gms | German Medical Science

Background: Autism Spectrum Disorder (ASD) is a highly heritable polygenetic disorder with several forms and degrees of handicap. It is currently diagnosed around the age of 6 years. Genetic testing at birth may contribute to earlier diagnosis and treatment, but cost-effectiveness is unproven.

Objective: To model the clinical pathway from diagnosis to early intervention (EI) and outcome in scenarios with genetic diagnostics compared to just psychometric diagnosis that follows a current guideline (Status Quo).

Methods: Early diagnosis based on genetic testing leads to more intensive and effective early intervention. Future scenarios assume genetic screening (Screening), genetic testing on request (GenADD), or genetic testing in cases with a family history of ASD (Predisposition). Simulations on Markov models using software TreeAge v. 18 and parameters found in the literature. The time horizon reached from birth to the 15th year of life or 67 years with cycle length 1 year. The models were stratified by autism severity, i.e. IQ initially below 70 or above. Effectiveness was both, dependency free life years (DFLY) gained by correct diagnosis and successful treatment,and the number of diagnosed patients that became independent after treatment. We choose the insurance view. Just direct costs for diagnostics and treatment were considered. Probabilistic sensitivity analyses (PSA) explore assumptions of different parameters, like the sensitivity of the genetic test, using the precisions stated in the literature or possible future developments.

Results: Status Quo is the most cost-effective scenario with the current parameter values. The other scenarios follow in the order of Predisposition, GenADD, and Screening. None of the scenarios is dominating, though. All scenarios with genetic tests have a higher number of detection than Status Quo. Intensified early intervention may be cost effective with horizon 67 years. The currently high false positive rate of genetic testing might be detrimental to that. The PSA showed distributions with large ranges that cause considerable overlaps in the scatterplot.

Discussion: The descriptive variety and range of the parameters reduced the precision and extended the confidence interval of the parameters and at the end the results on cost-effectiveness. Our model shows that Screening and GenADD should not be an option for inaccurate genetic tests. Once they are more accurate, the potential of early intervention may unfold. By implementing the Canadian clinical pathway, the chance to reach a higher number of DFLY seems to be plausible. Further evaluations with better data need to underpin the current results.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.