TY - JOUR
T1 - Long-term cost-effectiveness of a melanoma prevention program using genomic risk information compared with standard prevention advice in Australia
AU - Managing Your Risk Study Group
AU - Law, Chi Kin
AU - Cust, Anne E.
AU - Smit, Amelia K.
AU - Trevena, Lyndal
AU - Fernandez-Penas, Pablo
AU - Nieweg, Omgo E.
AU - Menzies, Alexander M.
AU - Wordsworth, Sarah
AU - Morton, Rachael L.
AU - Newson, Ainsley J.
AU - Kimlin, Michael
AU - Keogh, Louise
AU - Law, Matthew
AU - Kirk, Judy
AU - Dobbinson, Suzanne J.
AU - Kanetsky, Peter
AU - Mann, Graham
AU - Dawkins, Hugh
AU - Savard, Jacqueline
AU - Dunlop, Kate
AU - Jenkins, Mark
AU - Allen, Martin
AU - Butow, Phyllis
AU - Lo, Serigne
AU - Low, Cynthia
AU - Espinoza, David
N1 - Funding Information:
The study has been endorsed by the Melanoma and Skin Cancer Trials Group (ANZMTG 03.17). The authors would like to thank the people that participated in the Melanoma Genomics Managing Your Risk Study. The authors would like to thank Georgina Fenton, Gillian Reyes-Marcelino, Ashleigh Sharman, Lauren Humphreys, Ainsley Furneaux-Bate, and Rosa Evaquarta for assistance with the conduct of the study. This study was funded by an Australian National Health and Medical Research Council Project Grant #1129822 and CRE (1135285) and endorsed by Melanoma and Skin Cancer Trials (ANZMTG 03.17). Anne E. Cust was funded by fellowships from the NHMRC (#1147843 and #2008454). Amelia K. Smit received a Research Training Program (RTP) Stipend Scholarship and a Merit Top Up Scholarship from the University of Sydney and a Melanoma Institute Australia Postgraduate Research Scholarship. NHMRC Investigator Grant (#2009476) to Alexander M. Menzies. Support from Nicholas and Helen Moore and Melanoma Institute Australia to Alexander M. Menzies. Rachael L. Morton is funded through an NHMRC Investigator Grant (#1194703) and a University of Sydney Robinson Fellowship. No funding sources had any involvement in the study design, data collection, analysis, interpretation, publication, nor approval of the manuscript. Conceptualization: C.K.L. A.E.C. A.K.S. R.L.M.; Data Curation: A.K.S. A.E.C.; Formal Analysis: C.K.L. R.L.M.; Funding Acquisition: A.E.C. A.K.S. L.T. S.W. R.L.M.; Investigation: C.K.L. A.K.S. A.E.C. R.L.M.; Methodology: C.K.L. R.L.M.; Project Administration: A.K.S. A.E.C.; Resources: A.E.C.; Software: C.K.L.; Supervision: A.E.C. R.L.M.; Validation: A.K.S. A.E.C. R.L.M.; Visualization: C.K.L. R.L.M.; Writing-original draft: C.K.L. R.L.M.; Writing-review and editing: All authors. Ethical approval was obtained from the Human Research Ethics Committee at The University of Sydney (2017/163) and all participants gave informed consent. Data were de-identified for statistical analysis.
Funding Information:
This study was funded by an Australian National Health and Medical Research Council Project Grant #1129822 and CRE (1135285) and endorsed by Melanoma and Skin Cancer Trials (ANZMTG 03.17). Anne E. Cust was funded by fellowships from the NHMRC (#1147843 and #2008454). Amelia K. Smit received a Research Training Program (RTP) Stipend Scholarship and a Merit Top Up Scholarship from the University of Sydney and a Melanoma Institute Australia Postgraduate Research Scholarship. NHMRC Investigator Grant (#2009476) to Alexander M. Menzies. Support from Nicholas and Helen Moore and Melanoma Institute Australia to Alexander M. Menzies. Rachael L. Morton is funded through an NHMRC Investigator Grant (#1194703) and a University of Sydney Robinson Fellowship. No funding sources had any involvement in the study design, data collection, analysis, interpretation, publication, nor approval of the manuscript.
Publisher Copyright:
© 2023 American College of Medical Genetics and Genomics
PY - 2023/12
Y1 - 2023/12
N2 - Purpose: Evidence indicates that a melanoma prevention program using personalized genomic risk provision and genetic counseling can affect prevention behaviors, including reducing sunburns in adults with no melanoma history. This analysis evaluated its longer-term cost-effectiveness from an Australian health system perspective. Methods: The primary outcome was incremental cost effectiveness ratio (ICER) of genomic risk provision (intervention) compared with standard prevention advice. A decision-analytic Markov model was developed using randomized trial data to simulate lifetime cost-effectiveness. All costs were presented in 2018/19 Australian dollars (AUD). The intervention effect on reduced sunburns was stratified by sex and traditional risk, which was calculated through a validated prediction model. Deterministic and probabilistic sensitivity analyses were undertaken for robustness checks. Results: The per participant cost of intervention was AUD$189. Genomic risk provision targeting high-traditional risk individuals produced an ICER of AUD$35,254 (per quality-adjusted life year gained); sensitivity analyses indicated the intervention would be cost-effective in more than 50% of scenarios. When the intervention was extended to low-traditional risk groups, the ICER was AUD$43,746 with a 45% probability of being cost-effective. Conclusion: Genomic risk provision targeted to high-traditional melanoma risk individuals is likely a cost-effective strategy for reducing sunburns and will likely prevent future melanomas and keratinocyte carcinomas.
AB - Purpose: Evidence indicates that a melanoma prevention program using personalized genomic risk provision and genetic counseling can affect prevention behaviors, including reducing sunburns in adults with no melanoma history. This analysis evaluated its longer-term cost-effectiveness from an Australian health system perspective. Methods: The primary outcome was incremental cost effectiveness ratio (ICER) of genomic risk provision (intervention) compared with standard prevention advice. A decision-analytic Markov model was developed using randomized trial data to simulate lifetime cost-effectiveness. All costs were presented in 2018/19 Australian dollars (AUD). The intervention effect on reduced sunburns was stratified by sex and traditional risk, which was calculated through a validated prediction model. Deterministic and probabilistic sensitivity analyses were undertaken for robustness checks. Results: The per participant cost of intervention was AUD$189. Genomic risk provision targeting high-traditional risk individuals produced an ICER of AUD$35,254 (per quality-adjusted life year gained); sensitivity analyses indicated the intervention would be cost-effective in more than 50% of scenarios. When the intervention was extended to low-traditional risk groups, the ICER was AUD$43,746 with a 45% probability of being cost-effective. Conclusion: Genomic risk provision targeted to high-traditional melanoma risk individuals is likely a cost-effective strategy for reducing sunburns and will likely prevent future melanomas and keratinocyte carcinomas.
UR - http://www.scopus.com/inward/record.url?scp=85174458908&partnerID=8YFLogxK
U2 - 10.1016/j.gim.2023.100970
DO - 10.1016/j.gim.2023.100970
M3 - Article
C2 - 37658729
AN - SCOPUS:85174458908
SN - 1098-3600
VL - 25
JO - Genetics in Medicine
JF - Genetics in Medicine
IS - 12
M1 - 100970
ER -