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The Cost of Raising Individuals with Fragile X or Chromosome 15 Imprinting Disorders in Australia

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Title: The Cost of Raising Individuals with Fragile X or Chromosome 15 Imprinting Disorders in Australia
Language: English
Authors: Baker, Emma K., Arora, Sheena, Amor, David J., Date, Perrin, Cross, Meagan, O'Brien, James, Simons, Chloe, Rogers, Carolyn, Goodall, Stephen, Slee, Jennie, Cahir, Chris, Godler, David E.
Source: Journal of Autism and Developmental Disorders. Apr 2023 53(4):1682-1692.
Availability: Springer. Available from: Springer Nature. One New York Plaza, Suite 4600, New York, NY 10004. Tel: 800-777-4643; Tel: 212-460-1500; Fax: 212-460-1700; e-mail: customerservice@springernature.com; Web site: https://link.springer.com/
Peer Reviewed: Y
Page Count: 11
Publication Date: 2023
Document Type: Journal Articles
Reports - Research
Descriptors: Costs, Child Rearing, Genetic Disorders, Severity (of Disability), Foreign Countries, Autism Spectrum Disorders, Predictor Variables
Geographic Terms: Australia
DOI: 10.1007/s10803-021-05193-4
ISSN: 0162-3257
1573-3432
Abstract: The study characterised differences in costs associated with raising a child between four rare disorders and examined the associations between these costs with clinical severity. Caregivers of 108 individuals with Prader-Willi, Angelman (AS), Chromosome 15q Duplication and fragile X (FXS) syndromes completed a modified Client Services Receipt Inventory and participants completed intellectual/developmental functioning and autism assessments. AS incurred the highest yearly costs per individual ($AUD96,994), while FXS had the lowest costs ($AUD33,221). Intellectual functioning negatively predicted total costs, after controlling for diagnosis. The effect of intellectual functioning on total costs for those with AS was significantly different to the other syndromes. The study highlights the significant costs associated with these syndromes, particularly AS, linked with severity of intellectual functioning.
Abstractor: As Provided
Entry Date: 2023
Accession Number: EJ1372066
Database: ERIC
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  Value: <anid>AN0162852002;aut01apr.23;2023Apr04.06:38;v2.2.500</anid> <title id="AN0162852002-1">The Cost of Raising Individuals with Fragile X or Chromosome 15 Imprinting Disorders in Australia </title> <p>The study characterised differences in costs associated with raising a child between four rare disorders and examined the associations between these costs with clinical severity. Caregivers of 108 individuals with Prader-Willi, Angelman (AS), Chromosome 15q Duplication and fragile X (FXS) syndromes completed a modified Client Services Receipt Inventory and participants completed intellectual/developmental functioning and autism assessments. AS incurred the highest yearly costs per individual ($AUD96,994), while FXS had the lowest costs ($AUD33,221). Intellectual functioning negatively predicted total costs, after controlling for diagnosis. The effect of intellectual functioning on total costs for those with AS was significantly different to the other syndromes. The study highlights the significant costs associated with these syndromes, particularly AS, linked with severity of intellectual functioning.</p> <p>Keywords: Fragile X syndrome; Angelman syndrome; Prader-Willi syndrome; Chromosome 15 Duplication syndrome; Health Economics</p> <p>Supplementary Information The online version contains supplementary material available at https://doi.org/10.1007/s10803-021-05193-4.</p> <hd id="AN0162852002-2">Introduction</hd> <p>Fragile X syndrome (FXS) and chromosome 15 (C15) imprinting disorders, including Angelman (AS), Prader-Willi (PWS) and Chromosome 15q duplication (Dup15q) syndromes are characterised by varying degrees of intellectual disability (ID), autism spectrum disorder (ASD) features, and challenging behaviours (Kalsner & Chamberlain, [<reflink idref="bib28" id="ref1">28</reflink>]; Raspa et al., [<reflink idref="bib41" id="ref2">41</reflink>]). Approximately 135 individuals are born with one of these syndromes each year in Australia. Most infants with AS, FXS, and Dup15q syndrome are not diagnosed within the first year of life (Supplemental Table S1 for summary of each syndrome). For PWS, diagnosis in infancy allows early initiation of growth hormone treatment (Kimonis et al., [<reflink idref="bib31" id="ref3">31</reflink>]). Such early <emph>targeted</emph> interventions are reliant on early diagnosis (e.g., communication/speech, physical, and behaviour therapies). Early diagnoses may now be possible through inclusion of each of these syndromes in population wide newborn screening (NBS) using a methylation-based screening method that has recently been developed called Methylation Specific Quantitative Melt Analysis (MS-QMA; Inaba et al., [<reflink idref="bib27" id="ref4">27</reflink>]; Kraan et al., [<reflink idref="bib32" id="ref5">32</reflink>]). MS-QMA can be used to screen for the four syndromes simultaneously based on the levels of DNA methylation, at a reagent cost consistent with the costs of other conditions currently included in state sponsored NBS programs. However, in addition to having a validated screening test, inclusion of these and other conditions in NBS panels requires further, specific criteria to be met. These include the benefits to the infants and to society (e.g., economic benefits) outweighing the risks and burdens of screening and treatment (Department of Health., [<reflink idref="bib19" id="ref6">19</reflink>]; Therrell et al., [<reflink idref="bib45" id="ref7">45</reflink>]).</p> <p>In Australia, the inclusion of new tests and/or new conditions for existing newborn screening panels for public subsidy is considered by the Medical Services Advisory Committee (MSAC). MSAC appraises new medical services proposed for public funding and provides advice to Government on whether a new medical service should be publicly funded on an assessment of its comparative safety, clinical effectiveness, cost-effectiveness, and total cost, using the best available evidence.</p> <p>This study aims to understand the costs associated with these conditions and to help identify the cost savings that might result from earlier diagnosis and interventions targeting these conditions. This information will assist in the assessment of combined screening for FXS, PWS, AS and Dup15q syndrome for public subsidy. For these conditions to be included in publicly subsidised programs in Australia, and in many other countries with Health Technology Assessment systems (e.g., Canada, UK, Scotland, Japan), the costs and health outcomes of the test must be considered, usually using cost-utility analyses (CUA) or cost effectiveness analyses (CEA). CUAs and CEAs allow the intervention (the test) to be compared to the status quo by estimating the cost per gain in a unit of health outcome. Therefore, an understanding of the costs associated with each condition is imperative in assessing the relative benefit/cost ratio of any intervention targeting that condition. These analyses will also help with understanding how new therapies, currently being trialled for these disorders (https://clinicaltrials.gov/), may reduce the costs associated with these disorders.