicates a disproportionate contribution of these diseases to pediatric mortality.

These estimates represent the minimum effect of IEM on pediatric mortality because, given continuously improving diagnostic ascertainment, it is very likely that additional children with IEM previously died without a diagnosis. This likely included preterm babies whose deaths have been attributed to prematurity.

This study may serve as a benchmark for assessing the potential benefit of expanded newborn screening programs (particularly regarding disorders of intermediary metabolism), enzyme replacement therapies for lysosomal storage disease, and new therapies for energy metabolism defects.

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Article Information

Author Contributions: Dr Boneh had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

Study concept and design: Boneh.

Acquisition of data: Goel, Lusher.

Analysis and interpretation of data: Goel, Boneh.

Drafting of the manuscript: Goel.

Critical revision of the manuscript for important intellectual content: Lusher, Boneh.

Statistical analysis: Goel.

Administrative, technical, or material support: Lusher.

Study supervision: Boneh.

Financial Disclosures: None reported.

References
1.
Hutchesson AC, Bundey S, Preece MA, Hall SK, Green A. A comparison of disease and gene frequencies of inborn errors of metabolism among different ethnic groups in the West Midlands, UK.  J Med Genet. 1998;35(5):366-370PubMedArticle
2.
Applegarth DA, Toone JR, Lowry RB. Incidence of inborn errors of metabolism in British Columbia, 1969-1996.  Pediatrics. 2000;105(1):e10PubMedArticle
3.
Dionisi-Vici C, Rizzo C, Burlina AB,  et al.  Inborn errors of metabolism in the Italian pediatric population: a national retrospective survey.  J Pediatr. 2002;140(3):321-327PubMedArticle
4.
 Consultative Council on Obstetric and Paediatric Mortality and Morbidity (CCOPMM). Victorian Perinatal Data Collection (VPDC). Victorian Birth Defects Register (VBDR). Victoria Department of Health Web site. http://www.health.vic.gov.au/ccopmm/index.htm. Accessed June 10, 2010
5.
Bernier FP, Boneh A, Dennett X, Chow CW, Cleary MA, Thorburn DR. Diagnostic criteria for respiratory chain disorders in adults and children.  Neurology. 2002;59(9):1406-1411PubMedArticle
6.
 Interactive statistical calculation pages. http://statpages.org/index.html. Accessed June 11, 2010
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