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Clinical utility of genomics in childhood syndromes (12-month follow-up)

Clinical utility of genomics in childhood syndromes (12-month follow-up)

Background

Melbourne Genomics’ 16 Clinical Flagships have been at the forefront of determining when genomic testing makes a demonstrable difference to the safety and quality of patient care.

This study was a 12-month follow-up of the Melbourne Genomics Childhood Syndromes Demonstration Flagship (2014-2015). The follow-up study was designed to address questions remaining about the longer-term clinical and health economic impacts of early genomic sequencing.

One of the stated advantages of genomic sequencing (compared to other tests) is that genomic information can be stored and reanalysed in future, as more is learnt about the causes of disease. This study aimed to address whether reanalysis of stored genomic data led to new diagnoses, and the most cost-effective and clinically useful timeframe for reanalysis.

Publications

"Exome Sequencing has higher diagnostic yield compared to simulated disease-specific panels in children with suspected monogenic disorders", Dillon, O., Lunke, S., Stark, Z., Yeung, A., Thorne, N., Gaff, C., White, S., Tan, T., European Journal of Human Genetics (2018) doi:10.1038/s41431-018-0099-1

"Long-term economic impacts of exome sequencing for suspected monogenic disorders: diagnosis, management, and reproductive outcomes", Deborah Schofield, Luke Rynehart, Rupendra Shresthra, Susan M. White and Zornitza Stark, Genetics in Medicine (2019) doi.org/10.1038/s41436-019-0534-x

"Does genomic sequencing early in the diagnostic trajectory make a difference? A follow-up study of clinical outcomes and cost-effectiveness", Stark, Z., Schofield, D., Martyn, M., Rynehart,L., Shrestha, R., Alam, K., Lunke, S., Tan, T.Y., Gaff, C.L., White, S.M., Genetics in Medicine (2018) doi:10.1038/s41436-018-0006-8

Project description and activities

In the Melbourne Genomics Health Alliance Childhood Syndromes Clinical Flagship, 80 children under two years of age with a likely clinical diagnosis received a genomic sequencing test. Importantly, genomic testing was completed at the same time as usual investigations, and the impact of each pathway was rigorously evaluated.

The follow-up study looked at aspects of both the child’s care and family-related outcomes, at least 12 months after test results were returned. Further investigations, health utilisation and health outcomes were determined for the children. Cost-effectiveness studies considered the downstream effects of early diagnosis, as well as the reanalysis of stored data.

The Childhood Syndromes 12-month follow-up study was led by Associate Professor Susan White and Associate Professor Zornitza Stark (both from Murdoch Children’s Research Institute). Health economic analysis was performed with Professor Deborah Schofield.

Outcomes

This study showed that changes in clinical management and health outcomes for children with an early diagnosis led to cost-savings of $1,578 per quality-adjusted life year (QALY) gained, without increasing the use of hospital services.

Cascade testing of family members resulted in diagnosis of an additional 12 relatives. Two of these had their clinical management altered.

The effect of a diagnosis on parents’ reproductive confidence was striking, with nine pregnancies in the diagnosed group compared to one in the undiagnosed group. Genomic sequencing had an additional cost of $8,118 per QALY gained, when the costs and benefits of cascade testing and reproductive service use were considered.

Ongoing usual testing in undiagnosed children did not lead to any new diagnoses. In contrast, four diagnoses were made following reanalysis of stored genomic data. Cost-effectiveness investigations found reanalysis of undiagnosed patients at 18 months offered an incremental cost-saving, with $1,059 saved for each additional diagnosis, compared to the standard care pathway.

Lessons learnt

  • Early diagnosis and changes to management improved health outcomes for children in this cohort, without increasing downstream healthcare costs.

  • Reanalysis of stored genomic data is more effective and cost-effective than ongoing testing.

Impact

This was the first study internationally to systematically follow up patients who had undergone genomic sequencing early in their care.

The evidence generated in this study formed the basis of a Medicare Services Advisory Committee application (undertaken by Australian Genomics using the Melbourne Genomics data). Genetic testing for childhood syndromes item numbers 73358, 73359, 73360, 73361, 73362 and 73363 came into effect on 1 May 2020

Clinical Flagship team




Name

Organisation

Role

Sue White

MCRI/VCGS

Clinical geneticist

Zornitza Stark

MCRI/VCGS

Clinical geneticist

Alicia Oshlack

MCRI

Bioinformatician

Alison Yeung

MCRI/VCGS

Clinical geneticist

Belinda Chong

MCRI/VCGS

Medical scientist

Charlotte Anderson

Victorian Life Sciences Computation Initiative

Bioinformatician

Christiane Theda

Royal Women’s Hospital

Neonatologist

David Amor

MCRI/VCGS

Clinical geneticist

Dylan Mordaunt

Women’s and Children’s Hospital

Pathologist

Emma Creed

Mercy Hospital

Genetic counsellor

Gemma Brett

MCRI/VCGS

Genetic counsellor

George McGillivray

RCH / MCRI/VCGS

Clinical geneticist

Heidi Peters

RCH

Metabolic physician

Ivan Macciocca

MCRI/VCGS

Genetic counsellor

Joy Yaplito-Lee

RCH

Metabolic physician

Katrina Bell

MCRI

Bioinformatician

Khurshid Alam MCRI Health economist

Lilian Downie

MCRI/VCGS

Genetics fellow

Luke Rynehart MCRI Health economist

Maie Walsh

MCRI/VCGS

Genetics fellow

Monique Ryan

RCH / MCRI

Neurologist

Patrick Yap

MCRI/VCGS

Genetics fellow

Paul Ekert

RCH / MCRI

Paediatrician

Paul James

RMH / PeterMac

Clinical geneticist

Peter Georgeson

UoM

Bioinformatician

Ravi Savarirayan

MCRI/VCGS

Clinical geneticist

Richard Leventer

RCH / MCRI

Paediatric neurologist

Rupendra Shrestha University of Sydney Health economist
Sebastian Lunke MCRI/VCGS Medical scientist

Shannon Cowie

MCRI/VCGS

Medical scientist

Simon Sadedin

MCRI/VCGS

Bioinformatician

Tiong Tan

MCRI/VCGS

Clinical geneticist