</p> <p>While there is some literature exploring medical or resource utilisation in AS and PWS (Khan et al., [<reflink idref="bib30" id="ref8">30</reflink>]; Shoffstall et al., [<reflink idref="bib44" id="ref9">44</reflink>]), there is no literature, to our knowledge, comparing overall costs associated with caring for individuals with PWS, AS or Dup15q syndrome, internationally or in the Australian context. The clinical and medical presentations of each of these syndromes will likely result in increased health care resource utilisation. For example, severe seizures occur in more than 80% of individuals with AS (Bindels-de Heus et al., [<reflink idref="bib15" id="ref10">15</reflink>]) and Dup15q syndrome (isodicentric subtype; Conant et al., [<reflink idref="bib18" id="ref11">18</reflink>]) and require ongoing monitoring and treatment throughout the lifespan (Khan et al., [<reflink idref="bib30" id="ref12">30</reflink>]; Thomson et al., [<reflink idref="bib46" id="ref13">46</reflink>]). Larson and colleagues ([<reflink idref="bib33" id="ref14">33</reflink>]) found that the frequency and severity of seizures increased in adults with AS aged over 25 years compared to young persons with AS aged 16–20 years. For PWS, overweight and obesity is reported in 40% of children and adolescents (Diene et al., [<reflink idref="bib20" id="ref15">20</reflink>]), and up to 98% of adults with the syndrome (Grugni et al., [<reflink idref="bib25" id="ref16">25</reflink>]), which significantly increases the risk for morbidity if not externally supported (Butler et al., [<reflink idref="bib16" id="ref17">16</reflink>]).</p> <p>Autistic features are also commonly observed in each of these syndromes. However, the prevalence of individuals meeting Diagnostic and Statistical Manual (DSM) criteria for ASD varies between research studies for each syndrome, given varying methodologies and assessments are often used to define ASD. Approximately 30% of individuals with FXS (Richards et al., [<reflink idref="bib42" id="ref18">42</reflink>]), 26.7% with PWS (Bennett et al., [<reflink idref="bib14" id="ref19">14</reflink>]), and 34% with AS (Richards et al., [<reflink idref="bib42" id="ref20">42</reflink>]) are reported to meet diagnostic criteria for ASD. Compared to other copy number variants known to cause ASD, Dup15q syndrome confers the greatest risk (Moreno-De-Luca et al., [<reflink idref="bib35" id="ref21">35</reflink>]), and as such most individuals with Dup15q syndrome meet diagnostic criteria for ASD (DiStefano et al., [<reflink idref="bib21" id="ref22">21</reflink>]). Nonetheless, across all four syndromes autistic features are common, regardless of whether these symptoms meet diagnostic thresholds.</p> <p>Understanding the magnitude and pattern of costs associated with these disorders can assist in the prioritisation and cost-effective provision of screening programs, health care, and early intervention services for FXS, AS, PWS and Dup15q syndrome, with broader implications for other rare syndromes where ID and ASD are significant comorbidities. Thus, this study explores the similarities and differences in the costs associated with caring for individuals affected with these syndromes in the Australian setting, aiming to characterise costs based on comorbidities, behavioural challenges, and age of diagnosis. It was hypothesised that costs would differ between these groups linked to the specific comorbidities experienced by each syndrome, with ID and ASD severity providing a major contribution to these costs.</p> <hd id="AN0162852002-3">Method</hd> <p></p> <hd id="AN0162852002-4">Participants</hd> <p>This study included 108 individuals, aged between 8 months and 45 years, with a diagnosis of FXS, PWS, AS, or Dup15q syndrome. Participants were recruited between November 2016 and March 2019 via Victorian Clinical Genetics Services, Hunter Genetics (NSW), Genetics Services of Western Australia, and Australian disorder specific support groups and organisations. Participants were included in the study based on a molecular diagnosis of the respective syndrome (confirmed with diagnostic reports). For males with FXS, 36% were <emph>FMR1</emph> CGG size mosaic. That is, they were mosaic for <emph>FMR1</emph> alleles termed premutation (PM: 55–199 CGG repeats) in combination with methylated full mutation (FM: ≥ 200 CGG repeats) <emph>FMR1</emph> alleles that cause FXS. All females with FXS and remaining males only had FM alleles. The genetic molecular classes of the C15 imprinting disorder groups are presented in Supplemental Table S2. Study exclusion criteria included any other genetic conditions, the presence of significant medical or neurological condition(s) including stroke, malignancies, severe head trauma, liver or renal failure, and inadequate control of seizures.</p> <hd id="AN0162852002-5">Materials</hd> <p>Parents/caregivers completed a modified version of the Client Service Receipt Inventory (CSRI; Supplemental Material Appendix A). Modification of the CSRI was undertaken in consultation with stakeholders, family support organisations (Prader-Willi Syndrome Association of Australia, Foundation for Angelman Syndrome Therapeutics; Dup15q Australia Ltd) and clinical specialists to include disorder specific information. The original CSRI was developed for patients with psychiatric disorders (Beecham & Knapp, [<reflink idref="bib13" id="ref23">13</reflink>]) but has also been used in studies of patients with ID (Doran et al., [<reflink idref="bib22" id="ref24">22</reflink>]). The CSRI collects data on service utilisation, household composition, income, and care arrangements (Beecham & Knapp, [<reflink idref="bib13" id="ref25">13</reflink>]). Parents/caregivers also completed a developmental and medical history questionnaire which included questions regarding lifetime presence of seizures.</p> <p>Parents/caregivers also completed the Aberrant Behaviour Checklist-Community (ABC-C; Aman et al., [<reflink idref="bib1" id="ref26">1</reflink>]) to assess behavioural problems. For the FXS group the fragile X specific version of the ABC-C was used (Sansone et al., [<reflink idref="bib43" id="ref27">43</reflink>]), while for the C15 imprinting syndromes, the original ABC-C scoring was used. Kerr and colleagues ([<reflink idref="bib29" id="ref28">29</reflink>]) developed a utility index (UI) from the ABC-C, in order to estimate health-related quality of life impact for economic evaluation. Briefly, the ABC-UI was developed to enable reporting of health state utility scores in children, adolescents, and adults with FXS, based on responses to the ABC-C. Nine key health items to determine health related quality of life impacts in FXS were selected via statistical analyses and clinical experts (Kerr et al., [<reflink idref="bib29" id="ref29">29</reflink>]). We applied this algorithm to all FXS participants' ABC-C questionnaires.</p> <p>Participants aged > 12 months who were at a minimum cruising/walking were assessed with the Autism Diagnostic Observation Schedule-2nd edition (ADOS-2; Lord et al., [<reflink idref="bib34" id="ref30">34</reflink>]), a semi-structured assessment of autism symptoms in the domains of social affect and restricted and repetitive behaviours. The ADOS-2 also provides categorical classifications: Autism, Autism Spectrum and Non-Spectrum. In this study, participants were classified with ASD if they met the ADOS-2 cut-off for 'Autism' or 'Autism Spectrum' and non ASD if they met the 'Non-Spectrum' cut-off.</p> <p>The Mullen Scales of Early Learning (Mullen, [<reflink idref="bib36" id="ref31">36</reflink>]) was used to assess intellectual functioning in FXS and PWS children aged 8 months to 2 years and 11 months and all individuals with AS. An age-appropriate Wechsler intelligence scale (Wechsler, [<reflink idref="bib47" id="ref32">47</reflink>], [<reflink idref="bib48" id="ref33">48</reflink>], [<reflink idref="bib49" id="ref34">49</reflink>]) was used for the remaining FXS and PWS individuals. Given the propensity for many individuals with FXS and C15 imprinting disorders to fall at the floor on standardised intellectual functioning assessments, we used corrected full-scale intelligence quotient scores (cFSIQ; see Arpone et al., [<reflink idref="bib3" id="ref35">3</reflink>] for a description of this method). Depending on the developmental level observed during the ADOS-2 the individual with Dup15q syndrome, completed either the MSEL or an age-appropriate Wechsler scale. Thus, the MSEL was used beyond its normative age range in some individuals with AS and Dup15q syndrome, with IQ scores calculated, as previously described (Baker et al., [<reflink idref="bib12" id="ref36">12</reflink>], [<reflink idref="bib11" id="ref37">11</reflink>]).</p> <hd id="AN0162852002-6">Data Analysis/Empirical Approach</hd> <p>Costs were estimated using individual data (bottom-up approach). The CSRI asked caregivers to recall resource and service utilisation across varying time periods (1 month to 1 year) depending on the resource/service category. In this study costs were standardised to reflect the costs incurred in the previous one-year period. Costs are reported per resource use category and by syndrome. Where participants had a diagnosis of FXS further sub-group analyses were conducted, analysing cost by sex, combining participants with a FM allele and mosaicism for PM and FM (PM/FM) alleles.</p> <p>Resource utilisation, service use, and government benefits are reported as costs incurred in the previous year. A societal perspective was adopted, reporting costs incurred by the healthcare system but also costs incurred by individuals and families. Whether the cost was incurred by the individual or by government was determined by assuming that all costs relating to that resource use category were incurred by the most likely payer in the Australian health care context. For example, in Australia most prescription medicines are publicly funded and as such the analysis assumed that these costs were incurred by government. The questionnaire asked individuals to report resource and service utilisation that related to their disability.</p> <p>Resource utilisation (including equipment, medications, and transportation) service use (including out of home care, hospital admissions, outpatient visits, special education, group home/residential care), lost employment, informal care and government benefits received for each individual were collected via the modified CSRI (Supplemental Table S3 for costs and their sources). Examples of equipment used by participants included but were not limited to wheelchairs, toilet aids, hoists, walkers, special car seats and supportive clothing. Medications included prescription medications and over-the-counter medications. Transport costs were those costs reported by the caregiver to be a result of the child's disability. Participants were asked to self-report how much they spent on transport as a result of the medical condition, for example taxi journeys and payments for special school buses. Out of home care included social, short-term, overnight or day respite. Hospital admissions included inpatient visits or emergency department visits and outpatient visits included visits to general practitioners, medical specialists, or other allied health practitioners. Informal care refers to unpaid care provided by people such as grandparents, aunts, uncles, other family and friends. While informal care is unpaid it carries an opportunity cost, whereby the care provided represents a cost to the family and society, in terms of hours in paid employment and leisure hours forgone. The opportunity cost of informal care was valued using the average hourly wage. Costs relating to informal care provided by the primary caregiver were not included.</p> <p>Previous year costs relating to special education for individuals aged under five years and 18 years and over were assumed to be zero since they reported not being in any education. Costs relating to unemployment relate to the number of weeks the affected individuals aged over 18 years old were not in paid employment. The total cost of unemployment was calculated by multiplying the number of weeks in unemployment by the average Australian weekly income (Australian Bureau of Statistics, [<reflink idref="bib5" id="ref38">5</reflink>], [<reflink idref="bib6" id="ref39">6</reflink>]). This total cost of unemployment was then split into cost to government and cost to individual, according to the average taxation rate.</p> <p>Source data for the costs applied included the Schooling Resource Standard (Australian Government Department of Education, [<reflink idref="bib7" id="ref40">7</reflink>]), National Disability Insurance Scheme (NDIS) Price Guide and Support Catalogue (Australian Government, [<reflink idref="bib10" id="ref41">10</reflink>]), Australian Bureau of Statistics (Australian Bureau of Statistics, [<reflink idref="bib4" id="ref42">4</reflink>], [<reflink idref="bib5" id="ref43">5</reflink>]), Medicare Benefits Schedule (Australian Government Department of Health, [<reflink idref="bib8" id="ref44">8</reflink>]), Pharmaceutical Benefits Scheme (Australian Government Department of Health, [<reflink idref="bib9" id="ref45">9</reflink>]), FXS and AS equipment survey (Supplemental Note S1). All costs were inflated to 2019/2020 prices using inflation rates derived using the average service price inflation (Australian Bureau of Statistics, [<reflink idref="bib6" id="ref46">6</reflink>]).</p> <p>Multiple regression analyses were conducted to measure whether the participant's diagnosis, experience of seizures, and presence of ASD and behavioural problems were associated with increased total costs. Regression analyses used FXS as the base, as there is currently a greater understanding of the economic cost of FXS and the sample of FXS was larger than the C15 imprinting disorder groups. All analyses controlled for the following variables: participant age, participant sex, country of birth, and primary language. Three regression analyses were conducted to analyse the effect of participant's diagnosis and comorbidities on total costs, as detailed in Supplemental Note S2. In the first regression model the effect of diagnostic category on total cost was estimated. In the second regression model total cost was regressed on diagnostic category, seizures, age of diagnosis, and behaviour. In the third regression model diagnostic category was interacted with FSIQ. Participants with a missing response for any of the covariates controlled for within the models were removed via listwise deletion in STATA.</p> <p>Given FXS is an X linked condition where females are usually less severely affected, another set of multiple regression analyses were used to assess whether participant's sex influenced costs in FXS. Consistent with the previous regression analyses experience of seizures, and presence of ASD and behavioural problems were also included in these models. All analyses controlled for participant age, country of birth, and primary language (see Supplemental Note S3 for details).</p> <hd id="AN0162852002-7">Results</hd> <p>Table 1 shows the sample characteristics and Supplemental Figure S1 provides the distribution of age for participants affected with each syndrome. Table 2 shows the costs associated with each syndrome. AS incurred the highest mean cost per person ($AUD 96,988). The cost per individual in the previous year was $AUD 57,576 for PWS, $AUD 52,130 for Dup15q syndrome and $AUD 33,219 for FXS. Of participants with FXS (FM only and PM/FM mosaic), males had a higher cost than females ($AUD 38,569 compared to $AUD 24,164; Supplementary Table S4). The resource use categories with the largest costs were incurred by the government, including government benefits paid to individuals/families, and costs associated with unemployment of the affected individual, group home/residential care living, and informal care.