Clinical trial NCT02065193: Prevalence of Autism Spectrum Conditions in Mainland China
Official title: Social Communication Research and Epidemiological Study in China
Study type: OBSERVATIONAL
Overall status: UNKNOWN
Conditions: Autism Spectrum Conditions/Disorders
Lead sponsor: University of Cambridge
Sponsor class: OTHER
Collaborators: name: China Disabled Persons Federation
name: Chinese University of Hong Kong
First posted: 2014-02-17
Enrollment: 280000
Sex: ALL
Minimum age (years): 6
Maximum age (years): 11
Standard ages: CHILD
Accepts healthy volunteers: no
Observational model: ECOLOGIC_OR_COMMUNITY
Time perspective: PROSPECTIVE
Sampling method: PROBABILITY_SAMPLE
Study population: Study population in each city is a defined region, usually a district or two districts. We focus on urban populations in this study.

Brief summary: The China SCORE study is a prevalence study of Autism Spectrum Conditions (ASC) in 14 regions in mainland China. It will include the following steps:

1. Large population-based screening This study will be conducted in urban areas but not rural areas across mainland China. One city of each region will participate, and in total there will be 14 cities for screening. Within each city, a number of 40 to 60 ordinary primary schools will be randomly selected from the defined region. All the students who are in 1st to 4th grade will asked to participate in order to form a sample of approximately 20,000 students.

   Screening questionnaires The screening pack includes the Chinese CAST, the AQ-Child, the AQ-Adult short version (10 items), and risk factors questionnaire. An information sheet and consent form will be included in the pack as well.
2. Further assessments We expect approximately 5% on the CAST will score positive in ordinary school population. Thus, for a 20,000 sample, we would expect 900 positives (90% response rate). All the screen-positives and a random selected 5% from borderline group will be invited for clinical assessment. The diagnosis of clinical assessment will be divided into three categories: definite ASC, suspected ASC, and non-ASC. Then all the children with clinical assessment results as definite ASC and suspected ASC and a randomly selected 10-20 non-ASC will be invited for research diagnostic assessment using the ADOS and ADI-R, as well as RPM as IQ test. After that, the consensus diagnosis between ADOS/ADI-R assessment and the clinical diagnosis will be the final diagnosis.
3. Case identification in special schools All the children in special schools or training institutes in study region will be asked to fill in the screening pack. The children who do not attend any ordinary or special schools will be identified according to their residential ID in the studied regions. All screen-positives in special education will be assessed using the ADOS and ADI-R. Then those who met the criteria of ASC on ADOS or/and ADI-R will be assessed by psychiatrists and the clinical diagnosis will be the final diagnosis.

If we combine the prevalence of ordinary schools and special schools together, we will get an estimate of the prevalence of ASC in school-population in China. If we combine all the cases identified from schools and from residential records, we will generate an estimate of the prevalence of ASC in the general population in mainland China.


Eligibility criteria: Inclusion Criteria:

* All children who are in study region will be recruited for this study.
* All children aged 6-11 years old.

Exclusion Criteria:

* Children who are not in the study region.
* Children who are not found from ordinary schools, private training centres, public special schools and community household with the help of local residence records will not be included for this study.

Primary outcomes:
measure: Three-staged consensus diagnosis
timeFrame: The assessments will be finished in one year.
Secondary outcomes:
Other outcomes:
Locations:
city: Fuzhou
country: China
facility: Fujian CDPF
state: Fujian
city: Shenzhen
country: China
facility: Shenzhen CDPF
state: Guangdong
city: Jiamusi
country: China
facility: Heilongjiang CDPF
state: Heilongjiang
city: Luoyang
country: China
facility: Luoyang CDPF
state: Henan
city: Hengyang
country: China
facility: Hengyang CDPF
state: Hunan
city: Jilin
country: China
facility: Jilin Mingzhi Centre
state: Jilin
city: Benxi
country: China
facility: Liaoning CDPF
state: Liaoning
city: Changzhi
country: China
facility: Shanxi CDPF
state: Shanxi
city: Xian
country: China
facility: Shanxi CDPF
state: Shanxi
city: Beijing
country: China
facility: Beijing CDPF
city: Guangzhou
country: China
facility: Guangdong CDPF
city: Hangzhou
country: China
facility: Zhejiang CDPF
city: Wuhan
country: China
facility: Hubei CDPF
city: Yangzhou
country: China
facility: Jiangsu CDPF
Study officials:
affiliation: University of Cambridge
name: Carol Brayne, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: University of Cambridge
name: Simon Baron-Cohen, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: University of Cambridge
name: Carrie Allison, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: China Disabled Persons Federation
name: Hong You, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: China Disabled Persons Federation
name: Jibin Han, Master
role: PRINCIPAL_INVESTIGATOR
affiliation: Chinese University of Hong Kong
name: Sian Griffiths, MD
role: PRINCIPAL_INVESTIGATOR
affiliation: Chinese University of Hong Kong
name: Huso Yi, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: Cambridge/CUHK
name: Xiang Sun, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: MRC Biostatistics Unit
name: Fiona E Matthews, PhD
role: PRINCIPAL_INVESTIGATOR
affiliation: University of Cambridge
name: Bonnie Auyeung, PhD
role: PRINCIPAL_INVESTIGATOR
References: