Background
‘Additional’ or ‘secondary’ genomic findings are changes in genes that indicate a risk of future disease but are unrelated to the reason the patient is undergoing testing. We use the term Additional Findings (AF) when these changes are deliberately sought, rather than being found unintentionally. This is also the term preferred by patients.
Whether to search for such findings and provide them to patients having genomic testing for clinical care is a topic of debate. There are both resourcing and ethical implications.
The provision of AF for a set list of serious, treatable conditions is recommended by the American College of Medical Genetics when patients undergo diagnostic genomic sequencing. It is now standard in the United States to offer AF at the same time as diagnostic testing. European and Canadian guidelines do not actively promote AF analysis, but nor do they preclude it.
Studies internationally are investigating the impact of AF on health outcomes. However, the way in which AF are offered (the ‘model of care’) also requires careful consideration, as this will have impact on uptake, costs and possibly also outcomes.
Publications
“A novel approach to offering additional genomic findings – A protocol to test a two-step approach in the healthcare system”, Martyn, M., Kanga-Parabia, A., Lynch, E., James, P.A., Macciocca, I., Trainer, H.A., Halliday, J., Keogh, L., Wale, J., Winship, I., Bogwitz, M., Valente, G., Walsh, M., Downie, L., Amor, D., Wallis, M., Cunningham, F., Burgess, M., Brown, N.J., Jarmolowicz, A., Lunke, S., Goranitis, I., Melbourne Genomics Health Alliance, Gaff, C.L., Journal of Genetic Counselling (2019). doi:10.1002/jgc4.1102
"Introducing Edna: A trainee chatbot designed to support communication about additional (secondary) genomic findings", David Ireland, DanaKai Bradford, Emma Szepe, Ella Lynch, Melissa Martyn, David Hansen and Clara Gaff, Patient Education and Counselling (2020) https://doi.org/10.1016/j.pec.2020.11.007
"Evaluating the resource implications of different service delivery models for offering additional genomic findings", Martin Vu, Koen Degeling, Melissa Martyn, Elly Lynch, Belinda Chong, Clara Gaff and Maarten J. IJzerman, Genetics in Medicine (2020) https://doi.org/10.1038/s41436-020-01030-8
Project description
The objective of this project was to undertake a proof-of-concept study to better understand the implications of offering additional findings analysis to Victorian patients.
A model of care was evaluated in which adults were offered additional genomic analysis for disease predisposition (‘additional findings’) after diagnostic genomic testing was complete.
Adult participants who had diagnostic testing (or parents of children who had trio whole exome sequencing) through Melbourne Genomics’ clinical projects from 2014 onwards were eligible1.
The proof-of-concept project was led by Melbourne Genomics’ Executive Director, Professor Clara Gaff; Clinical Project Manager, Elly Lynch; and Evaluation Project Manager, Dr Melissa Martyn. The Melbourne Genomics members involved were: The Royal Children’s Hospital, The Royal Melbourne Hospital, Monash Health, Murdoch Children’s Research Institute (Victorian Clinical Genetics Services), Austin Health and The University of Melbourne.
Expert reference groups were formed from the organisations involved, to drive and advise the project.
Activities
Between November 2017 and November 2018, 20 eligible patients were randomly selected each month until 200 people had been approached.
Those electing to receive further information were offered pre-test genetic counselling, with a decision-support kit forwarded prior to this appointment.
Those who attended genetic counselling and consented to AF analysis had their stored genomic data
re-analysed for a list of 58 genes associated with adult-onset conditions with known treatments or intervention publicly funded in Victoria. Results were returned by phone or face-to-face.
The process was then comprehensively evaluated:
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Participants were asked to complete surveys at two time-points (pre- and post-results), to ascertain their understanding, experiences and preferences and were contacted six months following testing, to assess recall of results.
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Genetic counselling consultations were recorded and analysed thematically.
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Genetic counsellors involved in the study were interviewed about their experiences of counselling for AF and their perspectives on service provision and models.
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A focus group was held with laboratory personnel involved in variant interpretation to understand laboratory perspectives.
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Health economic modelling to identify cost-effective service models for AF is underway.
CSIRO has prototyped a ‘chatbot’ (chat robot) for delivery of information to patients about AF2, as an adjunct to genetic counselling.