</p> <p>Table 1 Sample characteristics of FXS, PWS, AS and Dup15q syndrome</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" rowspan="2" /><th align="left" colspan="2"><p>FXS</p></th><th align="left" colspan="2"><p>PWS</p></th><th align="left" colspan="2"><p>AS</p></th><th align="left" colspan="2"><p>Dup15q syndrome</p></th></tr><tr><th align="left"><p>n</p></th><th align="left"><p>M (SD)</p></th><th align="left"><p>n</p></th><th align="left"><p>M (SD)</p></th><th align="left"><p>n</p></th><th align="left"><p>M (SD)</p></th><th align="left"><p>n</p></th><th align="left"><p>M (SD)</p></th></tr></thead><tbody><tr><td align="left"><p>Age at assessment (yrs)</p></td><td align="left"><p>35</p></td><td align="left"><p>9.44 (9.24)</p></td><td align="left"><p>32</p></td><td align="left"><p>10.32 (10.40)</p></td><td align="left"><p>27</p></td><td align="left"><p>11.63 (9.75)</p></td><td align="left"><p>14</p></td><td align="left"><p>9.84 (7.18)</p></td></tr><tr><td align="left"><p>Age at diagnosis (mths)</p></td><td align="left"><p>34</p></td><td align="left"><p>29.71 (3.94)</p></td><td align="left"><p>32</p></td><td align="left"><p>18.50 (58.08)</p></td><td align="left"><p>27</p></td><td align="left"><p>52.85 (87.01)</p></td><td align="left"><p>13</p></td><td align="left"><p>30.81 (26.72)</p></td></tr><tr><td align="left"><p>cFSIQ</p></td><td align="left"><p>35</p></td><td align="left"><p>51.71 (22.74)</p></td><td align="left"><p>31</p></td><td align="left"><p>59.77 (15.95)</p></td><td align="left"><p>26</p></td><td align="left"><p>22.04 (12.93)</p></td><td align="left"><p>13</p></td><td align="left"><p>33.77 (26.09)</p></td></tr><tr><td align="left"><p>ABC UI</p></td><td align="left"><p>35</p></td><td align="left"><p>0.764 (0.148)</p></td><td align="left"><p>28</p></td><td align="left"><p>0.758 (0.181)</p></td><td align="left"><p>27</p></td><td align="left"><p>0.757 (0.111)</p></td><td align="left"><p>13</p></td><td align="left"><p>0.581 (0.200))</p></td></tr><tr><td align="left"><p>Irritability</p></td><td align="left"><p>35</p></td><td align="left"><p>8.40 (7.13)</p></td><td align="left"><p>28</p></td><td align="left"><p>9.36 (9.64)</p></td><td align="left"><p>27</p></td><td align="left"><p>7.19 (5.39)</p></td><td align="left"><p>13</p></td><td align="left"><p>13.77 (10.22)</p></td></tr><tr><td align="left"><p>Lethargy</p></td><td align="left"><p>35</p></td><td align="left"><p>4.43 (4.17)</p></td><td align="left"><p>28</p></td><td align="left"><p>6.25 (5.35)</p></td><td align="left"><p>27</p></td><td align="left"><p>3.63 (3.59)</p></td><td align="left"><p>13</p></td><td align="left"><p>11.31 (10.28)</p></td></tr><tr><td align="left"><p>Stereotypy</p></td><td align="left"><p>35</p></td><td align="left"><p>3.17 (3.16)</p></td><td align="left"><p>28</p></td><td align="left"><p>2.11 (3.00)</p></td><td align="left"><p>27</p></td><td align="left"><p>4.04 (4.01)</p></td><td align="left"><p>13</p></td><td align="left"><p>8.08 (5.68)</p></td></tr><tr><td align="left"><p>Hyperactivity</p></td><td align="left"><p>35</p></td><td align="left"><p>8.63 (7.73)</p></td><td align="left"><p>28</p></td><td align="left"><p>8.82 (9.03)</p></td><td align="left"><p>27</p></td><td align="left"><p>16.11 (10.43)</p></td><td align="left"><p>13</p></td><td align="left"><p>24.62 (15.77)</p></td></tr><tr><td align="left"><p>Inappropriate Speech</p></td><td align="left"><p>35</p></td><td align="left"><p>2.29 (3.11)</p></td><td align="left"><p>28</p></td><td align="left"><p>3.43 (3.21)</p></td><td align="left"><p>27</p></td><td align="left"><p>0.41 (0.93)</p></td><td align="left"><p>13</p></td><td align="left"><p>4.31 (3.92)</p></td></tr><tr><td align="left"><p>Social Avoidance</p></td><td align="left"><p>35</p></td><td align="left"><p>2.11 (2.70)</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td></tr></tbody></table> </ephtml> </p> <p>Table 1 Sample characteristics of FXS, PWS, AS and Dup15q syndrome</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left" /><th align="left"><p>n</p></th><th align="left"><p>%</p></th><th align="left"><p>n</p></th><th align="left"><p>%</p></th><th align="left"><p>n</p></th><th align="left"><p>%</p></th><th align="left"><p>n</p></th><th align="left"><p>%</p></th></tr></thead><tbody><tr><td align="left"><p>% male</p></td><td align="left"><p>35</p></td><td align="left"><p>62.9%</p></td><td align="left"><p>32</p></td><td align="left"><p>46.9%</p></td><td align="left"><p>27</p></td><td align="left"><p>59.3%</p></td><td align="left"><p>14</p></td><td align="left"><p>57.1%</p></td></tr><tr><td align="left"><p>Children/Adolescents (< 18 yrs)</p></td><td align="left"><p>35</p></td><td align="left"><p>91.4%</p></td><td align="left"><p>32</p></td><td align="left"><p>81.1%</p></td><td align="left"><p>27</p></td><td align="left"><p>66.7%</p></td><td align="left"><p>14</p></td><td align="left"><p>92.9%</p></td></tr><tr><td align="left"><p>Children (< 5 yrs)</p></td><td align="left"><p>35</p></td><td align="left"><p>28.6%</p></td><td align="left"><p>32</p></td><td align="left"><p>37.5%</p></td><td align="left"><p>27</p></td><td align="left"><p>33.3%</p></td><td align="left"><p>14</p></td><td align="left"><p>28.6%</p></td></tr><tr><td align="left"><p>% seizures</p></td><td align="left"><p>35</p></td><td align="left"><p>11.4%</p></td><td align="left"><p>31</p></td><td align="left"><p>12.9%</p></td><td align="left"><p>27</p></td><td align="left"><p>74.1%</p></td><td align="left"><p>14</p></td><td align="left"><p>57.1%</p></td></tr><tr><td align="left"><p>Country of birth</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>Australia</p></td><td align="left"><p>34</p></td><td align="left"><p>97.1%</p></td><td align="left"><p>32</p></td><td align="left"><p>96.8%</p></td><td align="left"><p>27</p></td><td align="left"><p>96.3%</p></td><td align="left"><p>14</p></td><td align="left"><p>92.9%</p></td></tr><tr><td align="left"><p>Other</p></td><td align="left"><p>34</p></td><td align="left"><p>2.9%</p></td><td align="left"><p>32</p></td><td align="left"><p>3.1%</p></td><td align="left"><p>27</p></td><td align="left"><p>3.7%</p></td><td align="left"><p>14</p></td><td align="left"><p>7.1%</p></td></tr><tr><td align="left"><p>Primary Language</p></td><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /><td align="left" /></tr><tr><td align="left"><p>English</p></td><td align="left"><p>33</p></td><td align="left"><p>97.0%</p></td><td align="left"><p>32</p></td><td align="left"><p>90.6%</p></td><td align="left"><p>27</p></td><td align="left"><p>100.0%</p></td><td align="left"><p>14</p></td><td align="left"><p>100.0%</p></td></tr><tr><td align="left"><p>Other</p></td><td align="left"><p>33</p></td><td align="left"><p>3.0%</p></td><td align="left"><p>32</p></td><td align="left"><p>9.4%</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td><td align="left"><p>–</p></td></tr><tr><td align="left"><p>ASD (ADOS-2)</p></td><td align="left"><p>35</p></td><td align="left"><p>82.9%</p></td><td align="left"><p>27</p></td><td align="left"><p>70.4%</p></td><td align="left"><p>25</p></td><td align="left"><p>44.4%</p></td><td align="left"><p>11</p></td><td align="left"><p>100%</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>ABC UI</emph> Aberrant Behavior Checklist Utility Index, <emph>ADOS-2</emph> Autism Diagnostic Observation Schedule-2nd edition, <emph>AS</emph> Angelman syndrome, <emph>ASD</emph> autism spectrum disorder, <emph>cFSIQ</emph> corrected full scale IQ, <emph>Dup15q</emph> Chromosome 15q duplication syndrome, <emph>FXS</emph> Fragile X syndrome, <emph>M</emph> mean, <emph>PWS</emph> Prader-Willi syndrome, <emph>SD</emph> standard deviation</p> <p>Table 2 Mean costs relating to the participant's disability in the previous year by syndrome</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Cost category</p></th><th align="left"><p>FXS</p><p>Total cost ($) (95%CI)</p><p>N = 35</p></th><th align="left"><p>PWS</p><p>Total