Early warning score for Autism Spectrum Disorder using real-world data

Date of Approval
Application Number
Technical Summary

Early diagnosis of ASD would allow for early intervention so that children can fully leverage the developmental window to improve faster. Current ASD-specific screening tools have been ineffective, with poor sensitivity and low positive predictive value. This study will fully leverage the personal history of the evolution of conditions in the UK population to assess their potential to provide an early diagnosis. We will develop an early warning scoring system for the prediction of ASD based on a Cox proportional hazards model with time-varying covariates, where both linear and non-linear specifications (e.g. interaction between risk factors) will be explored. We will demonstrate the performance of this system through a robust validation design and by comparing it with existing ASD screening methods (e.g. the modified checklist for Autism in toddlers) and recently developed algorithms in the literature.

Health Outcomes to be Measured

Time to diagnosis of Autism spectrum disorders


Yajing Zhu - Chief Investigator - Roche
Yajing Zhu - Corresponding Applicant - Roche
Christopher Chatham - Collaborator - F. Hoffmann - La Roche Ltd
Kelly Zalocusky - Collaborator - Genentech - Roche Company


CPRD Mother-Baby Link;Patient Level Index of Multiple Deprivation;Practice Level Index of Multiple Deprivation