Dubbed ‘Edna’ (E-DNA), the chatbot is the first of its kind globally developed specifically to support genetic counselling for adults being tested to ascertain future risk of preventable or treatable conditions. Edna is currently undergoing a feasibility trial with patients, genetic counsellors and genetics students, and is slated to undergo a larger-scale patient trial in the near future.
Outcomes and lessons learnt
Findings from this project will be made available following publication of results.
Impact
This was the first study internationally to test such a ‘two-step’ approach to additional findings as a clinical model of care.
Project team
Name |
Organisation |
Role |
Clara Gaff |
Melbourne Genomics |
Executive Director |
Melissa Martyn |
Melbourne Genomics |
Evaluation Project Manager |
Elly Lynch |
Melbourne Genomics |
Clinical Project Manager |
Alison Trainer |
RMH / PeterMac |
Clinical geneticist |
Anaita Kanga-Parabia |
Melbourne Genomics |
Research assistant |
Anna Jarmolowicz |
Melbourne Genomics |
Genetic counsellor |
Anna Ritchie |
MCRI/VCGS |
Medical scientist |
Belinda Chong |
MCRI/VCGS |
Medical scientist |
Belinda Creighton |
Monash Health |
Genetic counsellor |
Crystle Lee |
MCRI/VCGS |
Medical scientist |
David Amor |
MCRI/VCGS |
Clinical geneticist |
Dean Phelan |
MCRI/VCGS |
Medical scientist |
Emily Allen |
MCRI |
Genetic counsellor |
Emily Higgs |
RMH |
Genetic counsellor |
Fiona Cunningham |
Monash Health |
Genetic counsellor |
Giulia Valente |
Melbourne Genomics |
Genetic counsellor |
Heather Chalinor |
Austin Health |
Genetic counsellor |
Helen Curd |
Monash Health |
Genetic counsellor |
Ivan Macciocca |
MCRI/VCGS |
Genetic counsellor |
Jane Halliday |
MCRI |
Epidemiologist |
Janney Wale |
Melbourne Genomics |
Community Advisory Group member |
Katherine Rose |
Monash Health |
Genetic counsellor |
Kirsty West |
Melbourne Genomics |
Genetic counsellor |
Kristin Rigbye |
MCRI/VCGS |
Medical scientist |
Lilian Downie |
MCRI/VCGS |
Genetics fellow |
Ling Lee |
Melbourne Genomics |
Evaluation officer |
Louise Keogh |
UoM |
Health sociologist |
Lucinda Salmon |
Austin Health |
Genetic counsellor |
Maie Walsh |
MCRI/VCGS |
Genetics fellow |
Maira Kentwell |
RMH / PeterMac |
Genetic counsellor |
Matthew Burgess |
Austin Health |
Genetic counsellor |
Megan Cotter |
Austin Health |
Genetic counsellor |
Michael Bogwitz |
RMH |
Genetic counsellor |
Michelle Torres |
MCRI/VCGS |
Medical scientist |
Naomi Baker |
MCRI/VCGS |
Medical scientist |
Natalie Thorne |
Melbourne Genomics |
Head of Innovation and Technology |
Natasha Brown |
MCRI/VCGS |
Clinical geneticist |
Paul James |
RMH / PeterMac |
Clinical geneticist |
Rigan Tytherleigh |
Melbourne Genomics |
Research assistant |
Robyn McNeil |
Melbourne Genomics |
Evaluation officer |
Rona Weerasuriya |
Melbourne Genomics |
Evaluation officer |
Sebastian Lunke |
MCRI/VCGS |
Medical scientist |
Sze Chern Lim |
MCRI/VCGS |
Medical scientist |
Vanessa Kumar |
MCRI/VCGS |
Medical scientist |
Yael Prawer |
Melbourne Genomics |
Genetic counsellor |
1 Other eligibility criteria: patients who consented to be contacted for further research and are English-speaking. Not all eligible patients were approached.
2 A chat robot (‘chatbot’) is a computer program that uses artificial intelligence to simulate conversation. This rapidly emerging technology presents an opportunity to make better use of genetic counsellor time. As an adjunct to the AF study, a ‘trainee’ chatbot was developed and is in refinement (in conjunction with CSIRO) to augment genetic counselling for additional findings.