cost ($) (95%CI)</p><p>N = 32</p></th><th align="left"><p>AS</p><p>Total cost ($) (95%CI)</p><p>N = 27</p></th><th align="left"><p>Dup15q syndrome</p><p>Total cost ($) (95%CI)</p><p>N = 14</p></th></tr></thead><tbody><tr><td align="left"><p>Out of home care</p></td><td align="left"><p>5332 (694 to 9971)</p></td><td align="left"><p>1926 (358 to 3494)</p></td><td align="left"><p>15,738 (1921 to 29,553)</p></td><td align="left"><p>6414 (− 2153 to 14,981)</p></td></tr><tr><td align="left"><p>Cost of purchasing and renting equipment</p></td><td align="left"><p>149 (44–253)</p></td><td align="left"><p>321 (82–560)</p></td><td align="left"><p>430 (276–584)</p></td><td align="left"><p>488 (175–802)</p></td></tr><tr><td align="left"><p>Government benefits</p></td><td align="left"><p>6752 (2651–10,583)</p></td><td align="left"><p>10,020 (4905–15,134)</p></td><td align="left"><p>9149 (3668–14,631)</p></td><td align="left"><p>7637 (724–14,549)</p></td></tr><tr><td align="left"><p>Inpatient and ED hospital admissions</p></td><td align="left"><p>NR</p></td><td align="left"><p>2586 (-462–5632)</p></td><td align="left"><p>4794 (− 360–9947)</p></td><td align="left"><p>5910 (− 3119–14,938)</p></td></tr><tr><td align="left"><p>Outpatient visits</p></td><td align="left"><p>5469 (3504–7434)</p></td><td align="left"><p>6303 (4095–8511)</p></td><td align="left"><p>5181 (2901–7462)</p></td><td align="left"><p>8386 (4420–12,353)</p></td></tr><tr><td align="left"><p>Cost of medications</p></td><td align="left"><p>300 (100–500)</p></td><td align="left"><p>7714 (4909–10,520)</p></td><td align="left"><p>587 (364–810)</p></td><td align="left"><p>542 (-43–1127)</p></td></tr><tr><td align="left"><p>Special education</p></td><td align="left"><p>7483 (3500–12,186)</p></td><td align="left"><p>4047 (1489–6645)</p></td><td align="left"><p>5288 (868–9707)</p></td><td align="left"><p>15,997 (7979–24,014)</p></td></tr><tr><td align="left"><p>Group home/residential care living</p></td><td align="left"><p>NR</p></td><td align="left"><p>8001 (−7831–23,833)</p></td><td align="left"><p>28,449 (-2775–59,674)</p></td><td align="left"><p>NR</p></td></tr><tr><td align="left"><p>Lost employment / employment taxation</p></td><td align="left"><p>3735 (-1553–9024)</p></td><td align="left"><p>12,256 (3189–21,322)</p></td><td align="left"><p>19,367 (7785–30,949)</p></td><td align="left"><p>4669 (−4569–13,907)</p></td></tr><tr><td align="left"><p>Informal care (excl. primary caregivers)</p></td><td align="left"><p>4534 (254–8815)</p></td><td align="left"><p>5909 (508–11,310)</p></td><td align="left"><p>8320 (1524–15,116)</p></td><td align="left"><p>2674 (-1533–6881)</p></td></tr><tr><td align="left"><p>Transportation</p></td><td align="left"><p>1869 (-701–4440)</p></td><td align="left"><p>1182 (567–1797)</p></td><td align="left"><p>1502 (687–2317)</p></td><td align="left"><p>1110 (69–2150)</p></td></tr><tr><td align="left"><p>Total cost to government</p></td><td align="left"><p>25,485 (16,068–34,092)</p></td><td align="left"><p>42,481 (25,844–78,086)</p></td><td align="left"><p>72,870 (39,554–106,187)</p></td><td align="left"><p>45,031 (31,472–58,591)</p></td></tr><tr><td align="left"><p>Total cost to individual/family</p></td><td align="left"><p>7733 (2747–12,719)</p></td><td align="left"><p>15,095 (7249–22,941)</p></td><td align="left"><p>24,118 (14,346–33,889)</p></td><td align="left"><p>7099 (-964–15,162)</p></td></tr><tr><td align="left"><p>Total cost</p></td><td align="left"><p>33,219 (23,653–42,784)</p></td><td align="left"><p>57,576 (37,030–78,123)</p></td><td align="left"><p>96,988 (59,025–134,951)</p></td><td align="left"><p>52,130 (36,091–68,169)</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>AS</emph> Angelman syndrome, <emph>CI</emph> confidence interval, <emph>Dup15q</emph> Chromosome 15q duplication syndrome, <emph>ED</emph> emergency department, <emph>FXS</emph> Fragile X syndrome, <emph>PWS</emph> Prader-Willi syndrome, <emph>NR</emph> none reported</p> <p>The AS group had significantly greater total costs compared to the FXS group, after controlling for participant age, country of birth, and primary language (Table 3).</p> <p>Table 3 Regression analyses regressing total cost on diagnosis</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Cost category</p></th><th align="left"><p>Total cost Coefficient N = 106</p></th></tr></thead><tbody><tr><td align="left" colspan="2"><p>Diagnosis (base FXS)</p></td></tr><tr><td align="left"><p> PWS</p></td><td align="left"><p>19,731</p></td></tr><tr><td align="left"><p> AS</p></td><td align="left"><p><bold>53,892**</bold></p></td></tr><tr><td align="left"><p> Dup15q syndrome</p></td><td align="left"><p>16,990</p></td></tr><tr><td align="left"><p>Sex (base male)</p></td><td align="left"><p>-10,882</p></td></tr><tr><td align="left"><p>Constant</p></td><td align="left"><p>27,630</p></td></tr><tr><td align="left"><p>R-squared</p></td><td align="left"><p>0.40</p></td></tr></tbody></table> </ephtml> </p> <p>Costings are relative to FXS, positive numbers indicate greater cost than FXS while negative costs indicate less than FXS. All models control for participant age, country of birth and primary language <emph>AS</emph> Angelman syndrome, <emph>Dup15q</emph> Chromosome 15q duplication syndrome, <emph>FXS</emph>, Fragile X syndrome, <emph>PWS</emph> Prader-Willi syndrome ***,**,* = Significant at the < 0.001, 0.01 and 0.05 levels respectively</p> <hd id="AN0162852002-8">Determing Impact of Comorbidities on Costings</hd> <p>Total yearly costs were reduced by a mean of $AUD 734, after controlling for diagnostic category, for every one point increase in cFSIQ (Table 4). Regression analysis that interacted cFSIQ and diagnostic category revealed that the relationship between cFSIQ on costs differed depending on the diagnositc category (Table 4). Marginal effects analysis showed that for those with AS, total cost significantly decreased by $5102 per year per point increase in cFSIQ (Table 5). Post-hoc testing revealed that the difference in the effect of FSIQ on total costs for those with AS was significantly different to those with FXS, PWS or Dup15q syndrome. When the sub-scales of the ABC-C were included in the analysis (Supplemental Table S5) results were consistent with those reported in Table 4.</p> <p>Table 4 Regression analyses (main effects only and interaction of diagnosis with FSIQ) regressing total cost on diagnosis, seizures, age of diagnosis, intellectual functioning, and behavioural problems</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Cost category</p></th><th align="left"><p>Total cost Coefficient N = 93</p></th><th align="left"><p>Interaction model (Diagnosis with FSIQ) N = 93</p></th></tr></thead><tbody><tr><td align="left"><p>Diagnosis (base FXS)</p></td><td align="left" /><td align="left" /></tr><tr><td align="left"><p> PWS</p></td><td align="left"><p>21,874</p></td><td align="left"><p>74,312</p></td></tr><tr><td align="left"><p> AS</p></td><td align="left"><p>29,401</p></td><td align="left"><p><bold>151,951***</bold></p></td></tr><tr><td align="left"><p> Dup15q syndrome</p></td><td align="left"><p> − 10,435</p></td><td align="left"><p>3184</p></td></tr><tr><td align="left"><p>cFSIQ</p></td><td align="left"><p><bold> − 734*</bold></p></td><td align="left"><p> − 351</p></td></tr><tr><td align="left"><p>Diagnosis (base FXS) x cFSIQ</p></td><td align="left" /><td align="left" /></tr><tr><td align="left"><p> PWS</p></td><td align="left"><p>–</p></td><td align="left"><p> − 928</p></td></tr><tr><td align="left"><p> AS</p></td><td align="left"><p>–</p></td><td align="left"><p><bold> − 4751***</bold></p></td></tr><tr><td align="left"><p> Dup15q syndrome</p></td><td align="left"><p>–</p></td><td align="left"><p>107</p></td></tr><tr><td align="left"><p>Seizures</p></td><td align="left"><p>7440</p></td><td align="left"><p> − 8919</p></td></tr><tr><td align="left"><p>ASD (ADOS-2)</p></td><td align="left"><p>2841</p></td><td align="left"><p> − 11,418</p></td></tr><tr><td align="left"><p>ABC-C UI</p></td><td align="left"><p> − 87,946</p></td><td align="left"><p> − 117,786</p></td></tr><tr><td align="left"><p>Age of diagnosis (mths)</p></td><td align="left"><p>129</p></td><td align="left"><p>37</p></td></tr><tr><td align="left"><p>Sex (base male)</p></td><td align="left"><p> − 5369</p></td><td align="left"><p> − 11,291</p></td></tr><tr><td align="left"><p>Constant</p></td><td align="left"><p>115,378</p></td><td align="left"><p><bold>153,326*</bold></p></td></tr><tr><td align="left"><p>R-squared</p></td><td align="left"><p>0.51</p></td><td align="left"><p>0.63</p></td></tr></tbody></table> </ephtml> </p> <p>Costings are relative to FXS, positive numbers indicate greater costs than FXS, while negative numbers indicate less costs than FXS. All models control for participant age, country of birth and primary language <emph>ABC-C UI</emph> Aberrant Behavior Checklist-Community Utility Index, <emph>ADOS-2</emph> Autism Diagnostic Observation Schedule-2nd edition, <emph>AS</emph> Angelman syndrome, <emph>ASD</emph> autism spectrum disorder, <emph>cFSIQ</emph> corrected Full Scale IQ, <emph>Dup15q</emph> Chromosome 15q duplication syndrome, <emph>FXS</emph> Fragile X syndrome, <emph>PWS</emph> Prader-Willi syndrome ***,**,* = Significant at the < 0.001, 0.01 and 0.05 levels respectively</p> <p>Table 5 Marginal effect of FSIQ on total cost by diagnosis category</p> <p> <ephtml> <table frame="hsides" rules="groups"><thead><tr><th align="left"><p>Cost category</p></th><th align="left"><p>Marginal effect ($)</p></th></tr></thead><tbody><tr><td align="left"><p>Diagnosis</p></td><td align="left" /></tr><tr><td align="left"><p>FXS</p></td><td align="left"><p> − 351</p></td></tr><tr><td align="left"><p>PWS</p></td><td align="left"><p> − 1278</p></td></tr><tr><td align="left"><p><bold>AS</bold></p></td><td align="left"><p><bold> − 5102***</bold></p></td></tr><tr><td align="left"><p>Dup15q syndrome</p></td><td align="left"><p> − 244</p></td></tr></tbody></table> </ephtml> </p> <p> <emph>AS</emph> Angelman syndrome, <emph>Dup15q</emph> Chromosome Duplication 15q syndrome, <emph>FXS</emph> Fragile X syndrome, <emph>PWS</emph> Prader-Willi syndrome ***,**,*Significant at the < 0.001, 0.01 and 0.05 levels respectively</p> <hd id="AN0162852002-9">Comparison Between Males and Females with FXS</hd> <p>Females with FXS did not incur significantly different total costs compared to males with FXS after controlling for participant age and country of birth (Supplemental Table S6). Presence of seizures, age of diagnosis, and behavioural issues were not significantly associated with total costs for those with FXS (Supplemental Table S7).</p> <hd id="AN0162852002-10">Discussion</hd> <p>This study demonstrates the considerable economic impact of FXS, PWS, AS and Dup15q syndrome, with the majority of costs incurred by the Australian government (benefits paid to families, unemployment, out of home care). Of the syndromes included in this analysis AS was associated with the highest costs, with a mean annual cost of $AUD 96,988, while FXS was associated with the lowest costs per individual ($AUD 33,219). The estimate for FXS is somewhat lower than has been reported in previous literature (Chevreul et al., [<reflink idref="bib17" id="ref47">17</reflink>]) with the exception of a study in Hungary which estimated the incremental annual per person cost for FXS to be Euro 4951 (~ $AUD 8380) (Chevreul et al., [<reflink idref="bib17" id="ref48">17</reflink>]). However, a study from Sweden (Chevreul et al., [<reflink idref="bib17" id="ref49">17</reflink>]) estimated the incremental annual per person cost of FXS to be Euro 58,862 (~ $AUD 99,630), while another from the US estimated $USD 33,409 (~ $AUD 52,260) (Nazareth et al., [<reflink idref="bib37" id="ref50">37</reflink>]). Differences in estimates are likely due to availability and access to services within each country, the varying healthcare systems, and the aetiology of each cohort studied such as proportion of individuals with PM/FM mosaicism, who usually have better intellectual functioning than their FXS counterparts with only FM alleles (Baker et al., [<reflink idref="bib11" id="ref51">11</reflink>]; Pretto et al., [<reflink idref="bib39" id="ref52">39</reflink>]).</p> <p>Previous research has found that the lost opportunity cost of time spent caring by primary caregivers represents the greatest proportion of the cost burden relating to ID (Doran et al., [<reflink idref="bib22" id="ref53">22</reflink>]). In a recent Australian study of children with ID aged 2–10 years (Arora et al., [<reflink idref="bib2" id="ref54">2</reflink>]), it was estimated that care because of the child's disability cost the individual/family $AUD 5033.69 per month (2018–2019 prices). Moreover, the opportunity cost of lost time spent caring comprised the greatest proportion of the cost burden of childhood ID, which was estimated at $AUD12.501 billion per year based on prevalence estimates of childhood ID in Australia. Thus, our estimates of the economic burden are likely underestimated, given the significant lost opportunity costs that have been attributed to ID more generally. Future research examining the costs associated with these four syndromes should include the lost opportunity cost in the data collection and analyses.</p> <hd id="AN0162852002-11">Cost Implications for Early Diagnosis and Targeted Intervention</hd> <p>Our findings have implications for the diagnostic and clinical care of these syndromes. Our findings showed reductions in total yearly costs were related to better intellectual functioning. Specifically, for every one-point increase in cFSIQ, total yearly costs were reduced by $AUD734. Further analyses demonstrated that the effect of cFSIQ on total costs for those with AS was significantly different to the other three syndromes. This suggests that the severe ID associated with AS (usually more severe than the other three syndromes) is a significant contributor to the financial burden of AS. The findings provide support for interventions that target intellectual/cognitive functioning in these disorders, particularly AS. Even small improvements in intellectual functioning may result in significant cost reductions. However, further research in larger samples of individuals with each condition is required to better understand these relationships.</p> <p>The significant ID in these syndromes may also result in lost employment, as usually one parent is required to take on a full-time caring role. Ouyang and colleagues ([<reflink idref="bib38" id="ref55">38</reflink>]) found that approximately 40% of parents of children with FXS reported quitting employment because of their child's condition. Moreover, multivariate analyses stratified by age and controlling for co-occurring conditions and functional difficulties demonstrated that the odds ratio for the FXS group (aged 12–17 years) was significantly elevated for financial burden, quitting employment, and reducing work hours, relative to children with ASD only. In an Italian study of parents of children with PWS (Ragusa et al., [<reflink idref="bib40" id="ref56">40</reflink>]), 62% of family caregivers reported changing their job after the birth of their child with PWS. More specifically, over one-third left their current work, 8% reported changing jobs to assist the child, 8% requested part-time work, and 3% gave up the perspective of a career. For AS and Dup15q syndrome there is limited data on lost employment. Nonetheless, a recent qualitative study acknowledged reduced caregiver capacity to work as an important factor in a patient centred model of care (Willgoss et al., [<reflink idref="bib50" id="ref57">50</reflink>]). There are now a number of active clinical trials aiming to improve cognitive functioning in FXS, with one recent study (Hessl et al., [<reflink idref="bib26" id="ref58">26</reflink>]) of 100 children and adolescents with FXS demonstrating modest improvements in working memory (WM) and executive functioning skills after undergoing intensive WM training using Cogmed (https://<ulink href="http://www.cogmed.com/">www.cogmed.com/</ulink>). Similarly, there is some evidence for improvement in intellectual functioning with growth hormone use in PWS (Dykens et al., [<reflink idref="bib23" id="ref59">23</reflink>]), with early treatment (before 12 months of age) demonstrating better effects than those treated later (1 to 5 years of age; Dykens et al., [<reflink idref="bib23" id="ref60">23</reflink>]). Based on research demonstrating that the neural circuits in a child's brain are most adaptable in the first three years of life (Goode et al., [<reflink idref="bib24" id="ref61">24</reflink>]) interventions, particularly those targeting cognitive functioning may be most effective when implemented during this early developmental phase. Thus, if future additional targeted interventions became available that demonstrate efficacy in improving intellectual functioning in each syndrome, and the individuals are diagnosed as early as possible (in the 1st year of life) through newborn screening, this may result in significant cost savings to both the government and families.</p> <hd id="AN0162852002-12">Differences in Cost Utilisation</hd> <p>The study also demonstrated differences in cost utilisation across syndromes. In particular individuals with PWS had greater costs related to pharmaceutical use compared to those with FXS, AS or Dup15q syndrome. Higher medication costs in PWS are likely due to the specific comorbid issues experienced by these individuals including obesity and low muscle tone (treated with growth hormone) and hypothyroidism (treated with thyroxine). This finding is consistent with a large study from the USA demonstrating synthetic hormones, predominantly recombinant human growth hormone (rhGH) was a leading driver of medication costs in PWS, particularly for those aged between 5 and 17 years (Shoffstall et al., [<reflink idref="bib44" id="ref62">44</reflink>]).</p> <p>Taken together these findings have implications for funding schemes related to ID more generally (e.g., NDIS in Australia). Providing recommendations regarding allocation of funding based on the specific syndrome and their base set of needs and the specific comorbidities, may assist in informing these government funding schemes and significantly reduce government costs.</p> <hd id="AN0162852002-13">Strengths and Limitations</hd> <p>This study used a modified version of the CSRI that was adapted for the Australian setting but also to include items that were specific to each of the syndromes included in the study. This modified CSRI appears to have been successful in capturing disorder-specific resource utilisation and may be useful for health economic research in other rare disorders. A strength of this study is the detailed cost information reported across a wide range of resource use categories coupled with formal assessments of intellectual functioning and behavioural symptoms in a relatively large cohort for these rare syndromes.</p> <p>A limitation of this study is that without a control group, estimates reported in this study may be overestimated as some medications and visits to health professionals may not be related to the disability itself. Nevertheless, care was taken to collect costs relating only to the disability where possible and costs potentially not related to the disability are likely to represent a small proportion of total costs. Conversely, the costs reported here are more likely to be a significant underestimation of costs incurred by families, as the time spent caring for the participant by primary caregivers was not reported in this study. Moreover, the psychological caregiver burden (e.g., stress, depression) associated with caring for children with these syndromes (Ouyang et al., [<reflink idref="bib38" id="ref63">38</reflink>]; Wulffaert et al., [<reflink idref="bib51" id="ref64">51</reflink>]), represents a potential source of underestimated lost opportunity cost (income) as well as high resource utilisation in the parents themselves (Ouyang et al., [<reflink idref="bib38" id="ref65">38</reflink>]). Further costs relevant under a societal perspective that were not able to be incorporated in the study included those associated with travel and time costs for medical appointments, private health insurance, and early intervention programs and should also be considered in future health economic evaluations.</p> <p>Additionally, the wide age ranges likely influenced costing data. Specifically, special education and group home/residential care living costs were lower than expected for the AS and PWS groups, respectively. This is likely attributed to the AS group having a greater number of adult participants (not in education) and the PWS group having a small number of adults who may be more likely to be in residential care/group homes. Thus, while this study has provided initial costings related to raising and caring for children with these four rare syndromes in Australia, future research in larger independent cohorts is required. Addressing the limitations of this current study by collecting more specific disorder related data for medication and health professional visits as well as costings of lost employment and mental health service use of the carers would be highly beneficial. Another limitation of the current study is that data could not be analysed separately for the specific genetic sub-types of FXS, AS, PWS, and Dup15q syndrome, each with specific co-morbidities, due to the small number of individuals within each molecular class for these disorders.</p> <hd id="AN0162852002-14">Conclusions</hd> <p>The costs associated with raising and caring for individuals with FXS, PWS, AS and Dup15q syndrome are significant and experienced over a wide range of resource use categories including costs associated with out of home care, special education, group home/residential care living, government benefits, lost employment of the affected individual, medications, and visits to health professionals and hospitals. Significant reductions in total yearly costs were related to intellectual functioning across these syndromes, suggesting that the economic burden across these syndromes can be reduced by earlier diagnosis and targeted interventions.</p> <hd id="AN0162852002-15">Authors' Contributions</hd> <p>EKB was involved in the conceptualisation and design of the study, modification of the data collection instrument, collected data, and drafted the initial manuscript. SA carried out the analyses. DJA was involved in the conceptualisation and design of the study, assisted with participant recruitment, and obtained funding to support this study. PD collected data and assisted with data preparation. MC, JO, CS and CC assisted in the modification of the data collection instrument and assisted with participant recruitment. CR and JS assisted in participant recruitment and data collection. SG supervised data analyses. DEG conceptualised and designed the study, supervised data collection, and obtained funding to support this study. All authors critically reviewed the manuscript for important intellectual content and approved the final manuscript as submitted and agree to be accountable for all aspects of the work. All authors had complete access to the study data that support the publication.</p> <hd id="AN0162852002-16">Funding</hd> <p>This study was supported by the Victorian Government's Operational Infrastructure Support Program, with salaries supported by NHMRC project Grants (No. 1049299 and No. 1103389 to DEG.); Murdoch Children's Research Institute, Royal Children's Hospital Foundation (DEG); Next Generation Clinical Researchers Program—Career Development Fellowship, funded by the Medical Research Future Fund (MRF1141334 to DEG); the Financial Markets Foundation for Children (Australia; no. 2017 – 361 to DEG and DJA); the Foundation for Angelman Syndrome Therapeutics (FAST; Australia to EKB); joint funding from the Prader-Willi Syndrome Association of Australia Inc (PWSAA), Prader-Willi Syndrome Association NSW Inc, Prader-Willi Syndrome Association of Victoria Inc, Interaction Disability Services Ltd, FAST Australia, and Dup15q Australia Ltd co-contributed with the Dup15q Alliance (USA) 50/50; and the Foundation for Prader-Willi Research (USA). We would also like to acknowledge Marta Arpone, Annabelle May-Marsh, Nusrat Ahmed and Cherie Green for their assistance with neuropsychological assessments.</p> <hd id="AN0162852002-17">Data Availability</hd> <p>The datasets generated during and/or analysed during the current study are available from the corresponding author on reasonable request.</p> <hd id="AN0162852002-18">Declarations</hd> <p></p> <hd id="AN0162852002-19">Conflict of interest</hd> <p>EKB has received funding for research carried out in this work. SA has acted as a paid consultant to analyse the data presented in this manuscript. MC, JB, CS and CC are affiliated with organisations that in part funded this study. DJA and DEG have all received funding for research carried out in this work. All other authors have no conflicts of interest to declare. Representatives from FAST (MC and CS), PWSAA (JO) and Dup15q Australia Ltd (CC) contributed to the design of the study including modification of the questionnaire used and contributed to drafting of the manuscript. All other funders only provided financial support.</p> <hd id="AN0162852002-20">Ethical Approval</hd> <p>All procedures were approved by The Royal Children's Hospital Human Research Ethics Committees (HREC #33066) and have therefore been performed in accordance with the ethical standards laid down in the 1964 Declaration of Helsinki and its later amendments. All parents/caregivers provided written informed consent and participants who were deemed cognitively able also provided written informed consent.</p> <hd id="AN0162852002-21">Supplementary Information</hd> <p>Below is the link to the electronic supplementary material.</p> <p>Graph: Supplementary file1 (DOCX 190 kb)</p> <hd id="AN0162852002-22">Publisher's Note</hd> <p>Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.</p> <ref id="AN0162852002-23"> <title> References </title> <blist> <bibl id="bib1" idref="ref26" type="bt">1</bibl> <bibtext> Aman MG, Singh NN, Stewart AW, Field CJ. The aberrant behavior checklist: A behavior rating scale for the assessment of treatment effects. American Journal of Mental Deficiency. 1985; 89; 5: 485-491. 3993694</bibtext> </blist> <blist> <bibl id="bib2" idref="ref54" type="bt">2</bibl> <bibtext> Arora S, Goodall S, Viney R, Einfeld S. 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  Group: Src
  Data: 11
– Name: DatePubCY
  Label: Publication Date
  Group: Date
  Data: 2023
– Name: TypeDocument
  Label: Document Type
  Group: TypDoc
  Data: Journal Articles<br />Reports - Research
– Name: Subject
  Label: Descriptors
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Costs%22">Costs</searchLink><br /><searchLink fieldCode="DE" term="%22Child+Rearing%22">Child Rearing</searchLink><br /><searchLink fieldCode="DE" term="%22Genetic+Disorders%22">Genetic Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Severity+%28of+Disability%29%22">Severity (of Disability)</searchLink><br /><searchLink fieldCode="DE" term="%22Foreign+Countries%22">Foreign Countries</searchLink><br /><searchLink fieldCode="DE" term="%22Autism+Spectrum+Disorders%22">Autism Spectrum Disorders</searchLink><br /><searchLink fieldCode="DE" term="%22Predictor+Variables%22">Predictor Variables</searchLink>
– Name: Subject
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Australia%22">Australia</searchLink>
– Name: DOI
  Label: DOI
  Group: ID
  Data: 10.1007/s10803-021-05193-4
– Name: ISSN
  Label: ISSN
  Group: ISSN
  Data: 0162-3257<br />1573-3432
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: The study characterised differences in costs associated with raising a child between four rare disorders and examined the associations between these costs with clinical severity. Caregivers of 108 individuals with Prader-Willi, Angelman (AS), Chromosome 15q Duplication and fragile X (FXS) syndromes completed a modified Client Services Receipt Inventory and participants completed intellectual/developmental functioning and autism assessments. AS incurred the highest yearly costs per individual ($AUD96,994), while FXS had the lowest costs ($AUD33,221). Intellectual functioning negatively predicted total costs, after controlling for diagnosis. The effect of intellectual functioning on total costs for those with AS was significantly different to the other syndromes. The study highlights the significant costs associated with these syndromes, particularly AS, linked with severity of intellectual functioning.
– Name: AbstractInfo
  Label: Abstractor
  Group: Ab
  Data: As Provided
– Name: DateEntry
  Label: Entry Date
  Group: Date
  Data: 2023
– Name: AN
  Label: Accession Number
  Group: ID
  Data: EJ1372066
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1372066
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1007/s10803-021-05193-4
    Languages:
      – Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 11
        StartPage: 1682
    Subjects:
      – SubjectFull: Costs
        Type: general
      – SubjectFull: Child Rearing
        Type: general
      – SubjectFull: Genetic Disorders
        Type: general
      – SubjectFull: Severity (of Disability)
        Type: general
      – SubjectFull: Foreign Countries
        Type: general
      – SubjectFull: Autism Spectrum Disorders
        Type: general
      – SubjectFull: Predictor Variables
        Type: general
      – SubjectFull: Australia
        Type: general
    Titles:
      – TitleFull: The Cost of Raising Individuals with Fragile X or Chromosome 15 Imprinting Disorders in Australia
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Baker, Emma K.
      – PersonEntity:
          Name:
            NameFull: Arora, Sheena
      – PersonEntity:
          Name:
            NameFull: Amor, David J.
      – PersonEntity:
          Name:
            NameFull: Date, Perrin
      – PersonEntity:
          Name:
            NameFull: Cross, Meagan
      – PersonEntity:
          Name:
            NameFull: O'Brien, James
      – PersonEntity:
          Name:
            NameFull: Simons, Chloe
      – PersonEntity:
          Name:
            NameFull: Rogers, Carolyn
      – PersonEntity:
          Name:
            NameFull: Goodall, Stephen
      – PersonEntity:
          Name:
            NameFull: Slee, Jennie
      – PersonEntity:
          Name:
            NameFull: Cahir, Chris
      – PersonEntity:
          Name:
            NameFull: Godler, David E.
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 04
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 0162-3257
            – Type: issn-electronic
              Value: 1573-3432
          Numbering:
            – Type: volume
              Value: 53
            – Type: issue
              Value: 4
          Titles:
            – TitleFull: Journal of Autism and Developmental Disorders
              Type: main
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